{"id":2325,"date":"2014-06-08T12:48:45","date_gmt":"2014-06-08T03:48:45","guid":{"rendered":"http:\/\/www.is.doshisha.ac.jp\/news\/?p=2325"},"modified":"2014-06-08T12:48:45","modified_gmt":"2014-06-08T03:48:45","slug":"ohbm2014","status":"publish","type":"post","link":"https:\/\/is.doshisha.ac.jp\/news\/?p=2325","title":{"rendered":"OHBM2014"},"content":{"rendered":"

2014\u5e746\u67088\u65e5~12\u65e5\u306b\u304b\u3051\u3066\uff0c\u30c9\u30a4\u30c4\u306e CCH-Congress Center in
\nHamburg\u306b\u3066\u958b\u50ac\u3055\u308c\u305fOHBM2014\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\uff0c\u5c71\u672c\u5148\u751f\uff0c\u6a2a\u5185\u5148\u751f\uff0c\u6728\u6751\u831c\uff08M2\uff09\uff0c\u6749\u7530\u51fa\u5f25\uff08M2\uff09\uff0c\u5c07\u7a4d\u5f69\u82bd\uff08M2\uff09\uff0c\u5f8c\u85e4\u771f\u6afb\uff08M2\uff09\uff0c\u65e9\u5ddd\u6e29\u5b50\uff08M2\uff09\u306e7\u540d\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3057\u305f\uff0e\u767a\u8868\u984c\u76ee\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\uff0e
\n\u300cThe differences of changing task difficulties on brain activities
\nbetween high and low score groups\u300d\u6749\u7530\u51fa\u5f25
\n\u300cImpact of the different degree of attention to the auditory and
\nvisual stimuli\u300d\u6728\u6751\u831c
\n\u300cGender difference in performance and brain function during memorizing
\ntask under influence of sound\u300d\u5c07\u7a4d\u5f69\u82bd
\n\u300cA study of multiple brain activities during cooperative work by
\nsimultaneous fNIRS measurements\u300d\u5f8c\u85e4\u771f\u6afb
\n\u300cExamination of the proficiency level on skill acquisition using
\ncerebral blood flow changes\u300d\u65e9\u5ddd\u6e29\u5b50
\n\u7121\u4e8b\u306b5\u540d\u3068\u3082\u767a\u8868\u3092\u7d42\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e2\u5ea6\u76ee\u306e\u56fd\u969b\u5b66\u4f1a\u3060\u3063\u305f\u3053\u3068\u3082\u3042\u308a\uff0c\u521d\u3081\u3066\u306e\u56fd\u969b\u5b66\u4f1a\u3088\u308a\u306f\uff0c\u7dca\u5f35\u3059\u308b\u3053\u3068\u3082\u306a\u304f\u767a\u8868\u3067\u304d\u305f\u3068\u601d\u3044\u307e\u3059\uff0e\u30dd\u30b9\u30bf\u30fc\u306b\u306f\u305d\u308c\u305e\u308c\u4f55\u4eba\u304b\u306e\u65b9\u304c\u8db3\u3092\u904b\u3093\u3067\u4e0b\u3055\u308a\uff0c\u8cb4\u91cd\u306a\u8cea\u554f\u3084\u610f\u898b\u3092\u9802\u304f\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3068\u3066\u3082\u6709\u610f\u7fa9\u306a\u6642\u9593\u3092\u904e\u3054\u3059\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u3067\u9802\u3044\u305f\u8cea\u554f\u3084\u610f\u898b\u3092\u30e2\u30c1\u30d9\u30fc\u30b7\u30e7\u30f3\u3068\u3057\uff0c\u3053\u308c\u304b\u3089\u3082\u7814\u7a76\u306b\u52b1\u3093\u3067\u3044\u304d\u307e\u3059\uff0e
\n\u30c9\u30a4\u30c4\u306e\u30cf\u30f3\u30d6\u30eb\u30af\u306f\u6cbb\u5b89\u3082\u826f\u304f\uff0c\u591c8\u6642\u9803\u307e\u3067\u7a7a\u3082\u660e\u308b\u304b\u3063\u305f\u305f\u3081\u9577\u3044\u6642\u9593\u5b66\u4f1a\u3078\u306e\u53c2\u52a0\u3084\u89b3\u5149\u3092\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e
\n\u5b66\u4f1a\u53c2\u52a0\u306b\u3042\u305f\u308a\uff0c\u3054\u6307\u5c0e\u304f\u3060\u3055\u3063\u305f\u5148\u751f\u65b9\uff0c\u307e\u305f\u30ea\u30cf\u30fc\u30b5\u30eb\u306b\u53c2\u52a0\u3057\u3066\u8cea\u554f\u3084\u610f\u898b\u3092\u304f\u3060\u3055\u3063\u305f\u7814\u7a76\u73ed\u3084\u7814\u7a76\u5ba4\u306e\u7686\u69d8\u672c\u5f53\u306b\u3042\u308a\u304c\u3068\u3046\u3054\u3056\u3044\u307e\u3057\u305f\uff0e\u4eca\u5f8c\u3068\u3082\u3054\u6307\u5c0e\uff0c\u3054\u97ad\u64bb\u306e\u7a0b\u5b9c\u3057\u304f\u304a\u9858\u3044\u81f4\u3057\u307e\u3059\uff0e
\n\"10433199_645875792169398_221463249735913244_n\"\"P1050534\"\"P1050626\"<\/a>
\n\u3010\u6587\u8cac\uff1aM2 \u65e9\u5ddd\u3011
\n
\n\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n\u5f8c\u85e4\u771f\u6afb<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nfNIRS\u540c\u6642\u8a08\u6e2c\u306b\u3088\u308b\u5354\u8abf\u4f5c\u696d\u6642\u306e\u8907\u6570\u4eba\u8133\u6d3b\u52d5\u306e\u691c\u8a0e<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nA study of multiple brain activities during cooperative work by simultaneous fNIRS measurement<\/td>\n<\/tr>\n
\u8457\u8005<\/strong><\/td>\n\u5c71\u672c\u8a69\u5b50, \u5f8c\u85e4\u771f\u6afb, \u6a2a\u5185\u4e45\u731b, \u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/strong><\/td>\nOrganization for Human Brain Mapping<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nOHBM 2014 Annual Meeting<\/td>\n<\/tr>\n
\u4f1a\u5834<\/strong><\/td>\nCCH-Congress Center Hamburg<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2014\/6\/8-2014\/6\/12<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n 
\n1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30
\n2014\/6\/8\u304b\u30892014\/6\/12\u306b\u304b\u3051\u3066\uff0c\u30c9\u30a4\u30c4\u30fb\u30cf\u30f3\u30d6\u30eb\u30b0\u306eCCH (Congress Center Hamburg)\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fOHBM 2014 Annual Meeting\u3000(http:\/\/www.humanbrainmapping.org\/i4a\/pages\/index.cfm?pageid=3565<\/a>)\u3000\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306eOHBM Annual Meeting\u306f\uff0cOrganization for Human Brain Mapping (OHBM)\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u308b\u4f1a\u8b70\u3067\uff0c\u4eba\u9593\u306e\u6a5f\u80fd\u7684\u795e\u7d4c\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u306e\u5206\u91ce\u306b\u304a\u3051\u308b\u5927\u304d\u306a\u767a\u5c55\u3068\u305d\u308c\u3089\u306e\u79d1\u5b66\u306e\u4e3b\u6d41\u3078\u306e\u52d5\u304d\u306e\u305f\u3081\u306b\uff0c\u8133\u306e\u30de\u30c3\u30d4\u30f3\u30b0\u306e\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u3092\u63d0\u4f9b\u3059\u308b\u5927\u304d\u306a\u7d44\u7e54\u306e\u4e00\u3064\u306b\u767a\u5c55\u3057\uff0c\u4eba\u9593\u306e\u8133\u30de\u30c3\u30d4\u30f3\u30b0\u3092\u7814\u7a76\u5bfe\u8c61\u3068\u3059\u308b\u69d8\u3005\u306a\u30e2\u30c0\u30ea\u30c6\u30a3\u3092\u7528\u3044\u305f\u6700\u65b0\u304b\u3064\u9769\u65b0\u7684\u306a\u7814\u7a76\u306e\u60c5\u5831\u306e\u3084\u308a\u3068\u308a\u3092\u884c\u3046\u6559\u80b2\u7684\u306a\u30d5\u30a9\u30fc\u30e9\u30e0\u3092\u63d0\u4f9b\u3057\u307e\u3059\uff0e
\n\u79c1\u306f8\uff0c9\uff0c10, 12\u65e5\u306b\u53c2\u52a0\u3057\uff0c10\u65e5\u306b\u767a\u8868\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5c71\u672c\u5148\u751f\uff0c\u65e9\u5ddd\uff0c\u6728\u6751\uff0c\u5c07\u7a4d\uff0c\u6749\u7530\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
\n 
\n2. \u7814\u7a76\u767a\u8868
\n2.1. \u767a\u8868\u6982\u8981
\n\u79c1\u306fPoster session\u306e\u3046\u3061\uff0cMain Category: Imaging Methods\uff0cSub Category: Optical Imaging\/NIRS\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\uff0c\u6307\u5b9a\u3055\u308c\u305f\u6642\u9593(2\u6642\u9593)\u3067\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3057\u305f\uff0e
\n\u4eca\u56de\u306e\u767a\u8868\u306e\u6284\u9332\u3092\u4ee5\u4e0b\u306b\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
\u3010Introduction\u3011Social interaction is important for us to live our lives and a topic to attract attention in the field of brain science in recent years. In this area of research, particularly cooperative work is a focus. Cooperative work needs sharing timing. Miyake et al.(2004) investigated the mechanisms of timing control but haven\u2019t done research on brain activity on this occasion. We research interpersonal brain activities during cooperative work in our study. To approach this goal, we have two steps; a Human-Machine system as the first step and a Human-Human system as the second step. To investigate process of interactive shared timing which becomes the basis of human communication, we examine brain activities of two subjects who perform a synchronized cooperative tapping task based on previous study (Kon et al. 2006).\u3010Methods\u3011The synchronized cooperative tapping task requires two subjects. One of paired subjects move his\/her finger in synchronization with an auditory stimulus produced by the other\u2019s tapping in this task. They move their finger in synchronization with rhythmic tapping given by each other for 150 seconds. Seven healthy women (4 pairs; age: 23 years; right-handed) participated in this study. We focused on inferior frontal gyrus (IFG) and superior frontal gyrus (SFG) as region of interest (ROI), and measured cerebral blood flow changes using fNIRS. We had a questionnaire called KiSS-18 which is one of psychological indexes to evaluate social skills after experiments and developed by Kikuchi (2004). Kikuchi extracted three factors from KiSS-18; problem solution skill, trouble management skill and communication skill.\u3010Results\u3011
\nWe marked their task performances using synchronization error (SE) which is an interval between time of presented auditory stimulus and button press action. We calculated averages of SE in all subjects. Figure 1 shows differences of the averages of SE between both subjects in each pair. We focus on Pair 4 because they have the largest difference in all pairs. It indicates that they carried out task taking roles as leader and follower respectively. We estimated relationship between cerebral blood flow changes of both subjects using correlation coefficients. The values of correlation coefficients were 0.83 at CH14 and 19 in right SFG and 0.73 at CH18 and 22 in left SFG. Both subjects of Pair 4 have large scores of communication skill, which is a factor of KiSS-18, in all subjects and there was the smallest difference between the scores. It is reported that SFG have the function of predicting the behavior of another person (Cui, 2012). It is suggested that two subjects of Pair 4 perform the synchronized cooperative tapping task paying attention to movement of each other because their SFGs functioned as mentioned above from the results of large correlation coefficients.
\n\u3010Conclusion\u3011
\nIn order to investigate brain activities when two people work cooperatively, we carried out fNIRS experiment using synchronized cooperative tapping task at Human-Human system. We used KiSS-18 to evaluate social skill. Based on the score of tapping, we focused on a pair because their task performance suggested sharing roles. As the result, the correlation coefficients of their cerebral blood flow changes in SFG showed large values and their scores of communication skill were large and in the same range. Therefore, it is suggested that a pair who have large score of communication skill perform action with predicting the behavior of each other. Further consideration will be needed to yield any findings about a pair whose scores of communication skill are in the same range but small.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n2.2. \u8cea\u7591\u5fdc\u7b54
\n\u4eca\u56de\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u554f\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
\n\u30fb\u306a\u305cMRI\u3067\u306f\u306a\u304fNIRS\u3092\u7528\u3044\u3066\u3044\u308b\u306e\u304b\uff0e
\n\u2192Graduate School of Science and Technology, Keio University\u306eMidori Kodama\u3055\u3093\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u7b54\u3048\u306f\uff0c\u793e\u4f1a\u7684\u306a\u76f8\u4e92\u4f5c\u7528\u306e\u898b\u3089\u308c\u308b\u65e5\u5e38\u751f\u6d3b\u3092\u518d\u73fe\u3067\u304d\u308b\u74b0\u5883\u4e0b\u3067\u5b9f\u9a13\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u308b\u306e\u306fNIRS\u3067\u3042\u308b\u305f\u3081MRI\u3067\u306f\u306a\u304fNIRS\u3092\u7528\u3044\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u9818\u57df\u3092\u5b9a\u3081\u3066\u3057\u307e\u3046\u306e\u3067\u306f\u306a\u304f\u5168\u4f53\u3092\u898b\u305f\u3089\u3088\u3044\u306e\u3067\u306f\u306a\u3044\u304b\uff0e
\n\u2192\u3053\u3061\u3089\u3082Graduate School of Science and Technology, Keio University\u306eMidori Kodama\u69d8\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\uff0c\u8cea\u554f\u306e\u901a\u308a\u9818\u57df\u306e\u518d\u691c\u8a0e\u3092\u3059\u308b\u4e88\u5b9a\u3067\u3042\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u3069\u3046\u3084\u3063\u3066\u9818\u57df\u3092\u5b9a\u3081\u305f\u306e\u304b\uff0e
\n\u2192\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\uff0c\u4eba-\u6a5f\u68b0\u30b7\u30b9\u30c6\u30e0\u306b\u304a\u3044\u3066\u7740\u76ee\u9818\u57df\u3092\u5b9a\u3081\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u30bf\u30b9\u30af\u304c\u59cb\u307e\u3063\u305f\u6642\u306b\u5148\u306b\u53e9\u304d\u59cb\u3081\u308b\u4eba\u304cleader\u306a\u306e\u304b\uff0e
\n\u2192\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\uff0c\u5b9f\u9a13\u304c\u59cb\u307e\u308b\u524d\u306bleader \/ follower\u306f\u6307\u5b9a\u3057\u3066\u306a\u3044\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u30bf\u30b9\u30af\u306b\u3064\u3044\u3066\u3082\u3046\u5c11\u3057\u8a73\u3057\u304f\u6559\u3048\u3066\u307b\u3057\u3044\uff0e
\n\u2192\u81ea\u6cbb\u533b\u79d1\u5927\u5b66\u306e\u5b87\u8cc0\u69d8\uff0cPusan National University\u306eMuhammad Raheel Bhutta\u69d8\uff0cDepartment of Physics, Ryerson University\u306eMartin Merener\u69d8\uff0c\u3042\u3068\u3082\u3046\u4e00\u4eba\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\u304c\uff0c\u8a084\u540d\u306e\u65b9\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\uff0c\u79c1\u306f\u30bf\u30b9\u30af\u306e\u8a73\u7d30\u306b\u3064\u3044\u3066\u3082\u3046\u4e00\u5ea6\u8aac\u660e\u3057\u76f4\u3057\u307e\u3057\u305f\uff0e\u305d\u306e\u5834\u3067\u5b9f\u969b\u306b\u540c\u671f\u5354\u8abf\u30bf\u30c3\u30d4\u30f3\u30b0\u3092\u5b9f\u8df5\u3059\u308b\u3053\u3068\u3067\u7406\u89e3\u3092\u6df1\u3081\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e
\n 
\n\u30fbNIRS\u306e\u539f\u7406\u306b\u3064\u3044\u3066\u6559\u3048\u3066\u307b\u3057\u3044\uff0e
\n\u2192Department of Physics, Ryerson University\u306eMartin Merener\u69d8\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u7b54\u3048\u306f\uff0c\u7167\u5c04\u30d7\u30ed\u30fc\u30d6\u3068\u53d7\u5149\u30d7\u30ed\u30fc\u30d6\u3092\u982d\u76ae\u306e\u4e0a\u306b\u8a2d\u7f6e\u3057\u8fd1\u8d64\u5916\u5149\u3092\u4f7f\u3063\u3066\u8133\u8840\u6d41\u3092\u8a08\u6e2c\u3059\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u5ba4\u5185\u306e\u5149\u74b0\u5883\u306b\u3088\u3063\u3066\u3082\u8133\u8840\u6d41\u306f\u5909\u5316\u3059\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fbKiSS-18\u306b\u3064\u3044\u3066\u6559\u3048\u3066\u307b\u3057\u3044\uff0e
\n\u2192\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u307e\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\uff0c\u79c1\u306fKiSS-18\u306e\u5b9a\u7fa9\u306b\u3064\u3044\u3066\u3082\u3046\u4e00\u5ea6\u8aac\u660e\u3057\u307e\u3057\u305f\uff0e
\n 
\n 
\n2.3. \u611f\u60f3
\n2\u56de\u76ee\u306e\u56fd\u969b\u5b66\u4f1a\u3078\u306e\u53c2\u52a0\u3067\u3057\u305f\u304c\uff0c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\u521d\u3081\u3066\u3067\u3042\u3063\u305f\u305f\u3081\uff0c\u81ea\u5206\u306e\u30dd\u30b9\u30bf\u30fc\u306e\u524d\u3092\u901a\u308b\u4eba\u306b\u3069\u306e\u3088\u3046\u306b\u3057\u3066\u81ea\u5206\u306e\u7814\u7a76\u3092\u805e\u3044\u3066\u3082\u3089\u3046\u304b\u82e6\u52b4\u3057\u307e\u3057\u305f\uff0e\u30dd\u30b9\u30bf\u30fc\u306b\u6765\u3066\u304f\u3060\u3055\u3063\u305f\u4eba\u306e\u4e2d\u3067\u6570\u4eba\u65e5\u672c\u4eba\u306e\u65b9\u304c\u304a\u308a\uff0c\u65e5\u672c\u8a9e\u3067\u8aac\u660e\u3057\u3066\u3057\u307e\u3046\u3053\u3068\u3082\u3042\u308a\u307e\u3057\u305f\u304c\uff0c\u4ed6\u306e\u65b9\u306b\u306f\u3057\u3063\u304b\u308a\u3068\u8cea\u554f\u306b\u5bfe\u3057\u3066\u82f1\u8a9e\u3067\u56de\u7b54\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u30c7\u30fc\u30bf\u51e6\u7406\u306b\u3064\u3044\u3066\u660e\u6cbb\u5927\u5b66\u306eTakuro Zama\u69d8\u3088\u308a\u3054\u610f\u898b\u3092\u3044\u305f\u3060\u304d\uff0c\u4eca\u5f8c\u306e\u7814\u7a76\u306b\u6d3b\u304b\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n\u4ed6\u306e\u30aa\u30fc\u30e9\u30eb\u30bb\u30c3\u30b7\u30e7\u30f3\u306e\u767a\u8868\u3084\u30dd\u30b9\u30bf\u30fc\u3082\u8074\u8b1b\u3057\u307e\u3057\u305f\u304c\uff0c\u540c\u3058\u5206\u91ce\u306e\u7814\u7a76\u304c\u96c6\u307e\u308b\u5b66\u4f1a\u306f\uff0c\u4ed6\u306e\u4eba\u306e\u89e3\u6790\u65b9\u6cd5\u3082\u3068\u3066\u3082\u53c2\u8003\u306b\u306a\u308a\uff0c\u5145\u5b9f\u3057\u305f\u5b66\u4f1a\u53c2\u52a0\u3068\u306a\u308a\u307e\u3057\u305f\uff0e\u3082\u3063\u3068\u82f1\u8a9e\u304c\u7406\u89e3\u3067\u304d\u308c\u3070\u3088\u308a\u7406\u89e3\u3082\u6df1\u307e\u3063\u305f\u3060\u308d\u3046\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n 
\n3. \u8074\u8b1b
\n\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e3\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a A Near infrared spectroscopy study on Subliminal Perception\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Kazumasa Shimizu\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a OPTICAL IMAGING \/ NIRSAbstract\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/strong>In this research, the language stimulation which consists of a Chinese character of two characters was shown in presentation time on a threshold called 33msec which is near a subjective threshold value and they are under a differential threshold, and 200msec and 600msec, and the reconfirmation examination was done after that.
\nAs a result, even if it was under the condition which cannot discriminate from a stimulus, in the reconfirmation examination, high results were acquired more nearly intentionally than a chance level.
\nMoreover, at the time of presentation of language stimulation, NIRS which is a non-invading cerebral function measuring device was installed in the right-and-left both sides of the head centering on the Broca field, and cerebral activity was measured.
\nAs a result, it was suggested by changing the presentation time of language stimulation that cerebral activity time changes intentionally.
\nMethods:<\/strong>
\nNIRS(ETG-7000, Hitachi-Medico) was used for cerebral function measurement.
\nThe presentation procedure of a stimulus is as follows.
\n500msec presentation of the point of regard is carried out in introduction and middle of the screen.
\nNext, the masking pattern of 100msec is shown.
\nThen, a word stimulus is shown, and a masking pattern is shown again continuously.
\nUnder the present circumstances, the masking pattern shown to the 2nd times reverses black and white of the thing shown at a time.
\nRandom presentation of the word stimulus was carried out any of the stimulus presentation part installed in four less than 5-degree places from the center of a view they are.
\nThe presentation time of the word was 33msec, 200msec or 600msec, or blank presentation (presentation-less conditions) of 33msec.
\nThe presentation time of the masking pattern shown to the 2nd times was the time which pulled the presentation time of the word from 800msec.
\nWhen a blank was shown, the masking pattern carried out 767msec presentation.
\nResults:<\/strong>
\nWhen a reconfirmation test was done, while the number of presentation of the word of each presentation conditions was 25 pieces, in consideration of the number of presentation of the word which was not shown having been 75 pieces, the t test was performed between what set the results of the presentation-less condition group to one third, and other presentation groups.
\nAs a result, on 33msec conditions, in p= 0.01587 (<0.05) and 200msec conditions, it was set to p= 0.00003 (<0.05) and it was suggested by p= 0.03231 (<0.05) and 600msec conditions that there is a difference in the number of a presentation-less condition group and each of other group intentionally.
\nOn the other hand, In cerebral function measurement, the significant difference was mainly detected in the left Broca field, especially between 600msec conditions and 200msec conditions. However, a significant difference was not seen between 33msec conditions and 0msec conditions.
\nConclusions:<\/strong>
\nIn this research, language stimulation was shown to the participant on a subliminal condition and supraliminal conditions using the subjective threshold value.
\nAs a result, in the reconfirmation examination, the significant difference was seen between subliminal conditions and presentation-less conditions.
\nThis result supports the hypothesis that a stimulus of a subliminal may be recognized.
\nMoreover, from the measurement result of the brain activity at the time of language stimulation presentation, the significant difference was able to be found out among 2 conditions used as supraliminal conditions.
\nThis can be said to be being the result of suggesting that a certain relationship exists between the presentation time of language stimulation, and cerebral activity time.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\uff0c\u30b5\u30d6\u30ea\u30df\u30ca\u30eb\u52b9\u679c\u3092\u5229\u7528\u3057\u305f\u5b9f\u9a13\u3067\u3057\u305f\uff0e2\u3064\u306e\u5f37\u3044\u523a\u6fc0\u63d0\u793a\u306e\u9593\u306b0msec, 33msec, 200msec, 600msec\u306e\u5225\u306e\u523a\u6fc0\u753b\u50cf\u3092\u633f\u5165\u3057\u305f\u6642\u306b\u305d\u306e\u753b\u50cf\u3092\u8a8d\u8b58\u3067\u304d\u305f\u304b\u3069\u3046\u304b\u3092fNIRS\u3092\u7528\u3044\u3066\u8a08\u6e2c\u3057\u305f\u3082\u306e\u3067\u3057\u305f\uff0e\u6b63\u7b54\u7387\u3068\u3057\u3066\u306f\uff0c33msec\u306e\u3068\u304d\u304c\u826f\u304b\u3063\u305f\u304c\uff0c\u8133\u8840\u6d41\u306b\u306f\u5f71\u97ff\u3055\u308c\u3066\u306a\u304b\u3063\u305f\u305d\u3046\u3067\u3059\uff0e\u305d\u306e\u7406\u7531\u3068\u3057\u3066\u306f\uff0c\u8133\u3067\u8a8d\u8b58\u3059\u308b\u524d\u306b\u6d3b\u6027\u3057\u3066\u306a\u3044\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3044\u3046\u306e\u304c\u7b46\u8005\u306e\u8003\u3048\u3067\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Extended social-affective default network: altered connectivity in depression\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMaren Amft, Danilo Bzdok, Oliver Gruber, Roberto Goya-Maldonado, Christian Sorg, Valentin Riedl, Veronika M\u00fcller, Simon Eickhoff\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a MOOD AND ANXIETY DISORDERSAbstract\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/strong>
\nThe “default mode network” is not only a highly reliable resting-state network but has moreover been associated with experimental tasks, including social and affective processing (1,2,3). A recent combination of meta-analyses and network modeling then revealed an extended social-affective default (eSAD) network. The eSAD consists of regions that are i) part of the default mode and involved in either social cognition or emotional processing or ii) strongly connected to the formed (figure 1). Dysfunctions in the DMN were already described in individuals with major depressive disorder (MDD) (4). Most previous work, however, focused on within network dys-connectivity, ignoring aberrant interactions with non-DMN regions. We therefore investigated whether eSAD regions exhibit altered connectivity to regions outside the “default mode” in MDD.
\nMethods:<\/strong>
\nWe compared whole brain resting state connectivity between 106 MDD patients and 106 age-, gender- and movement-matched healthy controls. First, we compared functional connectivity within the eSAD network between MDD patients and controls. In another analysis, we computed the significant differences in whole-brain functional connectivity increases and decreases between the two groups seeding from each of the eSAD regions. We then identified those brain regions that show significant alternations in connectivity to at least two individual eSAD regions (p<0.05, cluster-level FWE corrected). We thus identified brain regions robustly dys-connected with multiple eSAD regions. We then performed quantitative functional decoding using the BrainMap database to identify the mental processes associated with the regions featuring dys-connectivity with the eSAD network in MDD.
\nResults:<\/strong>
\nIn general, we found a significant hyper-connectivity among eSAD regions, i.e., regions related to social, affective and introspective processes, in patients with MDD. Our whole brain analysis moreover revealed a set of seven brain regions, which were robustly dys-connected with several eSAD regions: the medial superior parietal lobe (mSPL) was the only region showing consistently higher connectivity with the eSAD. The supplementary motor area (SMA), right dorsal premotor cortex (dPMC), bilateral inferior frontal junction (IFJ) and the bilateral intra-parietal sulcus (IPS, extending to the inferior parietal lobule on the right), in turn, showed consistently lower connectivity with multiple eSAD regions (Figure 2). Importantly, all of these regions were negatively coupled with the eSAD in healthy controls. Functional decoding related the consistently hyper-connected mSPL region to explicit memory processes (e.g. episodic memory). The SMA, dPMC, IFJ and IPS (i.e. those regions showing increased anti-correlation with several eSAD regions in patients) were associated with attentional, executive and cognitive processes.
\nConclusions:<\/strong>
\nOur findings indicate an increased antagonism between social-affective-introspective and externally oriented attentional-cognitive brain regions in MDD. This might suggest decreased flexibility in the switching between these. Given that the eSAD regions are also hyper-connected, MDD patients might be locked in the affective-introspective mental state. The increased integration of a memory-relevant region into this network fits this view and relates well to the clinical symptoms of ruminations. Ruminations and debilitated attention in MDD may thus both relate to a) an increased coupling within introspective-affective regions (eSAD), b) stronger interaction of eSAD regions and memory related regions in the mSPL and c) more pronounced anti-correlations of eSAD regions with lateral fronto-parietal regions related to attention and executive functions. Patients with MDD might hence be “caught” in introspective, memory-centered thoughts about emotion, themselves and other people preventing recruitment of pertinent cognitive functions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\uff0cDefault Mode Network\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3057\u305f\uff0e\u5065\u5e38\u8005\u3068\u60a3\u8005\u306b\u5206\u985e\u3059\u308b\u3068\uff0cmSPL\u304c\u60a3\u8005\u306b\u3060\u3051\u7279\u6709\u306eDMN\u3060\u3068\u5224\u660e\u3057\u305f\u3068\u306e\u8aac\u660e\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e\u3053\u306e\u767a\u8868\u8005\u306b\u8cea\u554f\u3092\u3059\u308b\u3068\u4e01\u5be7\u306b\u8aac\u660e\u3057\u3066\u304f\u308c\u5206\u304b\u308a\u3084\u3059\u304b\u3063\u305f\u3067\u3059\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSocial Brain Network and Autism Spectrum Disorder: Reduced Connectivity to the Frontal Cortex\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Elgin Hoffmann, Carolin Br\u00fcck, Benjamin Kreifelts, Thomas Ethofer, Dirk Wildgruber\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Disorders of the Nervous System \/ AutismAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/strong>
\nSubjects with autism spectrum disorder (ASD) consistently present with difficulties in social interaction and the correct interpretation of social cues. However, underlying neural correlates remain yet to be clarified. Building on previous research, we presumed that in subjects with ASD social impairments might be associated with decreased activation and coupling of key regions of the social brain network (Ref. 7). In our study we examined ASD-related differences in the activation and connectivity of brain areas involved in the processing of facial, vocal and audiovisual social signals (i.e. fusiform face area (FFA), temporal voice area (TVA), and amygdala; Ref. 6, 2, 8).
\nMethods:<\/strong>
\n30 adult volunteers (10 subjects with ASD, 20 typically developed (TD) control subjects) participated in the study. Data was obtained using a 3T scanner (Siemens TRIO, BOLD-fMRI, 2D-EPI sequence: TR=1700 ms, TE=30 ms, 30 slices, 4mm thickness + 1 mm gap). Three well established functional blocked-design localizers were used to define brain areas commonly involved in the processing of facial, vocal, and audiovisual social signals. The voice-localizer contained sounds of human voices, animal sounds, and environmental sounds. The face-localizer showed houses, landscape scenes, objects, and faces, whereas the audio-visual localizer presented participants either with videos (AV), muted videos (V), or sound recordings (A) of people speaking (Ref. 4, 5).
\nData was analyzed using SPM8. Preprocessing steps included unwarping, realignment, coregistration with anatomical images, segmentation, normalization, and smoothing. First, differences between TD controls and ASD subjects were explored by comparing activation pattern between groups (ASD vs. TD). In a second step, different psychophysiological interaction (PPI) analyses aimed at identifying brain regions showing altered connectivity with different nodes of the social brain (Fig.1) were used to infer group differences in the connectivity:
\nPPI Voices: Aimed at locating brain regions showing an increased connectivity with voice-sensitive brain regions during the processing of voices as compared to animal or environmental sounds.
\nPPI Faces: Aimed at determining brain regions of enhanced connectivity with face-sensitive brain regions during the perception of faces as compared to houses, scenes, or objects.
\nPPI Audiovisual: Conducted to locate brain regions showing an enhanced connectivity with audiovisual processing areas during the perception of audiovisual as compared to unimodal social signals.
\nFor both steps statistical thresholds were set at a height threshold of p\u22640.01 and a cluster-wise significance level of p<0.05 corrected for multiple comparisons. ROI analyses were based on activation patterns of TD subjects.
\nResults:<\/strong>
\nWhile the activation analysis yielded no significant differences between ASD and TD subjects, significant group differences were observed with respect to brain connectivity:
\n– PPI Voices revealed a decreased connectivity between the right TVA and the superior medial frontal cortex (bilateral) for the ASD subjects compared to TD subjects.
\n– PPI Faces indicated a decreased connectivity between the right amygdala and the left inferior frontal cortex in the ASD group.
\n– PPI Audiovisual yielded no significant alterations in connectivity.
\n– No analysis found increased connectivity in ASD subjects as compared to TD.
\nConclusions:<\/strong>
\nIn ASD patients we found reduced connectivity of voice- and face-sensitive areas with frontal brain structures known to be involved in social cognitive processes such as mentalizing and evaluating social information (Ref. 3, 1). Future research should aim to clarify, however,\u00a0whether the observed\u00a0decreased cerebral connectivity should rather be considered the cause or the consequence of impaired social interactions in ASD.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u7814\u7a76\u306f\uff0c\u5065\u5e38\u8005\u3068\u81ea\u9589\u75c7\u60a3\u8005\u306b\u5206\u985e\u3057\u3066\uff0c\u8133\u5185\u306e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u3064\u3044\u3066\u8abf\u67fb\u3057\u305f\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u767a\u8868\u8005\u306b\u3088\u308b\u3068\uff0c\u5065\u5e38\u8005\u306f\u524d\u982d\u90e8\u3068\u306econnection\u304c\u3042\u3063\u305f\u304c\uff0c\u81ea\u9589\u75c7\u60a3\u8005\u306f\u524d\u982d\u90e8\u3068\u306econnection\u304c\u306a\u304b\u3063\u305f\u3068\u306e\u3053\u3068\u3067\u3059\uff0e\u305d\u306e\u7406\u7531\u3068\u3057\u3066\uff0c\u81ea\u9589\u75c7\u60a3\u8005\u306e\u4eba\u306f\u793e\u4f1a\u8a8d\u77e5\u80fd\u529b\u304c\u6b20\u5982\u3057\u3066\u3044\u308b\u305f\u3081\u3053\u306e\u3088\u3046\u306a\u7d50\u679c\u306b\u306a\u3063\u305f\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u8003\u5bdf\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u3053\u306e\u767a\u8868\u8005\u306fPPI\u3068\u3044\u3046\u79c1\u304c\u30a2\u30c9\u30d0\u30a4\u30b9\u3092\u53d7\u3051\u305f\u89e3\u6790\u624b\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3057\u305f\uff0eNIRS\u306b\u3082\u9069\u7528\u3067\u304d\u308b\u304b\u5c0b\u306d\u305f\u3068\u3053\u308d\uff0c\u96e3\u3057\u3044\u304b\u3082\u3057\u308c\u306a\u3044\u304c\u6311\u6226\u3057\u3066\u307f\u3066\u3082\u826f\u3044\u304b\u3082\u3057\u308c\u306a\u3044\u3068\u306e\u610f\u898b\u3092\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Prediction of leadership based on inter-brain synchronization\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Jing Jiang, Bohan Dai, Guang Shi, Wen Miao, Katharina von Kriegstein, Chunming Lu\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Social Neuroscience \/ Social CognitionAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/strong>
\nHumans are highly social animals and human societies are characterized by different types of relationships between individuals. Over human evolution, leader-follower relationships have played an important role in the survival and proliferation for the whole species (Van Vugt & Ahuja, 2010). However, it is not yet clear what neural mechanisms are involved in leader-follower and follower-follower relationships. The aim of the current study was to examine the neural features of leader-follower and follower-follower relationships. To do this we used functional near infra-red spectroscopy (fNIRS)- a very convenient neuroimaging technique to simultaneously measure brain activity of multiple individuals in natural environments during face-to-face communication (Cui, Bryant, & Reiss, 2012; Jiang et al., 2012).
\nMethods:<\/strong>
\nWe recruited twelve groups of healthy adults (mean age: 22\u00b12, 5 female groups and 6 male groups). Each group consisted of 3 persons who were not familiar with each other. The brain activity of the 3 persons was simultaneously measured with fNIRS. First, we acquired a resting state measurement (5 minutes). After this, the 3 persons had the task to discuss a topic that was suggested by the experimenter. The discussion was stopped after 5 minutes by the experimenter. The optode probe set was placed on the frontal, temporal, and parietal cortices of the left hemisphere. After the experiments, 8 independent raters with a psychology bachelor degree watched the videos and rated them according to a questionnaire about leadership skills. They then voted one suitable person of each group as the leader. Wavelet transform coherence (WTC) was used to calculate the coherence between two persons’ brain time series.
\nResults:<\/strong>
\nThe average vote rate for the leaders was 77.27%. A significant interaction effect between conditions (discussion, resting state) and relationships (leader-follower, follower-follower) was found in CH6 which covered the left temporo-parietal junction (TPJ) (F=12.29, p=0.002). During the discussion task, the coherence value was significantly higher for leader-follower (LF) relationship than for follower-follower relationship (FF) (F=5.01, p=0.037); while during the resting state, the two relationships showed the reverse pattern (F=11.67, p=0.003). CH6 also showed higher coherence increase for the discussion task as compared to the resting state for LF relationships (t(10)=4.624, p=0.001) but not for FF relationships (t(10)=-1.537, p=0.155). The difference between them was also significant (t(20)=3.506, p=0.002).
\nConclusions:<\/strong>
\nThe present findings indicate that the inter-brain coherence is different for leader-follower as compared to follower-follower relationships in the left TPJ. When individuals of a group do not interact, there is higher coherence between individuals who are voted as followers (resting-state). In contrast, during face-to-face communication (discussion task), the activity patterns in the TPJ change to be more similar between leader and follower. The different coherence patterns between two brains distinguish different human relationships.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\uff0c\u5168\u3066\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\u304c\uff0c\u81ea\u5206\u306e\u7814\u7a76\u3068\u3068\u3066\u3082\u985e\u4f3c\u3057\u3066\u3044\u308b\u305f\u3081\u9577\u3044\u6642\u9593\u8b70\u8ad6\u3055\u305b\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u79c1\u304c\u81ea\u5206\u306e\u7814\u7a76\u3067\u53c2\u8003\u306b\u3057\u3066\u3044\u308b\u8ad6\u6587\u3068\u540c\u3058\u89e3\u6790\u65b9\u6cd5\u3092\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u79c1\u306f\u305d\u306e\u53c2\u8003\u6587\u732e\u3092\u53c2\u8003\u306b\uff0cSFG\u3092\u7740\u76ee\u90e8\u4f4d\u3068\u3057\u3066\u3044\u307e\u3057\u305f\u304c\uff0c\u3053\u306e\u767a\u8868\u8005\u306b\u7740\u76ee\u90e8\u4f4d\u306b\u3064\u3044\u3066\u5c0b\u306d\u308b\u3068SFG\u306f\u3042\u307e\u308a\u6d3b\u6027\u304c\u898b\u3089\u308c\u306a\u304b\u3063\u305f\u304b\u3089TPJ\u3068\u3044\u3046\u5074\u982d\u8449\u306b\u3042\u308b\u7b87\u6240\u3092ROI\u3068\u3057\u3066\u691c\u8a0e\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u9762\u8b58\u306e\u306a\u30443\u4eba\u3067\u8b70\u8ad6\u3092\u3055\u305b\u308b\u3068\u7d0440\u79d2\uff5e50\u79d2\u5f8c\u306bleader\u3068follower\u306b\u81ea\u7136\u3068\u5206\u304b\u308c\u308b\u3068\u304a\u3063\u3057\u3083\u3063\u3066\u3044\u307e\u3057\u305f\uff0eNIRS\u3092\u7528\u3044\u3066\u8907\u6570\u4eba\u306e\u540c\u6642\u8a08\u6e2c\u3092\u3055\u308c\u3066\u3044\u308b\u70b9\u304b\u3089\uff0c\u89e3\u6790\u65b9\u6cd5\u3084\u30c7\u30fc\u30bf\u306e\u691c\u8a0e\uff0c\u7740\u76ee\u90e8\u4f4d\u306a\u3069\u6ca2\u5c71\u53c2\u8003\u306b\u306a\u308a\u307e\u3057\u305f\uff0e
\n 
\n\u53c2\u8003\u6587\u732e
\n1)\u00a0\u00a0\u00a0\u00a0 OHBM 2014, http:\/\/www.humanbrainmapping.org\/i4a\/pages\/index.cfm?pageid=3565<\/a>
\n 
\n\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
\u00a0<\/strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n\u65e9\u5ddd\u6e29\u5b50<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u8133\u8840\u6d41\u5909\u5316\u3092\u7528\u3044\u305f\u8a13\u7df4\u306b\u4f34\u3046\u6280\u80fd\u7fd2\u5f97\u306b\u304a\u3051\u308b\u7fd2\u719f\u5ea6\u5909\u5316\u306e\u691c\u8a0e<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nExamination of the proficiency level on skill acquisitionusing cerebral blood flow changes<\/td>\n<\/tr>\n
\u8457\u8005<\/strong><\/td>\n\u5c71\u672c\u8a69\u5b50\uff0c\u65e9\u5ddd\u6e29\u5b50\uff0c\u6a2a\u5185\u4e45\u731b\uff0c\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/strong><\/td>\nOrganization for Human Brain Mapping<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nOrganization for Human Brain Mapping (OHBM)<\/td>\n<\/tr>\n
\u4f1a\u5834<\/strong><\/td>\nCongress Center in Hamburg<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2014\/06\/08-2014\/06\/12<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n 
\n1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30
\n2014\/06\/08\u304b\u30892014\/06\/12\u306b\u304b\u3051\u3066\uff0c\u30c9\u30a4\u30c4\u306eCongress Center in Hamburg\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fOrganization for Human Brain Mapping (OHBM) 2014\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0eOHBM\u306f\uff0cOrganization for Human Brain Mapping \u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u305f\u5b66\u4f1a\u3067\uff0c\u795e\u7d4c\u5b66\u8005\uff0c\u7cbe\u795e\u79d1\u533b\uff0c\u5fc3\u7406\u5b66\u8005\uff0c\u7269\u7406\u5b66\u8005\uff0c\u6280\u8853\u8005\u3084\u7d71\u8a08\u5b66\u8005\u304c\u53c2\u52a0\u3057\u3066\uff0c\u8133\u79d1\u5b66\u5206\u91ce\u306b\u304a\u3051\u308b\u65b0\u3057\u3044\u77e5\u898b\u3092\u767a\u898b\u3059\u308b\u3079\u304f\uff0c\u30cb\u30e5\u30fc\u30ed\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u7814\u7a76\u306e\u767a\u5c55\u3084\u6210\u9577\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e
\n\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5c71\u672c\u5148\u751f\uff0c\u6a2a\u5185\u5148\u751f\uff0c\u5c07\u7a4d\uff0c\u6749\u7530\uff0c\u6728\u6751\uff0c\u5f8c\u85e4\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
\n 
\n2. \u7814\u7a76\u767a\u8868
\n2.1. \u767a\u8868\u6982\u8981
\n\u79c1\u306f10\u65e5\u306e12:45-14:45\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u300cPoster Session\u3010Imaging Methods\uff08Optical Imaging\/NIRS\uff09\u3011\u300d\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3057\u305f\uff0e
\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0cfNIRS\u3092\u4f7f\u7528\u3057\uff0c\u8133\u8840\u6d41\u5909\u5316\u3092\u5229\u7528\u3057\u305f\u7fd2\u719f\u5ea6\u5909\u5316\u306e\u691c\u8a0e\u3092\u884c\u3044\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
Introduction<\/strong>: Proficiency level on skill acquisition is hardly judged only by scores of a test. Therefore, it is needed some indexes to judge the proficiency level objectively other than task score. Then, we have run a long term experiment continuously, and investigated the process of proficiency using a physiological index. This study aims to find evaluation method for the proficiency level using physiological index.Methods<\/strong>: In our experiment, stereoscopic vision was used as a training task in which the difference in one’s ability could be observed. A Japanese character (Hiragana) was perceivable through the stereogram used in this experiment. As a long term experiment, some subjects who were not good at stereopsis were directed to practice it every day for four weeks, and their cerebral blood flow changes were measured once a week using fNIRS (functional near infrared spectroscopy) to investigate the changes in proficiency through their practices. This experiment aimed to examine the changes in proficiency caused by the progress of the training, and found an indicator to evaluate the proficiency using cerebral blood flow changes. Subjects were a healthy male and four healthy females. Conforming to the 10-20 method, we measured the both temporal, occipital, parietal, and frontal regions. During the task time, subjects were to gaze a cross mark which was shown in the center of the screen, and during the rest time, they were to say aloud the vowels, “a i u e o”, repeatedly. Subjects had performed stereoscopic vision in the task time. The task comprised two blocks; in the first block, the subjects were to gaze the screen for two seconds and in the other block, they were showed stereopsis for ten seconds. A subject was allowed to proceed to the next screen, once he\/she answered the stereopsis.Results<\/strong>: As experimental results, we examined the task performance, the reaction time and the cerebral blood flow changes. Firstly, the number of answers in which a subject answered correctly within the limited time was examined. We found that subjects had been developing proficiency of this task, because task scores had been increasing in every week. Secondly, reaction time was examined. The correlation coefficient between the performance and the reaction time was calculated, and it was found that a subject whose score had been improving showed a high negative correlation. From this result, it was considered that the subjects had been developing proficiency of this task in every week. Lastly, the cerebral blood flow changes were examined. The time-series row data of each week were visually studied, and it was confirmed that the cerebral blood flow had been decreasing. In order to illustrate numerically, SLOPE of the cerebral blood flow changes during the task time was used as a numeric indicator. Then, to determine the change of the region, the data was colored by the slope change. After data was separated by a positive or negative sign of the slope, the average value of all the regions in all weeks was calculated, and the data was colored using the average value as its thresholds. As the result of the examination on region changes, the cerebral blood flow changes also had been decreasing, as the visual confirmation of the measurement data. From these results, the effectiveness of SLOPE for the proficiency level evaluation was confirmed. However, there were some subjects whose cerebral blood flow change had increased only in the fourth week. At least three reasons can be considered. Firstly, they might have reached the stage of understanding problems in learning skills, but it had not reached the proficiency level yet. Secondly, they might have reached the skilled level, but proficient state was still unstable. Thirdly, psychological factors of subjects had affected.Conclusions<\/strong>: From these results, we found that cerebral blood flow change is decreased when the subjects acquire skills. Cerebral blood flow change slope can be the index for judging the proficiency level.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n2.2. \u8cea\u7591\u5fdc\u7b54
\n\u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>1<\/strong>
\n\u81ea\u6cbb\u533b\u79d1\u5927\u5b66\u6240\u5c5e\u306e\u5b87\u8cc0\u7f8e\u5948\u5b50\u5148\u751f\u304b\u3089\u306e\u8cea\u554f\u3067\u3059\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\u4eee\u8aac\u3067\uff0c\u8ab2\u984c\u6210\u7e3e\u306e\u4e0a\u304c\u308a\u59cb\u3081\u306b\u8133\u8840\u6d41\u5909\u5316\u304c\u5897\u52a0\u3059\u308b\u3068\u8003\u3048\u305f\u7406\u7531\u306f\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u6280\u80fd\u7fd2\u5f97\u306b\u306f\u7406\u89e3\u3068\u7fd2\u719f\u306e2\u6bb5\u968e\u304c\u3042\u308a\uff0c\u8ab2\u984c\u6210\u7e3e\u304c\u4e0a\u304c\u308a\u9014\u4e2d\u306e\u88ab\u9a13\u8005\u306f\u7406\u89e3\u6bb5\u968e\u306b\u3042\u305f\u308b\uff0e\u305d\u306e\u305f\u3081\uff0c\u8a66\u884c\u932f\u8aa4\u3092\u7e70\u308a\u8fd4\u3057\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3080\u305f\u3081\u8133\u8840\u6d41\u5909\u5316\u304c\u5897\u52a0\u3059\u308b\u3068\u8003\u3048\u305f\u3068\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
\n\u7fa4\u99ac\u5927\u5b66\u6240\u5c5e\u306e\u8c4a\u6751\u6681\u5148\u751f\u304b\u3089\u306e\u8cea\u554f\u3067\u3059\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u691c\u5b9a\u3092\u304b\u3051\u3066\u307f\u306a\u304b\u3063\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3068\u6b63\u898f\u5316\u306e\u65b9\u6cd5\u306f\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u79c1\u306f\uff0c\u691c\u5b9a\u306f\u4eca\u56de\u304b\u3051\u3066\u304a\u3089\u305a\uff0c\u76ee\u8996\u306b\u3088\u308b\u5224\u65ad\u3092\u884c\u3044\u307e\u3057\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e2\u3064\u76ee\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u306f\uff0c\u6b63\u898f\u5316\u306e\u65b9\u6cd5\u3092\u624b\u9806\u3092\u8e0f\u3093\u3067\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u3054\u610f\u898b\u3068\u3057\u3066\uff0c\u90e8\u4f4d\u306b\u3088\u3063\u3066\u7acb\u3066\u308b\u4eee\u8aac\u3082\u5909\u308f\u3063\u3066\u304f\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u304a\u3063\u3057\u3083\u3063\u3066\u3044\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
\n\u8cea\u554f\u8005\u306e\u304a\u540d\u524d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u8ab2\u984c\u6210\u7e3e\u304c\u4e0a\u6607\u3057\u3066\u3044\u304f\u3068\uff0c\u8133\u8840\u6d41\u5909\u5316\u306f\u306a\u304f\u306a\u308b\u3068\u3044\u3046\u3053\u3068\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u79c1\u306f\uff0c\u8133\u8840\u6d41\u5909\u5316\u304c\u306a\u304f\u306a\u308b\u306e\u3067\u306f\u306a\u304f\uff0c\u8133\u8840\u6d41\u5909\u5316\u306f\u6e1b\u5c11\u3057\u3066\u3044\u304f\u306e\u3060\u3068\u3044\u3046\u56de\u7b54\u3092\u3057\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u3082\u3046\u4e00\u554f\u8cea\u554f\u3092\u4e0b\u3055\u3063\u305f\u306e\u3067\u3059\u304c\uff0c\u79c1\u306e\u82f1\u8a9e\u529b\u306e\u4e4f\u3057\u3055\u3088\u308a\uff0c\u82f1\u8a9e\u3092\u805e\u304d\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u305a\uff0c\u7406\u89e3\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>4<\/strong>
\n\u30d4\u30c3\u30c4\u30d0\u30fc\u30b0\u5927\u5b66\u6240\u5c5e\u306eXiaoping Fang\u3055\u3093\u304b\u3089\u306e\u8cea\u554f\u3067\u3059\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u7acb\u4f53\u8996\u3068\u306f\uff0c\u8ab2\u984c\u306e\u6d41\u308c\u306e\u8aac\u660e\u306a\u3069\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u79c1\u306f\uff0c\u6301\u53c2\u3057\u3066\u3044\u305f\u30b9\u30c6\u30ec\u30aa\u30b0\u30e9\u30e0\u3092\u7528\u3044\u306a\u304c\u3089\u7acb\u4f53\u8996\u306e\u8aac\u660e\u3092\u884c\u3044\uff0c\u307e\u305f\uff0c\u8ab2\u984c\u306e\u6d41\u308c\u306b\u3064\u3044\u3066\u306f\u30dd\u30b9\u30bf\u30fc\u306e\u305d\u306e\u90e8\u5206\u3092\u6307\u3057\u793a\u3057\u306a\u304c\u3089\u8aac\u660e\u3092\u884c\u3044\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u5b9f\u9a13\u7d50\u679c\u306b\u304a\u3044\u3066\u90e8\u4f4d\u306b\u3088\u308a\u5dee\u304c\u751f\u3058\u305f\u306e\u306f\u8133\u6a5f\u80fd\u304c\u90e8\u4f4d\u306b\u3088\u308a\u7570\u306a\u308b\u304b\u3089\u306a\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3044\u3046\u3054\u610f\u898b\u3092\u9802\u304d\u307e\u3057\u305f\uff0e
\n 
\n2.3. \u611f\u60f3
\n\u53bb\u5e74\u521d\u3081\u3066\u306e\u56fd\u969b\u5b66\u4f1a\u306b\u51fa\u3066\u304b\u3089\u4e45\u3057\u3076\u308a\u306e\u5b66\u4f1a\u53c2\u52a0\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u521d\u3081\u3066\u306e\u5b66\u4f1a\u3088\u308a\u306f\u7dca\u5f35\u3059\u308b\u3053\u3068\u3082\u306a\u304f\uff0c\u767a\u8868\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u305f\u3068\u601d\u3044\u307e\u3059\uff0e\u305f\u3060\uff0c\u79c1\u306e\u82f1\u8a9e\u80fd\u529b\u306e\u4e4f\u3057\u3055\u3088\u308a\uff0c\u8cea\u554f\u3092\u805e\u304d\u53d6\u308b\u3053\u3068\u304c\u51fa\u6765\u306a\u304b\u3063\u305f\u3053\u3068\u3084\u81ea\u5206\u306e\u8a00\u3044\u305f\u3044\u3053\u3068\u304c\u8a00\u3048\u306a\u3044\u3053\u3068\u306a\u3069\u304c\u3042\u308a\u307e\u3057\u305f\uff0e\u53bb\u5e74\u306e\u5b66\u4f1a\u306b\u304a\u3044\u3066\u3082\u8a00\u8a9e\u306e\u58c1\u306b\u76f4\u9762\u3057\u3066\u3044\u308b\u305f\u3081\uff0c\u3053\u308c\u304b\u3089\u3055\u3089\u306b\u82f1\u8a9e\u306f\u52c9\u5f37\u3057\u3066\u3044\u3053\u3046\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n\u307e\u305f\uff0c\u767a\u8868\u306e\u969b\u306b\u306f\uff0c\u4f55\u4eba\u304b\u306e\u65b9\u304c\u79c1\u306e\u30dd\u30b9\u30bf\u30fc\u306b\u8db3\u3092\u904b\u3093\u3067\u4e0b\u3055\u308a\uff0c\u8cea\u554f\u3084\u610f\u898b\u3092\u9802\u304f\u3053\u3068\u304c\u51fa\u6765\u307e\u3057\u305f\uff0e\u9802\u3044\u305f\u610f\u898b\u306a\u3069\u3092\u53c2\u8003\u306b\u7814\u7a76\u3092\u9032\u3081\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e\u3055\u3089\u306b\uff0c\u767a\u8868\u3092\u805e\u304d\u306b\u6765\u3066\u4e0b\u3055\u3063\u305f\u65b9\u306e\u4e2d\u306b\u306f\u79c1\u306e\u7814\u7a76\u306b\u3064\u3044\u3066\u9762\u767d\u3044\u3068\u8a00\u3063\u3066\u4e0b\u3055\u3063\u305f\u65b9\u3082\u3044\u305f\u305f\u3081\uff0c\u7814\u7a76\u306b\u5bfe\u3059\u308b\u30e2\u30c1\u30d9\u30fc\u30b7\u30e7\u30f3\u304c\u4e0a\u304c\u308a\u307e\u3057\u305f\uff0e
\n 
\n3. \u8074\u8b1b
\n\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e5\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Learning-induced changes in functional connectivity differ for good vs less-good tone-learners\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Salomi Asaridou, Hubert Fonteijn, Peter Hagoort, James McQueen\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Language \/ Language AcquisitionAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a
\nIntroduction:<\/strong>
\nThe human brain is remarkable for its plasticity, adapting its function and structure in response to experience and learning. In the present study we investigated whether plastic changes occur in functional connectivity as measured with resting-state fMRI. More specifically, we wanted to test whether learning a non-native linguistic contrast such as tones can alter resting-state connectivity between auditory-language areas in the brain. Given the fact that non-native sound learning abilities vary greatly in adults, we expected learning-induced changes in the resting-state fMRI signal to differ for good compared to less-good learners.
\nMethods:<\/strong>
\nForty Dutch native-speakers (25 female, mean age=22.62, SD=3.16) with no prior tone language experience took part in the study. Participants were trained to match 24 auditory-presented words, differing minimally in tone, to pictures of items over the course of five separate sessions. Accuracy scores (percentage correct word-picture mappings) were recorded for each session and were analyzed using repeated-measures ANOVA with Session as a factor. Resting-state fMRI data were acquired at two time-points: before and after the five session training. Data were acquired on a 3T Trio scanner, with a 32-channel head-coil using a multi-echo sequence (TR =2000ms, TE1 =6.9ms, TE2 =16.2ms, TE3 =25ms, TE4 =35ms, TE5 =44ms, flip angle = 80\u00b0). The mean time-course of voxels in ten seed regions was extracted and linear correlations between them and all other voxels in the brain were calculated in SPM8 for each participant and each session using a standard GLM approach. Seed regions included the Pars Opercularis (POP), Pars Triangularis (PTr), Pars Orbitalis (POrb), Superior Temporal Gyrus (STG) and Heschl’s Gyrus (HG) in both hemispheres. Multiple regression was used for the second level random effects analysis with the final learning accuracy score of each participant added as a covariate.
\nResults:<\/strong>
\nThe repeated-measures ANOVA revealed a significant effect of session [F(1.567,61.127)=99.247, p<.001 (Greenhouse-Geisser corrected)] indicating that participants improved significantly over the course of the training. The imaging data analyses, which aimed to investigate how changes in functional connectivity before and after training related to variability in learning performance, revealed a negative correlation between learning score and left POrb \u2013 left STG connectivity (p=.025, FWE cluster corrected) after training. When looking at the difference in connectivity (after > before training), a negative correlation was found between learning score and difference in connectivity between the right STG \u2013 right Middle Temporal Gyrus (MTG) (p=.043, FWE cluster corrected). Negative correlation was also found between learning score and difference in connectivity between right HG \u2013 right POP (p=.045, FWE cluster corrected).
\nConclusions:<\/strong>
\nWe found learning-induced changes in resting-state connectivity following lexical tone training. As anticipated, the changes differed for good vs less-good learners. Overall, participants who performed better in learning non-native tones showed decreased functional connectivity. Specifically, connectivity between temporal areas (STG and MTG) as well as between the primary auditory cortex (HG) and frontal areas (POP) in the right hemisphere decreased after training in good learners. Good learners also showed less connectivity between left frontal (POrb) and left temporal (STG) areas after training. A recent study reported reduced resting-state connectivity in left fronto-parietal regions following a consonantal phonetic training (Ventura-Campos et al., 2013). The present finding of bilateral instead of left hemispheric changes could be attributed to the use of tonal contrasts, which potentially recruit additional right lateralized pitch processing resources. Our results are in line with previous findings on lexical tone and add to our understanding of the role of functional connectivity in language learning.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0cresting-state\u6642\u306e\u5b66\u7fd2\u306b\u3088\u3063\u3066\u8a98\u767a\u3055\u308c\u305f\u5909\u5316\u304c\u8a9e\u5f59\u7684\u306a\u30c8\u30fc\u30f3\u30fb\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u306b\u95a2\u3057\u3066\u8003\u5bdf\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u79c1\u81ea\u8eab\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306b\u95a2\u4fc2\u306e\u3042\u308b\u7814\u7a76\u3092\u884c\u3063\u3066\u3044\u308b\u305f\u3081\u8ab2\u984c\u306f\u7570\u306a\u308a\u307e\u3059\u304c\uff0c\u81ea\u8eab\u306e\u7814\u7a76\u306b\u3082\u7e4b\u304c\u308b\u3082\u306e\u304c\u3042\u308b\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aA confidence signal in ventral striatum and its role in perceptual learning\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Matthias Guggenmos, Martin Hebart, Shea Karst, Gregor Wilbertz, Philipp Sterzer\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Perception and Attention \/ <\/strong>Perception: VisualAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a
\nIntroduction:<\/strong>
\nPerceptual learning is the improvement in performance on sensory tasks following practice. Recent models of perceptual learning propose a reinforcement learning mechanism, in which reward prediction errors guide plasticity (Kahnt et al., 2011; Law and Gold, 2009). However, these models cannot easily explain why perceptual learning is often observed in the absence of external reward or feedback. One possibility is that internally generated feedback signals serve a similar purpose. In fact, recent studies (Schwarze et al. 2013; Daniel and Pollmann, 2012) reported a neural correlate of subjective confidence in the ventral striatum, a structure involved in reward processing and learning (O’Doherty et al., 2004). From this the intriguing hypothesis arises that confidence reflects an internal reward signal, enabling self-reinforced learning in the absence of feedback. To test this hypothesis we designed an fMRI experiment in which participants reported their confidence after each trial of a visual perceptual learning paradigm. We predicted that neural activation in the ventral striatum reflects subjective confidence and that individual perceptual learning success may be related to the strength of this striatal confidence signal during learning.
\nMethods:<\/strong>
\nTwenty-nine participants took part in the experiment, which comprised an extensive training session in the scanner and psychophysical threshold tests one week before (pre-test) and one day after training (post-test). The participants’ task was to detect noise-embedded peripheral Gabor patches, which were rotated clockwise or counterclockwise with respect to one of two possible reference axes. After each stimulus presentation, participants first reported their level of confidence and then indicated their percept. In the pre- and post-test we measured Gabor detection thresholds for 80.35% correct responses for both reference axes. During training participants were presented with Gabors of only one reference axis, but in two randomly interleaved conditions: in the constant performance condition (CP) the Gabor contrast was continuously adapted to keep performance at 80.35% correct, while in the constant stimulus condition (CS) the contrast was fixed at the pre-test level. In addition to 10 runs of perceptual training (\u00e1 48 trials), a functional localizer for the Gabor stimuli was acquired.
\nResults:<\/strong>
\nIn the pre\/post-test comparison participants had reliably lower contrast thresholds for the trained (-32.1%; p<0.001), but not the untrained reference axis (-3.0%; p=0.68). At the neural level bilateral ventral striatum showed a strong correlation with reported confidence (left: t(28)=8.92, pFWE<0.001; right: t(28)=8.36, pFWE<0.001; whole-brain corrected). Region of interest (ROI) analysis further revealed significant correlations with confidence in primary visual cortex (t(28)=6.08, pFWE=0.001; ROI based on BA17), left posterior fusiform gyrus (t(28)=5.81, pFWE=0.001; ROI based on the functional localizer) and ventral tegmental area (t(28)=3.18, pFWE=0.026; literature-based ROI). Finally, the confidence signal in the left ventral striatum was positively correlated with the degree of perceptual learning (r=0.342, p=0.038, one-tailed), after controlling for pre-training thresholds.
\nConclusions:<\/strong>
\nWe found robust and specific perceptual learning effects at the behavioural level. As hypothesized, the ventral striatum showed a strong correlation with reported confidence. To our knowledge, this is the first direct demonstration of this effect. Importantly, the confidence signal in the left ventral striatum was correlated with the degree of perceptual improvement, in line with the previously proposed idea of an involvement of the ventral striatum in self-reinforced perceptual learning. The coactivation of the ventral tegemental area and visual areas is suggestive of a dopaminergic modulation of visual areas as a function of confidence. Further analyses will have to elucidate the effective connectivity between those regions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\u77e5\u899a\u5b66\u7fd2\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3057\u305f\uff0e29\u4eba\u3082\u5b9f\u9a13\u3057\u3066\u304a\u308a\uff0c\u79c1\u3082\u306a\u308b\u3079\u304f\u591a\u304f\u306e\u30b5\u30f3\u30d7\u30eb\u3092\u3068\u308b\u3053\u3068\u3092\u76ee\u6a19\u306b\u52aa\u529b\u3057\u3066\u3044\u3053\u3046\u3068\u601d\u3044\u307e\u3057\u305f\uff0e\u77e5\u899a\u5b66\u7fd2\uff08perceptual learning\uff09\u3068\u3044\u3046\u8a00\u8449\u304c\u3042\u307e\u308a\u805e\u304d\u6163\u308c\u3066\u3044\u306a\u304b\u3063\u305f\u305f\u3081\uff0c\u7814\u7a76\u30c6\u30fc\u30de\u306b\u95a2\u3057\u975e\u5e38\u306b\u8208\u5473\u6df1\u304b\u3063\u305f\u3067\u3059\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000The specificity of dance versus music training on gray matter structure\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Falisha Karpati, Chiara Giacosa, Virginia Penhune, Nicholas Foster, Krista Hyde\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Learning and Memory \/ <\/strong>Skill LearningAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a
\nIntroduction:<\/strong>
\nIndividuals with specialized training, such as musicians and dancers, provide a unique approach to studying human brain plasticity. While several studies have investigated the structural brain correlates of music (Zatorre & Herholz, 2012), only one study has examined the neuroanatomical correlates of dance (Hanggi et al., 2010). Here we compared gray matter structure in professional dancers and musicians relative to non-trained controls in order to examine what brain areas might be the same or different across these two auditory-motor art forms.
\nMethods:<\/strong>
\nParticipants:
\nParticipants were 20 dancers, 15 musicians and 15 controls aged 18-40 years old. Groups were matched in age and gender. Participants were screened using a detailed questionnaire about their dance and music experience. Dancers and musicians were currently professional or undertaking a professional training program in dance or music, respectively. They had at least 10 years of training in their respective skill, and less than 3 years of training in the other. Controls had less than 3 years of formal training in dance, music, figure skating, aerobics or any competitive sport. Participants had no neurological or psychiatric history. The project was approved by our local ethics committee and all participants provided written informed consent.
\nScanning Protocol and Morphometric Analyses:
\nT1-weighted MR sequences were obtained for all participants on a 3 Tesla Siemens scanner. The T1 anatomical MRIs for all participants were submitted to “CIVET” (Ad-Dab’bagh et al., 2006) for processing and cortical thickness analyses. Each T1-weighted image volume was corrected for signal intensity nonuniformity, linearly transformed into standardized stereotaxic space, and segmented into gray and white matter, cerebrospinal fluid and background. The gray and white matter surfaces were then fitted using deformable models, resulting in two surfaces with 81920 polygons each. Next, a cortical thickness map was calculated for each subject, where cortical thickness was measured at every point (or vertex) on the cortical mantle, and then blurred with a 20 mm surface based blurring kernel (Lerch et al., 2005). Statistical analyses were performed at every point on the cortical mantle to test for group differences in cortical thickness using SurfStat software (Worsely, 2008). Age and gender were included as covariates. Results were thresholded over the whole brain at p<0.001 uncorrected.
\nResults:<\/strong>
\nMusicians had thicker cortex relative to controls in various brain regions, but most notably in the right superior temporal gyrus (Figure 1a). Dancers also had thicker cortex relative to controls in the superior temporal gyrus (Figure 1b), along with other brain areas such as the medial superior frontal gyrus. Musicians had thicker cortex than dancers in the right precentral gyrus (Figure 1c).
\nConclusions:<\/strong>
\nThe present results confirm previous findings of cortical thickness differences in musicians versus non-musicians in the right superior temporal gyrus, a region known to be implicated in auditory-musical processing (Bermudez et al., 2009). The finding that dancers also showed thicker cortex relative to controls in this same region likely reflects that auditory-musical processing is critical in both music and dance training. We also report novel findings of increased cortical thickness in musicians relative to dancers in an area of the precentral gyrus associated with mouth and tongue movements (Fox et al., 2001; Salmelin & Sams, 2002). This result likely reflects that many of the musicians tested here play wind instruments requiring enhanced mouth\/ tongue motricity. This work advances our understanding of the specificity of the neural correlates of dance and music training, and may have potential applications in therapies for motor disorders.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u6280\u80fd\u7fd2\u5f97\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3057\u305f\uff0e\u30c0\u30f3\u30b5\u30fc\u3084\u97f3\u697d\u5bb6\u304c\u88ab\u9a13\u8005\u3067\uff0c\u97f3\u697d\u306b\u95a2\u3059\u308b\u6280\u80fd\u7fd2\u5f97\u306b\u304a\u3051\u308b\u8133\u6a5f\u80fd\u3092\u8abf\u67fb\u3057\u3066\u3044\u307e\u3057\u305f\uff0e20\u4eba\u306e\u30c0\u30f3\u30b5\u30fc\u306815\u4eba\u306e\u97f3\u697d\u5bb6\uff0c15\u4eba\u306e\u30b3\u30f3\u30c8\u30ed\u30fc\u30eb\u7fa4\u306e\u88ab\u9a13\u8005\u3068\u3044\u3046\u975e\u5e38\u306b\u591a\u3044\u88ab\u9a13\u8005\u6570\u3092\u8a08\u6e2c\u3057\u3066\u3044\u308b\u7814\u7a76\u3067\u3057\u305f\uff0e\u97f3\u697d\u306b\u95a2\u3059\u308b\u7814\u7a76\u306f\u79c1\u81ea\u8eab\u697d\u5668\u3092\u6f14\u594f\u3057\u3066\u3044\u305f\u3053\u3068\u3082\u3042\u308a\uff0c\u8208\u5473\u304c\u3042\u308a\u307e\u3059\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Training of Dance Video Game Changes Brain Activity Related to Audio-visual Integration\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Yasunori Nomoto, Jack Noah, Atsumichi Tachibana, Shaw Bronner, Sotaro Shimada, Yumie Ono\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Learning and Memory \/ <\/strong>Skill LearningAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a
\nIntroduction:<\/strong>
\nWe used near-infrared spectroscopy (NIRS) to investigate how brain activities relating to multimodal sensory integration change with motor learning of a dance video game (del Olmo, 2005). Subjects played the game requiring integrated processing of visual, audio and tactile inputs and motor outputs in two conditions: with and without background music (Tachibana, 2011; Liegeois-Chauvel, 1998). We focused on two brain regions, the middle temporal gyrus (MTG), an area of multisensory integration, and the frontopolar cortex (FPC), associated with multitask decision making. Using subjects with varying skills, we have showed correlation between number of temporally accurate steps and brain activities in these two areas (Ono, 2014). Our previous data showed a bell-shaped oxyHb waveform in the MTG, in which high-performance players (HPP) took longer to reach to peak amplitude than low-performance players (LPP). Removal of music during gameplay increased cumulative oxyHb signal in the MTG in HPP while it decreased in LPP (Fig.1). In the FPC, HPP showed a small oxyHb increase followed by a steep and sustained decrease during the task period, while LPP showed box-car shaped with prolonged activation. In spite of the presence or absence of music, the cumulative amount of oxyHb signal in the FPC had a negative correlation with the number of temporally accurate steps. In this study, regional brain activity during gameplay was scanned using NIRS pre- and post 20h of training to investigate whether the training modify brain responses during gameplay within-subject along with the correlation found in the previous between-subject study.
\nMethods:<\/strong>
\nSubjects (6 males; 22.5 +\/-0.5 years) responded by pressing arrow buttons (up, down, left or right) on a dance mat at correct times with their feet to play. We studied cortical function using a block design with 30s of activity followed by 30s of rest repeated five times. Performance was scored by the number of temporally accurate steps, corresponding to proper button presses within +\/-22.5ms of the correct time.
\nResults:<\/strong>
\nBrain activities of LPP switched to that of HPP after training. In the MTG, training significantly increased the number of temporally accurate steps and increased the difference in the cumulative amount of oxyHb signal between conditions of without audio and with audio, shifting toward the distribution of HPP (p<0.001; paired t-test, Fig.1). In the FPC, the oxyHb waveform changed from the previous box-car shape to the decreasing shape observed in HPP. Cumulative amount of oxyHb signal was significantly decreased (p=0.049; paired t-test, Fig.2).
\nConclusions:<\/strong>
\nThese results suggest that MTG plays a role in the successful integration of visual and rhythmic cues and training allowed integration of visual and internally-generated rhythm to make accurate steps even without external auditory rhythmic cues. FPC is involved in processing prospective memory while multitasking and may work to compensate for insufficient integrative ability of visual and rhythmic cues in the MTG in LPP. Subjects might not require FPC activity to perform the game after training. However, the time to reach to peak amplitude in MTG did not extend with training. Although current subjects achieved better scores after training (97.9+\/-28.7 temporally accurate steps), they were much lower compared to the best players in the previous study (137.6+\/-18.3 steps). This suggests that short and intense training is sufficient to cause plastic changes in the FPC to achieve a certain level of improvement, however subjects require increased or modified training to change substantivity of MTG responses to achieve more precise motor control. Relative relationships between cortical areas may indicate how training affects motor skill and brain activities when performing cued motor tasks.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u30c0\u30f3\u30b9\u30d3\u30c7\u30aa\u30b2\u30fc\u30e0\u3092\u4f7f\u7528\u3057\u305f\u6280\u80fd\u7fd2\u5f97\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3059\uff0e\u904b\u52d5\u5b66\u7fd2\u306b\u3064\u3044\u3066\u691c\u8a0e\u3092\u884c\u3063\u3066\u3044\u308b\u3082\u306e\u3067\u3057\u305f\uff0eNIRS\u3092\u5229\u7528\u3057\u305f\u7814\u7a76\u3067\u3082\u3042\u308b\u3053\u3068\u304b\u3089\u3053\u306e\u7814\u7a76\u3067\u306e\u89e3\u6790\u65b9\u6cd5\u306a\u3069\u3092\u4f7f\u3046\u3053\u3068\u304c\u3067\u304d\u308b\u304b\u691c\u8a0e\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000R & B: Rhythm Learning in the Brain\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Ido Tavor, Rotem Botvinik, Roni Sapir, Yaniv Assaf\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Learning and Memory \/ <\/strong>Skill LearningAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a
\nIntroduction:<\/strong>
\nThe motor system is a cognitive domain that includes several cortical and sub-cortical regions and a well-defined fiber network connecting them. Diffusion MRI was recently shown to be sensitive to short term neuroplasticity in spatial navigation learning (1). While learning of spatial information is expected to cause structural changes in limbic system structures, the structural neuroplasticity aspects in higher cognitive domains are not straightforward. It is not clear, for example, if structural remodeling will occur when exposed to motor learning and if it does occur will it affect the entire network. In the current study we used DTI in order to investigate the neuroplasticity that accompanies sequential motor learning. We wish to examine whether different aspects of the learning procedure will involve different brain regions.
\nMethods:<\/strong>
\nWe set up a motor sequence learning task using an electric piano keyboard. 32 non-musician subjects were scanned before the task and immediately after it. During the task participant learned to play a short sequence based on the first 51 notes of Beethoven’s F\u00fcr Elise. Subjects were presented with an increasing number of notes on a virtual keyboard and were asked to repeat the sequence on the keyboard using their right hand. Presentation of a sequence included visual and auditory stimuli. The task included 63 trials, starting with a single note and ending with the whole piece. Subjects received feedback and were tested on accuracy of key pressing. The duration of the task was approximately 45 minutes. A subset of 15 subjects continued to a second learning session in which they received feedback and were tested on the rhythm of key pressing (a stage that is possible only after reaching a high level of accuracy) and then they were scanned again.
\nThe DTI protocol included diffusion weighted images with b value of 1,000 s\/mm2<\/sup>\u00a0at 30 directions and a b=0 image with isotropic resolution of 2.1 mm3<\/sup>. DTI analysis included extraction of mean diffusivity (MD) maps and normalization to MNI coordinate system using SPM. We then performed a voxelwise repeated measures ANOVA on the DTI images. Clusters were considered significant when P < 0.005 and cluster size is larger than 10 voxels.
\nResults:<\/strong>
\nBehaviorally, all subjects improved their accuracy and by the end of the first session succeeded to play most of the keys correctly (mean of 47.5\u00b11.5 correct notes out of 51). While the improvement in accuracy was relatively high, the rhythm and timing of the subjects did not reach a reasonable amount of learning. After the second learning however, an improvement in rhythm was also observed.
\nWe found significant MD reduction in the left premotor cortex, left middle temporal gyrus, right superior temporal gyrus and right cerebellum (Fig 1). In the subset that performed a second learning session we saw that these changes were diminished in the third scan (Fig 2), yet changes in new regions were observed: the left inferior frontal gyrus, the left lingual gyrus and the right anterior temporal gyrus.
\nConclusions:<\/strong>
\nWe showed that DTI can follow on short-term brain plasticity of an entire cognitive domain. One hour of learning was sufficient to cause structural brain changes in several motor system regions, as well as temporal regions that may be involved in the auditory aspect of the task. We found changes that occurred after subjects improved their accuracy without any improvement in the rhythm of key pressing. Then, a prolonged practice in the task in which rhythm performance improved as well, resulted in different patterns of brain plasticity within regions that are known to be involved in high-order cognitive processing of visual and auditory stimuli. The ability to detect learning-related brain changes in such a short time scale can shed light on the way neuroplasticity evolves within a system, and help to understand the role of each component of the system in cognitive improvement.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u8133\u306e\u8a8d\u77e5\u6a5f\u80fd\u306e\u89b3\u70b9\u304b\u3089\u6280\u80fd\u7fd2\u5f97\u6642\u306e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u89e3\u660e\u3092\u76ee\u7684\u306b\u3057\u305f\u7814\u7a76\u3067\u3057\u305f\uff0eDTI\u3092\u7528\u3044\u308b\u3053\u3068\u3067\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u691c\u8a0e\u3092\u884c\u3063\u3066\u3044\u307e\u3057\u305f\uff0e\u6280\u80fd\u7fd2\u5f97\u6642\u306e\u8133\u306e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u304c\u89e3\u660e\u3055\u308c\u308c\u3070\uff0c\u73fe\u5728\u79c1\u304c\u884c\u3063\u3066\u3044\u308b\u3088\u3046\u306a\u7814\u7a76\u3082\u3055\u3089\u306b\u6357\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u611f\u3058\u307e\u3057\u305f\uff0e
\n 
\n\u53c2\u8003\u6587\u732e
\n1)\u00a0\u00a0\u00a0\u00a0 OHBM2014, http:\/\/www.humanbrainmapping.org
\n 
\n\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/p>\n\n\n\n\n\n\n\n\n\n\n
\u5831\u544a\u8005\u6c0f\u540d<\/td>\n\u6728\u6751\u831c<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/td>\n\u8996\u899a\u523a\u6fc0\u3068\u8074\u899a\u523a\u6fc0\u306b\u5bfe\u3059\u308b\u6ce8\u610f\u306e\u5ea6\u5408\u3044\u306e\u5f71\u97ff<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/td>\nImpact of the different degree of attention to the auditory and visual stimuli<\/td>\n<\/tr>\n
\u8457\u8005<\/td>\n\u5c71\u672c\u8a69\u5b50, \u6728\u6751\u831c, \u6a2a\u5185\u4e45\u731b, \u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/td>\nOrganization for Human Brain Mapping<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/td>\nOHBM 2014 Annual Meeting<\/td>\n<\/tr>\n
\u4f1a\u5834<\/td>\nCCH – Congress Center Hamburg<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/td>\n2014\/6\/08-2014\/6\/12<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n 
\n\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30
\n2014\/6\/08-2014\/6\/12\u306b\u304b\u3051\u3066\uff0cCCH – Congress Center Hamburg\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fOrganization for Human Brain Mapping 2014 Annual Meeting\uff08http:\/\/www.humanbrainmapping.org\/i4a\/pages\/index.cfm?pageID=3565\uff09\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306eOHBM 2014 Annual Meeting\u306f\uff0cOrganization for Human Brain Mapping\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u305f\u96c6\u4f1a\u3067\uff0c\u201c\u30d2\u30c8\u8133\u6a5f\u80fd\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u5206\u91ce\u3084\u79d1\u5b66\u5206\u91ce\u306e\u767a\u5c55\u201d\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e
\n\u79c1\u306f\uff0c9\u65e5\u306b\u767a\u8868\uff0c8\uff0c12-13\u65e5\u306b\u306f\u516c\u8074\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5c71\u672c\u5148\u751f\uff0c\u6a2a\u5185\u5148\u751f\uff0c\u6749\u7530\uff0c\u5f8c\u85e4\uff0c\u65e9\u5ddd\uff0c\u5c07\u7a4d\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u7814\u7a76\u767a\u8868
\n\u767a\u8868\u6982\u8981
\n\u79c1\u306f9\u65e5\u306e\u30dd\u30b9\u30bf\u30fc\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u300cImaging Methods(Optical Imaging\/NIRS)\u300d\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c\u6642\u9593\u306f2\u6642\u9593\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e
\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3059\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
In the field of functional mapping of the brain, several experiments were investigated by observing the effects of the provided stimuli on subjects. However, the same reactions could be related to different stimuli leading to different processes of higher brain functions and different activity states.The degree of attention is modulated by stimuli, then it may be one of the most significant cause for the reactions and the activity states.Therefore, to associate cerebral function with a particular activity state of the brain, it is necessary to take into consideration the difference in the activity state induced by the degree of attention.The difference in the activity state of the brain that the difference degree of attention based on the interaction of senses and each different senses has been actively discussed, but has not been clarified.In this study, we performed two types of GO\/NOGO tasks with visual and auditory stimuli in parallel.In addition, we examined the effect to brain activity with the degree of attention to the multisensory, using cerebral blood flow (CBF) changes or reaction time (RT).The cerebral cortex oxy-hemoglobin concentration changes were observed in five healthy women, while these GO\/NOGO tasks were performed using functional near-infrared spectroscopy.Tasks were performed 10 minutes, and the activity states on attention degree are evaluated by the mean and variance of RT every 10 samples as parameters of attention.By comparing the period of the best to the worst responses to auditory and visual for each stimuli, the frontal cortex was focused as the attention-related regions that the CBF changes significantly increased or decreased (p <.05) in common with visual and auditory stimuli in all subjects.The region of indicating the attention was different, because the best performance period is different evaluation between by the mean and by the variance of RT.So, we consider as another parameter the mean and the variance of RT.It is regarded the different degree of attention as when subjects have the most attention to both visual and auditory, to visual than auditory, and to auditory than visual.The CBF changes on the highest degrees of attention of three are compared by using each parameter.And, CBF changes are increased either parameter in the order of the above.The region indicating the attention was different in the mean and variance of RT.It has generally been recognized that more the information input in the brain, more activated the brain is.It is believed that visual stimuli contain more information than auditory stimuli.So, visual stimuli also induce more load on the brain than auditory stimuli when subjects pay attention.In this experiment, it is also suggested that the degree of attention to the amount of information reflected in the attention-related regions, when they have the most attention to stimuli.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n\u8cea\u7591\u5fdc\u7b54
\n\u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
\n\u30fb\u8cea\u554f\u5185\u5bb91
\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u8cea\u554f\u306f\uff0cNIRS\u3067\u9178\u7d20\u6fc3\u5ea6\u306eFLOW\u3092\u898b\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u306e\u304b\uff1f\u305d\u306e\u8133\u8840\u6d41\u5909\u5316\u3068\u306f\uff0c\u52d5\u8108\u8840\u6d41\u306e\u5909\u5316\u306a\u306e\u304b\uff1f\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u79c1\u306f\uff0c\u78ba\u304b\u306b\u305d\u306e\u901a\u308a\u3067\u3059\uff0e\u8133\u8840\u6d41\u5909\u5316\u91cf\u306a\u306e\u3067\u672c\u767a\u8868\u3067\u306fFLOW\u306f\u8003\u5bdf\u3067\u304d\u3066\u3044\u306a\u3044\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e \u3057\u304b\u3057\u305d\u306e\u5f8c\uff0c\u8133\u8840\u6d41\u5909\u5316\u91cf\u304cNIRS\u7814\u7a76\u306e\u8ad6\u6587\u306e\u4e2d\u3067\u306a\u3093\u3068\u8868\u73fe\u3055\u308c\u3066\u3044\u308b\u304b\u78ba\u8a8d\u3057\u305f\u3068\u3053\u308d\uff0c\u3084\u306f\u308aChanges in CBF(Cerebral blood flow), measurement of CBF, Cerebral blood Oxygenation\u3068\u8868\u73fe\u3055\u308c\u3066\u304a\u308a\uff0cFLOW\u3067\u9593\u9055\u3044\u306a\u3044\u3053\u3068\u3092\u78ba\u8a8d\u3057\u307e\u3057\u305f\uff0e
\n\u307e\u305fNIRS\u4fe1\u53f7\u306f\u4e3b\u306b\u9759\u8108\u8840\u7531\u6765\u306eOxy-HB\u5909\u5316\u3068\u8003\u3048\u3089\u308c\u308b\u304c\uff0c\u8133\u8ce6\u6d3b\u9818\u57df\u3067\u306f\u8133\u8868\u304b\u3089\u8133\u5185\u3078\u3068\u5782\u76f4\u306b\u8d70\u308b\u8edf\u8108\u52d5\u8108(\u7d30\u52d5\u8108)\u307e\u3067\u9006\u884c\u6027\u306b\u62e1\u5f35\u304c\u751f\u3058\u308b\u305f\u3081\uff0c\u52d5\u8108\u30fb\u6bdb\u7d30\u8840\u7ba1\u5185\u306eOxy-HB\u5909\u5316\u3082\u7121\u8db3\u3067\u304d\u306a\u3044\u3068\u8003\u3048\u3089\u308c\u3066\u3044\u308b\u305d\u3046\u3067\u3059\uff0e\u3088\u3063\u3066\uff0c\u5404\u8840\u7ba1\u5185Hb\u5909\u5316\u306eNIRS\u4fe1\u53f7\u306b\u5bfe\u3059\u308b\u5bc4\u4e0e\u5ea6\u306f\uff0c\u691c\u51fa\u5149\u306e\u4f1d\u64ad\u7d4c\u8def\u5185\u306b\u304a\u3051\u308b\u8840\u7ba1\u5206\u5e03\u306b\u3088\u3063\u3066\u7570\u306a\u308b\u3068\u3044\u3046\u8fd4\u7b54\u304c\u6b63\u3057\u304b\u3063\u305f\u3088\u3046\u3067\u3059\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb92
\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u8ab2\u984c\u306e\u8a2d\u8a08\u3092\u6559\u3048\u3066\u304f\u3060\u3055\u3044\uff0e\u30ec\u30b9\u30c8\u3067\u97f3\u306f\u9cf4\u308a\u7d9a\u3051\u308b\u306e\u304b\uff1f\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u79c1\u306f\uff0c\u8ab2\u984c\u306e\u8aac\u660e\u3092\u884c\u3044\uff0c\u30ec\u30b9\u30c8\u3067\u3082\u97f3\u306f\u9cf4\u308a\u7d9a\u3051\u307e\u3059\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb93
\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u6ce8\u610f\u5ea6\u5408\u3044\u3092\u3069\u306e\u3088\u3046\u306b\u6c7a\u3081\u305f\u306e\u304b\uff1f\u306a\u305c\u6ce8\u610f\u5ea6\u5408\u3044\u3092\u5206\u3051\u3088\u3046\u3068\u601d\u3063\u305f\u306e\u304b\uff1f\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u79c1\u306f\uff0c \u6ce8\u610f\u5ea6\u5408\u3044\u306e\u691c\u8a0e\u65b9\u6cd5\u3092\u8aac\u660e\u3057\uff0c\u524d\u56de\u306e\u5b9f\u9a13\u3067\u660e\u3089\u304b\u306b\u306a\u3063\u305f\u500b\u4eba\u5dee\u306e\u8981\u56e0\u3092\u4f4e\u6e1b\u3059\u308b\u305f\u3081\u306b\u6ce8\u610f\u5ea6\u5408\u3044\u306e\u691c\u8a0e\u3092\u884c\u3063\u305f\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e
\n 
\n\u611f\u60f3
\n2\u6642\u9593\u3068\u3044\u3046\u77ed\u3044\u6642\u9593\u3067\u3057\u305f\u304c\uff0c10\u540d\u307b\u3069\u306e\u65b9\u3068\u304a\u8a71\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u306a\u304a\uff0cNIRS\u8a08\u6e2c\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u306b\u53c2\u52a0\u3057\u3066\u304a\u308a\uff0c\u5b9f\u9a13\u8a2d\u8a08\u3084\u89e3\u6790\u65b9\u6cd5\u306b\u5bfe\u3059\u308b\u8aac\u660e\u3092\u6c42\u3081\u3089\u308c\u308b\u3053\u3068\u304c\u975e\u5e38\u306b\u591a\u304b\u3063\u305f\u3067\u3059\uff0eMRI\u306b\u6bd4\u3079\u3066\uff0cNIRS\u7814\u7a76\u306f\u307e\u3060\u307e\u3060\u6570\u306f\u5c11\u306a\u304b\u3063\u305f\u3067\u3059\u304c\uff0cNeuroscience\u306b\u304a\u3044\u3066Attention\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u306b\u53c2\u52a0\u3057\u305f\u6642\u3088\u308a\u3082\uff0cNIRS\u7814\u7a76\u3082\u76db\u3093\u306b\u306a\u308aNIRS\u304c\u4e00\u822c\u7684\u306b\u8a8d\u77e5\u3055\u308c\u3066\u304d\u3066\u3044\u308b\u3088\u3046\u306b\u611f\u3058\u307e\u3057\u305f\uff0eNIRS\u30bb\u30c3\u30b7\u30e7\u30f3\u3068\u306f\u5225\u306e\u65e5\u306battention\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u3082\u3042\u308a\uff0c\u305d\u3061\u3089\u306b\u51fa\u305f\u307b\u3046\u304c\u7814\u7a76\u5185\u5bb9\u306e\u8cea\u554f\u306f\u5897\u3048\u305f\u304b\u3082\u3057\u308c\u306a\u3044\u3068\u6b8b\u5ff5\u306b\u3082\u601d\u3044\u307e\u3057\u305f\u304c\uff0cAttention\u30bb\u30c3\u30b7\u30e7\u30f3\u3067\u306f\u6ca2\u5c71\u516c\u8074\u3067\u304d\u305f\u306e\u3067\u826f\u304b\u3063\u305f\u3067\u3059\uff0e
\n 
\n 
\n\u8074\u8b1b
\n\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u8907\u6570\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e
\n\u2460<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Attentional load affects task-related brain activation but not task decoding\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Jason Chan, Aaron Kucyi, Joseph DeSouza\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Higher Cognitive Functions(Executive Function)
\nAbstract\u00a0 \uff1aIntroduction:
\nNeural resources are limited, and performing multiple tasks concurrently places a load on attention and results in disrupted task performance. While human neuroimaging studies have investigated the neural correlates of attentional load, how attentional load affects task processing is poorly understood. Here, we created an attentional load using a dual task paradigm, and examined task-related neural activity using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) with conventional univariate analysis and multivoxel pattern analysis (MVPA).
\nMethods:
\nBOLD fMRI scans (3.0T, T2*-weighted echo planar imaging, TR = 1970 ms, TE = 2.6 ms, flip angle = 78\u00b0, 64 x 64 matrix, 32 slices, voxel dimensions 3.3 x 3.3 x 3.3 mm) were acquired in 8 healthy adult subjects (4 females; mean age 26.6). Subjects performed blocks of pro-saccades and anti-saccades in alternation with fixation blocks (DeSouza et al., 2003), while a rapid serial visual presentation (RSVP) task was simultaneously presented during the pro-saccade and anti-saccade instruction cues to create an attentional load (Joseph et al., 1997; Chan and DeSouza, 2013). On 3 out of 6 total runs, subjects were instructed to ignore the RSVP task (i.e. pro-saccades and anti-saccades without RSVP). Subjects also performed an event-related pro-\/anti-saccade task with RSVP to define our regions of interest (ROIs): frontal eye fields (FEF), supplementary eye fields (SEF), intraparietal sulcus (IPS), and higher visual cortex (HVC). Neural activity related to pro-saccade and anti-saccade performance, in the absence and presence of an attentional load, was characterized using univariate analysis and MVPA. All preprocessing was performed in FSL (v5.0.1). Univariate general linear model analysis was used to assess mean activation levels within ROIs, for pro-saccades and anti-saccades, without and with RSVP. Mean percent signal change was compared between conditions using paired two-tailed t-tests with Bonferroni correction. MVPA was performed with the Pattern Recognition for Neuroimaging data Toolbox (PRoNTo v1.1) (Schrouff et al., 2013) using a support vector machine binary classifier. Pro-saccades were classified versus anti-saccades, without and with RSVP, for each ROI using a “leave-one-stimulus-pair-out” cross validation approach. To determine whether pro-saccades and anti-saccades were coded using similar activation patterns without RSVP compared to with RSVP, cross-trial type MVPA was also conducted. Decoding significance was tested with two-tailed t-tests versus 50% chance decoding with Bonferroni correction.
\nResults:
\nWhen pro-saccades and anti-saccades were performed without RSVP, activations in the L-IPS and R-IPS were significantly greater for anti-saccades compared to pro-saccades (p < 0.05), and there was a trend for activation to be greater for anti-saccades in the FEF and SEF. Task identity was significantly decoded in the L-FEF, L-IPS, and R-IPS (p < 0.05). When pro-saccades and anti-saccades were performed with RSVP, activations in almost all ROIs were significantly lower compared to saccade performance without RSVP (p < 0.05). In addition, pro-saccades and anti-saccades could not be differentiated based on mean activation in the FEF, SEF, or IPS. However, saccade task identity was significantly decoded in the R-FEF, L-IPS, R-IPS, and L-HVC (p < 0.05). Cross-trial type decoding revealed that task encoding without RSVP was similar to task encoding with RSVP, in the R-FEF, L-IPS, and R-IPS (p < 0.05).
\nConclusions:
\nIn this study, we demonstrated that attentional load affects mean activation, but not activation patterns, in brain areas commonly associated with pro-saccade and anti-saccade performance. These results suggest that attentional load may disrupt the strength of task-related neural activity, rather than the selection and identity of task representations.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0c\u8ab2\u984c\u95a2\u9023\u306e\u795e\u7d4c\u6d3b\u52d5\u3092fMRI\u306b\u3088\u3063\u3066\u89b3\u5bdf\u3057\uff0c\u6ce8\u610f\u8ca0\u8377\u304c\u3069\u306e\u3088\u3046\u306b\u8ab2\u984c\u51e6\u7406\u306b\u5f71\u97ff\u3057\u3066\u3044\u308b\u304b\u691c\u8a0e\u3059\u308b\u3068\u3044\u3046\u7814\u7a76\u767a\u8868\u3067\u3057\u305f\uff0e\u6ce8\u610f\u8ca0\u8377\u306f\u773c\u7403\u904b\u52d5\u5236\u5fa1\u306b\u95a2\u308f\u308b\u524d\u982d\u9802\u90e8\u306b\u304a\u3044\u3066\u5f71\u97ff\u3059\u308b\uff0e\u6ce8\u610f\u8ca0\u8377\u306f\u8ab2\u984c\u95a2\u9023\u90e8\u4f4d\u306e\u6d3b\u52d5\u3092\u6e1b\u3089\u3059\u3068\u7d50\u8ad6\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u6ce8\u610f\u8ca0\u8377\u306b\u3088\u3063\u3066\u6d3b\u52d5\u90e8\u4f4d\u304c\u7570\u306a\u308b\u306a\u3089\u3070\uff0c\u79c1\u306e\u7814\u7a76\u306b\u304a\u3044\u3066\u3082\u7740\u76ee\u90e8\u4f4d\u3092\u7d5e\u3089\u305a\u306b\u691c\u8a0e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\uff0e\u4eca\u5f8c\uff0c\u8133\u5168\u4f53\u3067\u6ce8\u610f\u5ea6\u5408\u3044\u306e\u7570\u306a\u308b\u3068\u304d\u306e\u8133\u6d3b\u52d5\u72b6\u614b\u3092\u691c\u8a0e\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
\n 
\n\u2461<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000The Functional Neuroanatomy of Tonic Alertness\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Clio COSTE, Andreas KLEINSCHMIDT\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Perception and Attention(Attention:Auditory\/Tactile\/Motor)
\nAbstract\u00a0 \uff1aIntroduction:
\nGrounded in the seminal work of Posner, decades of research have extensively investigated behavioral and neural aspects of attention (Petersen and Posner 2012). Behavioral and neurophysiological studies addressing sustained alertness have frequently employed long sessions with random occurrence of a given single target stimulus (Robertson et al. 1997) and have often also been conducted in sleep-deprived subjects. Yet, it can be argued that these paradigms collapse over the combined effects of arousal (when subjects struggle with staying awake), alertness (which we define as what ensures responding rapidly and correctly to whatever stimulus) and selective attention, the latter since the use of a single target constrains task-relevant sensory input to a predictable content. In the present experiment, we therefore attempted to study neural mechanisms of non-selective attention in rested participants.
\nMethods:
\nUsing functional neuroimaging (3 T, TR = 1.5 s) and a sparse event-related design with long, variable and unpredictable intervals (5s to 30s), we measured ongoing activity fluctuations and evoked responses in 16 healthy volunteers subjected to a vigilance task. Subject were instructed to respond as fast as possible whenever they detected any auditory or visual stimuli presented on top of the scanner’s background noise and visual white noise. We post-hoc sorted trials according to the individual subject’s median reaction time (RT) into fast and slow which we take to index high and low alertness, respectively. We extracted the fMRI signal time course from several resting-state functional connectivity (rs-fc) networks and regions of interest that were defined subject-by-subject. According to a priori hypotheses (Sadaghiani et al. 2009; Coste et al. 2011) we tested the effects of ongoing activity in a prestimulus baseline segment ranging from -1.5 s to 0 s for differences between short and long RT trials.
\nResults:
\nWe first examined the effects in areas that are of specific relevance for the task, notably the primary auditory and visual cortices. Greater pre-stimulus activity in the auditory cortex was followed by faster responses to auditory stimuli (p = 0.05) with no effect for visual stimuli (fig 1A); greater activity in visual cortex by faster responses to visual stimuli (p < 0.01) with no effect for auditory stimuli (fig. 1B). Building on our previous observations we probed activity in a cingulo-insular network putatively related to alertness and in several other so-called intrinsic connectivity networks. Confirming our initial hypothesis, trials with faster reaction times were preceded by higher activity in the cingulo-insular network (p = 0.01) and its constituent regions (Insula: p = 0.01; ACC: p = 0.003; Thalamus: p = 0.01) (Fig. 2A). Interestingly, higher default mode network activity was also associated with faster response speed (p = 0.01) (fig 2B). Dorsal attention network (DAN) activity was detrimental to performance speed on auditory trials (p = 0.04) but of no significant effect on visual trials (Fig. 2C).
\nConclusions:
\nAlthough myriad of studies of attention have used similar visual and auditory stimuli their focus has been on other aspects, e.g., selective, divided or cross-modal attention. In all these instances, the study of cue-induced or stimulus driven neural responses has proven useful to understand the neural bases of these facets of attention. Yet, with respect to non-selective attention as the topic of the present study we believe that such responses would not be interpretable because cues and target stimuli inevitably call upon selective attentional mechanisms. We therefore propose that ongoing activity variations are the most suitable, if not only, way to study whether and which neural structures are involved in maintaining sustained non-selective attention.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0c\u975e\u9078\u629e\u7684\u6ce8\u610f\u306e\u795e\u7d4c\u6a5f\u69cb\u306b\u7740\u76ee\u3057\u3066\u3044\u307e\u3059\uff0e\u5358\u4e00\u523a\u6fc0\u3092\u7528\u3044\u305f\u9577\u671f\u8ab2\u984c\u3092\u7761\u7720\u4e0d\u8db3\u88ab\u9a13\u8005\u306b\u5448\u793a\u3057\u6ce8\u610f\u529b\u3092\u8a08\u6e2c\u3059\u308b\u7814\u7a76\u3067\u306f\uff0c\u899a\u9192\u30fb\u8b66\u6212\u30fb\u9078\u629e\u7684\u6ce8\u610f\u306e\u30d1\u30e9\u30c0\u30a4\u30e0\u304c\u6df7\u5408\u3055\u308c\u3066\u3057\u307e\u3046\u305f\u3081\uff0c\u5b89\u9759\u72b6\u614b\u306e\u88ab\u9a13\u8005\u306e\u975e\u9078\u629e\u6027\u6301\u7d9a\u7684\u6ce8\u610f\u3092\u8a08\u6e2c\u3059\u308b\u3068\u3044\u3046\u7814\u7a76\u767a\u8868\u3067\u3057\u305f\uff0e\u79c1\u306e\u7814\u7a76\u306b\u3082DMN(Default Mode Network)\u306a\u3069\u95a2\u4e0e\u3057\u3066\u3044\u308b\u304b\u3082\u3057\u308c\u306a\u3044\u30fb\u691c\u8a0e\u3057\u306a\u3051\u308c\u3070\u3044\u3051\u306a\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u8996\u8074\u899a\u306e\u5448\u793a\u74b0\u5883\u3092\u7d71\u4e00\u3059\u308b\u305f\u3081\u306b\uff0c\u30d0\u30c3\u30af\u30b0\u30e9\u30a6\u30f3\u30c9\u30ce\u30a4\u30ba\u3068\u3057\u3066\uff0c\u97f3\u3060\u3051\u3067\u306a\u304f\u201dVisual White Noise (40fps)\u201d\u3092\u5448\u793a\u3057\u3066\u3044\u308b\u70b9\u3082\u9762\u767d\u3044\u306a\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n 
\n\u2462<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Neural correlates of objective and subjective proactive inhibition\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Matthijs Vink, Reinoud Kaldewaij, St\u00e9fan Du Plessis, Ren\u00e9 Kahn\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Higher Cognitive Functions(Executive Function)
\nAbstract\u00a0 \uff1a
\nIntroduction:
\nAnticipation plays an important role across all cognitive domains, including inhibition. Tasks that are used to study anticipation of stopping typically involve cues indicating the level of stop likelihood. However, whereas stop anticipation may on average match stop likelihood, this likely varies across trials. Here we investigate proactive control by investigating the effects of stop-signal likelihood and stop-signal anticipation on behaviour and brain activation using functional MRI and a modified stop task.
\nMethods:
\n20 participants performed a stop-signal anticipation task while being scanned with functional MRI (2D-EPI, TR = 1600ms, TE = 23ms, 683 scans). At the onset of each trial, stop likelihood was indicated by a cue. Next, participants indicated whether they anticipated a stop (yes\/no\/don’t know) via button press. We investigated the impact of stop likelihood (stop likelihood 0% versus stop likelihood > 0%) and stop anticipation (stop anticipated versus stop not anticipated) on activation during the cue period and the stimulus period for go trials, in regions defined in a previous study (Zandbelt et al., 2013).
\nResults:
\nAs expected, and in line with previous work (Jahfari et al., 2012; Verbruggen & Logan, 2008; Vink et al., 2005; Zandbelt & Vink, 2010), subjects slowed responding during the stimulus period when stop could occur (stop likelihood > 0%) as compared to when a stop could not occur (stop likelihood = 0%). Subjects indicated in about 50% of trials in which a stop could occur, that they actually anticipated a stop. Importantly, when stop likelihood >0%, subjects were slower when they anticipated a stop as compared to when they did not, revealing an additional effect of stop anticipation over stop likelihood. During the cue period, activation in the left premotor cortex (lPMC), striatum, and supplementary motor area (SMA) was increased when subjects anticipated a stop. In contrast, activation in these regions was not affected by stop likelihood. During the stimulus period, activation in the right inferior frontal gyrus (rIFG) and the right inferior parietal cortex (rIPC) increased when a stop could occur (stop likelihood >0%) compared to when it could not occur (stop likelihood 0%) related to stop likelihood. There was no difference in activation between trials in which participants anticipated a stop and trials in which they did not during this period.
\nConclusions:
\nTaken together, these data suggest that preparatory processes based on stop likelihood and stop anticipation both play an important role in proactive inhibitory control. Here we show for the first time that subjective anticipation of stopping affects behavior and brain activity. The striatum, lPMC and SMA are involved in stop anticipation. In contrast, activity in the rIFG and rIPC is not dependent on stop anticipation, but on stop likelihood, suggesting these areas are influenced by contextual information. The integration of both processes seems crucial for inhibitory control and, ultimately, successful goal-directed behavior.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0c\u4e8b\u524d\u306bCue(NOGO\u306e\u51fa\u73fe\u7387)\u304c\u5448\u793a\u3055\u308c\u308bGO\/NOGOtask\u3092\u7528\u3044\u3066\uff0cCue\u304c\u793a\u3059NOGO\u306e\u53ef\u80fd\u6027\u3068\u4e88\u6e2c\u306b\u57fa\u3065\u3044\u305f\u6e96\u5099\u30d7\u30ed\u30bb\u30b9\u306f\u6291\u5236\u5236\u5fa1\u306b\u304a\u3044\u3066\u91cd\u8981\u3067\u3042\u308b\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u308b\u3068\u3044\u3046\u7814\u7a76\u767a\u8868\u3067\u3057\u305f\uff0e\u79c1\u306e\u7814\u7a76\u3067\u7528\u3044\u3066\u3044\u308bGO\/NOGOtask\u3068\u306f\u7570\u306a\u308a\uff0c\u7d4c\u6642\u7684\u306b\u4f38\u3073\u308b\u30d0\u30fc\u3092\u30de\u30fc\u30af\u306e\u8fd1\u304f\u3067\u6b62\u3081\u308b(GO)\u304b\uff0c\u52dd\u624b\u306b\u6b62\u307e\u308b\u304b(NOGO)\u3092\u8a8d\u77e5\u3059\u308b\u3082\u306e\u3067\uff0c\u5b9f\u9a13\u8a2d\u8a08\u306e\u4ed5\u65b9\u3057\u3060\u3044\u3067\u69d8\u3005\u306a\u8133\u6a5f\u80fd\u3092\u8a08\u6e2c\u3067\u304d\u308b\u8ab2\u984c\u306a\u306e\u3060\u306a\u3042\u3068\u611f\u3058\u307e\u3057\u305f\uff0e\u4e8b\u524dCue\u3092\u5448\u793a\u3057\u3066\u3044\u306a\u304f\u3068\u3082\uff0c\u300c\u6b21\u306fGO\u304bNOGO\u306e\u3069\u3061\u3089\u306e\u4fe1\u53f7\u3060\u308d\u3046\u300d\u3068\u8003\u3048\u308b\u88ab\u9a13\u8005\u3082\u5b58\u5728\u3059\u308b\u3068\u8003\u3048\u3089\u308c\u308b\u306e\u3067\uff0cSMA(\u88dc\u8db3\u904b\u52d5\u91ce)\u4ed8\u8fd1\u306e\u6d3b\u52d5\u3082\u307f\u3066\u307f\u3088\u3046\u3068\u601d\u3044\u307e\u3059\uff0e
\n 
\n\u2463<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Attention modulates cerebral responses to conscious and unconscious tactile events\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Norman Forschack, Till Nierhaus, Matthias M\u00fcller, Arno Villringer\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aPerception and Attention(Attention:Auditory\/Tactile\/Motor)
\nAbstract\u00a0 \uff1a
\nIntroduction:
\nIt has been shown in invasive neurophysiological recordings as well as in non-invasive neuroimaging studies in humans that unconscious somatosensory stimulation, i.e. below perception threshold, can influence cortical processes [1,2,3,4]. Recently, we identified an event related potential (P60) and enhanced sensorimotor alpha (or mu) as corresponding markers in human EEG [5]. The purpose of the current study was to identify how selective tactile attention modulates cortical processing induced by subliminal stimulation. Furthermore, knowing the effect of attention might shed some light on the underlying neurophysiological correlates of processing subliminal stimuli.
\nMethods:
\nWe recorded EEG with 32 active Ag\/AgCl electrodes, while subjects (n=40) received 936 imperceptible electrical pulses over 26 two-minutes blocks to the left index finger, separated by 3.2s each, with a jitter of +\/- 1s. Additionally, in each block, up to four perceptible stimuli were randomly presented to the left or right hand (in total 104). Individual thresholds and the corresponding sub- and supraliminal stimulation intensities were assessed before the first experimental block and subsequently readjusted every time subjects completed a set of four blocks. Subjects’ task was to respond to perceived stimuli at the cued side and ignore stimuli at the other side. Accordingly, we derived two conditions where the unconsciously stimulated (i.e. left) hand was either attended or ignored and additionally four conditions where the conscious stimulation to the left or the right hand was either attended or ignored, respectively. The data was artifact corrected, stimulus locked event related potentials were calculated for each condition, sensorimotor alpha rhythm components were identified by means of independent component analysis and subsequently analyzed in time-frequency domain using morlet wavelets.
\nResults:
\nFor supraliminal stimulation we show the N80 component at posterior pericentral electrode sites was more pronounced in the ATTEND LEFT condition as compared to the IGNORE (ATTEND RIGHT) condition. Similarly, the event related suppression of Rolandic background rhythm was stronger in the ATTEND LEFT condition than in the IGNORE (ATTEND RIGHT) condition. These results confirm previous studies.
\nFor subliminal stimulation, we confirm that it evokes a P60 and an increase in background alpha rhythm. Interestingly, attention influenced the two EEG features differentially. The P60 component was more pronounced in the ATTEND LEFT condition than in the IGNORE (ATTEND RIGHT) condition. The early increase of sensorimotor alpha rhythm (around 150 to 200 ms), however, was stronger in the IGNORE (ATTEND RIGHT) condition than in the ATTEND LEFT condition. Interestingly, in the ATTEND LEFT condition, an increase in sensorimotor alpha rhythm strength occurred later (from around 200 to 300 ms, see figure 1).
\nConclusions:
\nThe differential impact of attention on the two EEG-signatures of subliminal processing in the contralateral cortex indicates different underlying neurophysiological events. The P60 component seems to reflect a cortical component which is “sensitized by attention”, i.e. be regarded as a task-relevant feature [8]. On the other hand, the enhancement of early induced alpha rhythm, when attention is NOT on the stimulated finger (IGNORE condition), seems to be consistent with the proposed functional role of alpha as being a mediator of inhibitory gating [9]: the (early) increase of mu activity may reflect a higher “susceptibility” for local inhibitory processing in the IGNORE condition.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0c\u6ce8\u610f\u306f\u95be\u5024\u4ee5\u4e0b(\u611f\u77e5\u3067\u304d\u306a\u3044)\u306e\u4f53\u5236\u611f\u899a\u523a\u6fc0\u306b\u5bfe\u3057\u3066\u76ae\u8cea\u53cd\u5fdc\u3092\u8abf\u6574\u3057\u3066\u3044\u308b\u304b\uff1f\u95be\u4e0a\u523a\u6fc0\u3068\u95be\u4e0b\u306e\u523a\u6fc0\u51e6\u7406\u306f\u795e\u7d4c\u30de\u30fc\u30ab\u30fc\u306b\u95a2\u3057\u3066\u3069\u3046\u7570\u306a\u3063\u3066\u3044\u308b\u304b\uff1f\u3092EEG\u3092\u7528\u3044\u3066\u8abf\u3079\u308b\u3068\u3044\u3046\u7814\u7a76\u767a\u8868\u3067\u3057\u305f\uff0e\u79c1\u306e\u7814\u7a76\u306f\u8a8d\u77e5\u3067\u304d\u308b\u524d\u63d0\u3067\u6ce8\u610f\u3092\u8a08\u6e2c\u3057\u3066\u3044\u307e\u3059\u304c\uff0c\u8a8d\u77e5\u3067\u304d\u306a\u3044\u30ce\u30a4\u30ba\u306a\u3069\u3082\u76ae\u8cea\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u3066\u3044\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u304b\u3082\u3057\u308c\u306a\u3044\u3068\u8003\u3048\u308b\u304d\u3063\u304b\u3051\u3068\u306a\u308a\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u523a\u6fc0\u304c\u5448\u793a\u3055\u308c\u308b\u5de6\u53f3\u306e\u3069\u3061\u3089\u304b\u306e\u6307\u306b\u6ce8\u610f\u3092\u5411\u3051\u3066\u304a\u304f\u65b9\u304c\uff0c\u8133\u6ce2\u632f\u5e45\u304c\u5927\u304d\u304f\u306a\u308b\u3089\u3057\u3044(CP4\u4ed8\u8fd1)\uff0e\u6ce8\u610f\u3092\u5411\u3051\u308b\u3068\u8a8d\u77e5\u611f\u5ea6\u304c\u826f\u304f\u306a\u308b\u306e\u306f\u4e88\u60f3\u3067\u304d\u308b\u304c\uff0c\u611f\u77e5\u3067\u304d\u306a\u3044\u523a\u6fc0\u306e\u8a8d\u77e5\u307e\u3067\u5f71\u97ff\u3055\u308c\u308b\u3068\u3044\u3046\u7d50\u679c\u306b\u306f\u9a5a\u304d\u307e\u3057\u305f\uff0e\u6ce8\u610f\u6a5f\u80fd\u306f\u3084\u306f\u308a\u8a8d\u77e5\u6a5f\u80fd\u5168\u822c\u306b\u95a2\u4e0e\u3059\u308b\u91cd\u8981\u306a\u8133\u6a5f\u80fd\u3067\u3042\u308b\u3068\u518d\u8a8d\u8b58\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u2464<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000PpTMS reveals probability-dependent changes in connectivity between rIFC-M1 on go\/nogo task\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Dilene van Campen, Franz-Xaver Neubert, Wery van den Wildenberg, K. Richard Ridderinkhof, Rogier Mars\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Higher Cognitive Functions(Decision Making)
\nAbstract\u00a0 \uff1a
\nIntroduction:
\nThe functional role of the right inferior frontal cortex (rIFC) in mediating human behavior is the subject of ongoing debate. Activation of the rIFC has been associated with both response inhibition and with signaling action adaptation demands resulting from unpredicted events (Garavan et al., 1999; Ridderinkhof et al. 2011; Vossel et al. 2011). The goal of this study is to investigate the role of rIFC by combining a go\/no-go paradigm with paired-pulse transcranial magnetic stimulation (ppTMS) over rIFC and the primary motor cortex (M1) to probe the functional connectivity between these brain areas. We hypothesized that if rIFC is involved primarily in response inhibition, then rIFC should exert an inhibitory influence over M1 on no-go (inhibition) trials regardless of no-go probability. If, by contrast, rIFC has a role on unexpected trials other than just response inhibition then rIFC should influence M1 on infrequent trials regardless of response demands.
\nMethods:
\nIn total twelve participants performed a go\/no-go task with 20% or 80% of the trials requiring response inhibition (no-go trials) in a classic and a reversed version of the task, respectively. To probe the influence of rIFC on the motor cortex, the functional connectivity between rIFC and M1 was assessed using paired-pulse transcranial magnetic stimulation (ppTMS). In this procedure, a single “test” TMS pulse is delivered over the hand representation of left M1 to elicit a motor-evoked potential (MEP) in the EMG recorded from the effector muscle. On half of the trials, a “conditioning” TMS pulse over rIFC precedes the test pulse over M1. By calculating the ratio of the MEP amplitude recorded on paired-pulse and single-pulse trials, the influence of rIFC on the motor cortex is assessed (Buch et al., 2010; Neubert et al., 2010). This is reported as the paired pulse effect (PPE). TMS pulses were delivered at one of three time intervals after stimulus onset, namely 75, 125, or 175 ms. Overall, for each SOA there were 32 single-pulse trials (sp) and 32 paired-pulse trials (pp), resulting in a total of 192 TMS pulse trials distributed over go and no-go trials per experiment.
\nResults:
\nBehaviorally, responses were slower to infrequent compared to frequent go trials (431 ms vs. 333 ms), while commission errors were more prevalent to infrequent compared to frequent no-go trials (20.8% vs. 0.3%).
\nOverall, differences in MEP amplitudes between the experiments were found indicating a different pattern of activation. Most important, facilitatory PPEs were observed not only on infrequent no-go trials, but also on infrequent go trials. The time difference between these PPEs (maximal at 125 and 175 ms after stimulus presentation, respectively) likely reflects the corresponding difference in response speed between the two contexts. Additionally, in case of frequent no-go trials, an inhibitory PPE was found that peaked around 125 ms after stimulus presentation
\nConclusions:
\nWe observed that rIFC suppressed M1 excitability during frequent no-go trials, but not during infrequent no-go trials, suggesting that the role of rIFC in response inhibition is context dependent rather than generic. Importantly, rIFC was found to facilitate M1 excitability on all low frequent trials, irrespective of whether the infrequent event involved response inhibition, a finding more in line with a predictive coding framework of cognitive control.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306f\uff0cGO\/NOGO task\u4e2d\u306e\uff0c\u53f3\u4e0b\u524d\u982d\u56de\u3068\u4e00\u6b21\u904b\u52d5\u91ce\u9593\u306e\u8133\u6d3b\u52d5\u3092\uff0c\u30d1\u30eb\u30b9\u7d4c\u982d\u84cb\u78c1\u6c17\u523a\u6fc0\uff08ppTMS\uff09\u3067\u8a08\u6e2c\u3057\uff0c\u53f3\u4e0b\u524d\u982d\u56de\u306e\u5f79\u5272\u3092\u8abf\u67fb\u3059\u308b\u3068\u3044\u3046\u7814\u7a76\u767a\u8868\u3067\u3057\u305f\uff0e\u7d50\u8ad6\u3068\u3057\u3066\uff0c\u4e00\u822c\u7684\u306b\uff0c\u53cd\u5fdc\u6291\u5236\u3060\u3051\u306e\u3068\u304d\u3088\u308a\u3082\uff0c\u4e88\u671f\u305b\u306c\u523a\u6fc0\u4fe1\u53f7\u3078\u306e\u884c\u52d5\u9069\u5fdc\u304c\u8981\u6c42\u3055\u308c\u305f\u3068\u304d\u306b\uff0c\u53f3\u4e0b\u524d\u982d\u56de\u306f\u4e00\u6b21\u904b\u52d5\u91ce\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u3068\u3057\u3066\u3044\u307e\u3059\uff0e\u79c1\u3082\u53f3\u4e0b\u524d\u982d\u56de\u30fb\u6ce8\u610f\u30fbGO\/NOGO\u306b\u7740\u76ee\u3057\u3066\u3044\u308b\u306e\u3067\uff0c\u53f3\u4e0b\u524d\u982d\u56de\u306e\u5f79\u5272\u3084\u3069\u3093\u306a\u3068\u304d\u306b\u3069\u3053\u3068\u63a5\u7d9a\u6027\u304c\u5f37\u304f\u306a\u308b\u304b\uff1f\u3068\u3044\u3046\u7814\u7a76\u306f\u3068\u3066\u3082\u9762\u767d\u304f\u611f\u3058\u307e\u3057\u305f\uff0eTMS\u306b\u3064\u3044\u3066\u7406\u89e3\u3067\u304d\u306a\u304b\u3063\u305f\u306e\u3067\u3059\u304c\uff0cNIRS\u4fe1\u53f7\u306e\u3088\u3046\u306a\u4ee3\u8b1d\u7269\u3092\u6e2c\u5b9a\u3057\u305f\u4fe1\u53f7\u3067\u3082\uff0c\u5b9f\u9a13\u8a2d\u8a08\u6b21\u7b2c\u3067\u3088\u308a\u591a\u304f\u306e\u3053\u3068\u304c\u89e3\u660e\u3067\u304d\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u8003\u3048\u307e\u3057\u305f\uff0e\u305d\u306e\u65b9\u6cd5\u306b\u3064\u3044\u3066\u306f\u4eca\u5f8c\u691c\u8a0e\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
\n 
\n\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n\u6749\u7530\u51fa\u5f25<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u8ab2\u984c\u306e\u96e3\u6613\u5ea6\u5909\u5316\u306b\u3088\u308b\u6210\u7e3e\u306e\u9055\u3044\u304c\u8133\u6d3b\u52d5\u306b\u4e0e\u3048\u308b\u5f71\u97ff<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nThe differences of changing task difficulties on brainactivities between high and low score groups<\/td>\n<\/tr>\n
\u8457\u8005<\/strong><\/td>\n\u5c71\u672c\u8a69\u5b50\uff0c\u6749\u7530\u51fa\u5f25\uff0c\u5ee3\u5b89\u77e5\u4e4b,<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/strong><\/td>\nOrganization for Human Brain Mapping<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nOHBM2014<\/td>\n<\/tr>\n
\u4f1a\u5834<\/strong><\/td>\n\u30cf\u30f3\u30d6\u30eb\u30af\u30b3\u30f3\u30b0\u30ec\u30b9\u30bb\u30f3\u30bf<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2014\/06\/08-2014\/06\/12<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n 
\n1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30
\n2014\/06\/08\u304b\u30892014\/06\/12\u306b\u304b\u3051\u3066\uff0c\u30cf\u30f3\u30d6\u30eb\u30af\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fOHBM2014\uff11\uff09<\/sup>\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\uff0cOrganization for Human Brain Mapping\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u305f\u7814\u7a76\u4f1a\u3067\u4eba\u9593\u306e\u8133\u30de\u30c3\u30d4\u30f3\u30b0\u3092\u8abf\u67fb\u3057\uff0c\u6700\u5148\u7aef\u3068\u8d77\u5de5\u7814\u7a76\u306e\u4ea4\u63db\u3092\u3059\u308b\u305f\u3081\u306e\u6559\u80b2\u30d5\u30a9\u30fc\u30e9\u30e0\u3092\u63d0\u4f9b\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e
\n\u79c1\u306f\u5168\u65e5\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5c71\u672c\u5148\u751f\uff0c\u6a2a\u5185\u5148\u751f\uff0c\u6728\u6751\uff0c\u5c06\u7a4d\uff0c\u5f8c\u85e4\uff0c\u65e9\u5ddd\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
\n\u30fb\u305d\u306e\u8b1b\u6f14\u4f1a\u304c\uff0c\u3069\u3046\u3044\u3046\u4e3b\u65e8\uff0c\u7814\u7a76\u9818\u57df\u306e\u7814\u7a76\u4f1a\u306a\u306e\u304b\u306b\u3064\u3044\u3066\u8aac\u660e
\n\u30fb\u8b1b\u6f14\u4f1a\u306eWeb\u30b5\u30a4\u30c8\u304c\u3042\u308b\u306a\u3089\uff0c\u8b1b\u6f14\u4f1a\u540d\u306e\u70b9\u3067\u53c2\u7167\u3059\u308b
\n\u30fb\u81ea\u5206\u306e\u53c2\u52a0\u65e5\u7a0b\u3068\uff0c\u4ed6\u306e\u53c2\u52a0\u8005\u306b\u3064\u3044\u3066\u8aac\u660e
\n 
\n2. \u7814\u7a76\u767a\u8868
\n2.1. \u767a\u8868\u6982\u8981
\n\u79c1\u306f9\u65e5\u306e\u5348\u5f8c\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u300cPoster session\u300d\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c2\u6642\u9593\u30dd\u30b9\u30bf\u30fc\u524d\u306b\u7acb\u3063\u3066\u3044\u3066\uff0c\u898b\u306b\u3053\u3089\u308c\u305f\u65b9\u306b\u8aac\u660e\u3059\u308b\u3068\u3044\u3046\u6d41\u308c\u3067\u3057\u305f\uff0e
\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u300cThe differences of changing task difficulties on brain
\nactivities between high and low score groups\u300d\u3068\u3044\u3046\u984c\u76ee\u3067\u884c\u3044\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
Introduction:In recent years, brain functions have been observed using functional brain imaging techniques,\u3000and studied actively. In an experiment measuring brain functions, an appropriate task is selected\u3000and used to accomplish the purpose of the study. However, the result of the task performance is
\nquite different among each subject. So, even if a number of subjects perform the same task, it is\u3000considered the effects of the task on brain activities are varied among individuals [2]. In this\u3000research, the effects of changing task difficulties on brain activities and its relationship to the result of a task performance are studied.
\nMethods:
\nIn this experiment, the subjects were to perform an auditory go\/nogo tasks. The difficulty of the\u3000task was determined by changing the differences in frequency between go and nogo stimuli. A go\u3000stimulus was set at 1000 Hz, and six kinds of nogo stimuli were prepared and they were set at\u30001020, 1030, 1040, 1050, 1060 or 1100 Hz. It was assumed the smaller the frequency differences\u3000between go and nogo stimuli got, the higher the difficulty of the task was. The task performance\u3000was evaluated based on results of the error rate and the reaction time on a go\/nogo task. The\u3000cerebral blood flow (CBF) in both sides of lateral and prefrontal cortex under a go\/nogo task was\u3000measured using functional near-infrared spectroscopy (fNIRS). Twelve healthy adults (male: five,\u3000female: seven) participated as the subjects of the experiment in this study.
\nResults:
\nWe calculated an average integrated value of Oxy-Hb during a task among subjects. The CBF of\u3000the frontal pole cortex (FPC) activated significantly under the nogo stimulus of 1060Hz, and the\u3000magnitude was tend to decrease with more difficult task. As a result of one-way ANOVA, the\u3000significant difference was seen in IFC among difficulties [F(5,66)=4.3169, p < .05]. On the other\u3000hand, CBF of the right inferior frontal cortex (IFC) had shown the strongest activity under nogo\u3000stimulus of 1030Hz. The less task difficulty was tend to reduce the activity level. As a result of\u3000one-way ANOVA, the significant difference wasn’t seen in IFC among difficulties [F(5,66)=0.864,\u3000p > .05]. Since it’s said FPC contributes greatly to the ability to judge [5], it’s suggested all the\u3000subjects can discriminate between go and nogo stimuli on relatively easy tasks. On the other\u3000hand, based on the result of IFC which there wasn’t a significant difference in changing the level\u3000of difficulties, brain activations on IFC vary greatly among individuals. So, in order to clarify the\u3000relationship between the effect of changing level of task difficulties and the performance of the\u3000task, the subjects were classified into two groups according to the task performance; the high\u3000score group (HSG) and the low score group (LSG). In IFC, CBF of HSG had the strongest activity\u3000under nogo stimulus of 1030Hz, and was trend to decrease where the task difficulty was lower.\u3000Meanwhile, any trend was observed in CBF of LSG. As a result of one-way ANOVA, the result of\u3000HSG had a significant difference among difficulties [F(5,30)=3.871, p < .05], while the result of\u3000LSG had no significant difference among difficulties [F(5,30)=0.702\uff0cp > .05]. It’s said inhibitorycontrol is mainly functioned during go\/nogo tasks [1,3,4]. Through this experiment, it’s suggested\u3000the more difficult the task gets, the greater the brain activities gets in HSG. This consideration\u3000corresponds to the fact that IFC contributes greatly to inhibitory control.
\nConclusions:
\nIn order to investigate effects of the task performance on brain activities, we measured brain\u3000activities under an auditory go\/nogo task using fNIRS. In IFC, which is known to contribute to the\u3000inhibitory control, the subjects in HSG had a trend in which the brain activities were increased as\u3000the tasks got more difficult. On the other hand, any trend was observed in CBF of LSG. From the\u3000above discussion, there’s differences of changing task difficulties on brain activities between high\u3000and low score groups.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n\u30fb\u81ea\u5206\u306e\u8b1b\u6f14\u65e5\u7a0b\uff0c\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\uff0c\u767a\u8868\u5f62\u5f0f
\n\u30fb\u4eca\u56de\u306e\u767a\u8868\u5185\u5bb9\u306b\u3064\u3044\u3066\u7c21\u5358\u306b\u8aac\u660e
\n2.2. \u8cea\u7591\u5fdc\u7b54
\n\u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>1<\/strong>
\n\u6771\u5317\u5927\u5b66\u6240\u5c5e\u306e\u5859\u3000\u6749\u5b50\u5148\u751f\u304b\u3089\u306e\u8cea\u554f\u3067\u3059\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306fNIRS\u306e\u6e2c\u5b9a\u4f4d\u7f6e\u306e\u518d\u73fe\u6027\u3092\u9ad8\u3081\u308b\u305f\u3081\u306b\u3057\u3066\u3044\u308b\u3053\u3068\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u79c1\u306f\uff0c\u56fd\u969b10\uff0d20\u6cd5\u306b\u6e96\u62e0\u3057\uff0c\u30d7\u30ed\u30fc\u30d6\u4f4d\u7f6e\u3092\u8a2d\u5b9a\u3057\u3066\u3044\u308b\u304c\uff0c\u500b\u4eba\u5dee\u304c\u5927\u304d\u3044\u306e\u3067\u307e\u3060\u691c\u8a0e\u6bb5\u968e\u3067\u3042\u308b\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e\u307e\u305f\u305d\u306e\u4ed6\u306b\u3082\uff0cNIRS\u306e\u30c7\u30fc\u30bf\u51e6\u7406\u65b9\u6cd5\u306b\u3064\u3044\u3066\u5206\u6563\u5206\u6790\u306e\u884c\u3044\u65b9\u306e\u78ba\u8a8d\u3084\uff0c\u8133\u306e\u4f4d\u7f6e\u306e\u8868\u3057\u65b9\u3092\u30d6\u30ed\u30fc\u30c9\u30de\u30f3\u3067\u793a\u3057\u305f\u65b9\u304c\u660e\u78ba\u3060\u304b\u3089\u3088\u3044\u3068\u30a2\u30c9\u30d0\u30a4\u30b9\u3092\u53d7\u3051\u307e\u3057\u305f\u3002
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
\n\u52a0\u85e4\u4fca\u5fb3\u5148\u751f\u304b\u3089\u306e\u8cea\u554f\u3067\u3059\uff0e\u8cea\u554f\u5185\u5bb9\u306f\u4e0b\u524d\u982d\u56de\u306e\u53f3\u3057\u304b\u307f\u3066\u3044\u306a\u3044\u304c\uff0c\u5de6\u53f3\u5dee\u306f\u3069\u306e\u3088\u3046\u306a\u304a\u306e\u3067\u3042\u3063\u305f\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306f\u60f3\u5b9a\u8cea\u554f\u3067\u3042\u308a\uff0c\u5de6\u53f3\u3067\u540c\u3058\u50be\u5411\u306f\u898b\u3089\u308c\u305f\u304c\u53f3\u306e\u50be\u5411\u306e\u307b\u3046\u304c\u5f37\u304b\u3063\u305f\u3068\u7b54\u3048\u308b\u3079\u304d\u3067\u3057\u305f\u304c\uff0c\u691c\u8a0e\u6bb5\u968e\u3068\u7b54\u3048\u3066\u3057\u307e\u3063\u305f\u306e\u3067\uff0c\u5de6\u53f3\u5dee\u306a\u3093\u3066\u898b\u308b\u3060\u3051\u3067\u3057\u3087\u3068\u3044\u3046\u8fd4\u4e8b\u3092\u3046\u3051\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
\n\u5973\u6027\u306e\u5916\u56fd\u4eba\u306e\u65b9\u304b\u3089\uff0c\u6210\u7e3e\u3068\u8133\u6d3b\u52d5\u306e\u95a2\u4fc2\u6027\u306f\u3069\u306e\u3088\u3046\u306a\u3082\u306e\u304b\u3068\u3044\u3046\u8cea\u554f\u3092\u3046\u3051\u307e\u3057\u305f\uff0e\u8ab2\u984c\u306e\u96e3\u6613\u5ea6\u306b\u5bfe\u3059\u308b\u50be\u5411\u306f\u898b\u3048\u308b\u304c\uff0c\u4f8b\u5916\u306e\u96e3\u6613\u5ea6\u3092\u9664\u304d\uff0c\u76f8\u95a2\u95a2\u4fc2\u306a\u3069\u3067\u793a\u305b\u305f\u3089\u3088\u308a\u3088\u3044\u3068\u30a2\u30c9\u30d0\u30a4\u30b9\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e\u3053\u306e\u3088\u3046\u306a\u5185\u5bb9\u306b\u95a2\u3057\u3066\uff0c\u8133\u6a5f\u80fd\u30de\u30c3\u30d4\u30f3\u30b0\u3067\u3082\u30a2\u30c9\u30d0\u30a4\u30b9\u3092\u53d7\u3051\u305f\u306e\u3067\u89e3\u6790\u3092\u884c\u3063\u3066\u307f\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e\u307e\u305f\u305d\u306e\u65b9\u306f\u81ea\u8eab\u306e\u7814\u7a76\u3067nback\u8ab2\u984c\u6642\u306e\u96e3\u6613\u5ea6\u306b\u3088\u308b\u5909\u5316\u50be\u5411\u3092\u898b\u3066\u3044\u3066\uff0c3back\u306e\u7d50\u679c\u306f\u500b\u4eba\u5dee\u304c\u5927\u304d\u3044\u3068\u304a\u3063\u3057\u3083\u3063\u3066\u3044\u307e\u3057\u305f\uff0e\u96e3\u6613\u5ea6\u306b\u95a2\u3059\u308b\u7814\u7a76\u306f\u4ed6\u306e\u7814\u7a76\u3067\u3082\u7740\u76ee\u3055\u308c\u3066\u3044\u3066\uff0c\u9762\u767d\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
\n 
\n\u8cea\u554f\u5185\u5bb9<\/strong>4<\/strong>
\n\u7537\u6027\u306e\u5916\u56fd\u306e\u65b9\u304b\u3089\uff0c\u8ab2\u984c\u306e\u96e3\u6613\u5ea6\u8a2d\u5b9a\u3092\u3069\u306e\u3088\u3046\u306b\u884c\u3063\u3066\u3044\u308b\u304b\u3068\u3044\u3046\u8cea\u554f\u3092\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u82f1\u8a9e\u304c\u308f\u304b\u308c\u3070\u3082\u3046\u5c11\u3057\u8a71\u304c\u5e83\u304c\u308b\u306e\u304b\u306a\u3042\u3068\u6b8b\u5ff5\u306a\u601d\u3044\u3092\u3057\u305f\u306e\u3067\uff0c\u82f1\u4f1a\u8a71\u80fd\u529b\u3092\u9ad8\u3081\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
\n\u30fb\u8cea\u554f\u3092\u7c21\u6f54\u306b\u66f8\u304f
\n\u30fb\u8cea\u554f\u8005\u306e\u6240\u5c5e\u3068\u540d\u524d\u3092\u63a7\u3048\u3066\u3044\u308c\u3070\u66f8\u304f
\n\u30fb\u8cea\u554f\u306b\u5bfe\u3059\u308b\u56de\u7b54\u3092\u66f8\u304f
\n 
\n2.3. \u611f\u60f3
\n\u305d\u306e\u4ed6\u306b\u30824\u4eba\u306e\u65b9\u306b\u898b\u306b\u6765\u3066\u3044\u305f\u3060\u304d\uff0c\u79c1\u306e\u7814\u7a76\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u4e0b\u3055\u308b\u3053\u3068\u304c\u3059\u3054\u304f\u5b09\u3057\u304b\u3063\u305f\u3067\u3059\uff0e\u3057\u304b\u3057\u4eca\u56de\u306f2\u6642\u9593\u3068neuroscience\u3088\u308a\u3082\u77ed\u304b\u3063\u305f\u305f\u3081\uff0c\u82f1\u8a9e\u306b\u6163\u308c\u308b\u524d\u306b\u7d42\u308f\u3063\u3066\u3057\u307e\u3063\u305f\u3068\u3044\u3046\u601d\u3044\u3082\u3042\u308a\u307e\u3057\u305f\uff0e\u4eca\u5f8c\u306e\u4eba\u751f\u306b\u5411\u3051\u3066\u82f1\u4f1a\u8a71\u80fd\u529b\u3092\u3055\u3089\u306b\u9ad8\u3081\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3068\u3044\u3046\u8ab2\u984c\u304c\u51fa\u6765\u3066\u3044\u3044\u6a5f\u4f1a\u3068\u306a\u308a\u307e\u3057\u305f\uff0e
\n\u307e\u305fOral\u30bb\u30c3\u30b7\u30e7\u30f3\u306b\u3082\u53c2\u52a0\u3059\u308b\u6a5f\u4f1a\u304c\u591a\u304f\u3042\u308a\uff0c\u5b66\u4f1a\u306e\u96f0\u56f2\u6c17\u3092\u611f\u3058\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u4f1a\u5834\u306e\u5e83\u3055\u306f\u76f4\u611f\u7684\u306bneuroscience\u306e5\u5206\u306e1\u7a0b\u5ea6\u3060\u3063\u305f\u304b\u306a\u3068\u601d\u3044\u307e\u3059\uff0e
\n 
\n3. \u8074\u8b1b
\n\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e5\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Effect of attention on early auditory evoked gamma band response in healthy subjects – an MEG study\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aNenad Polomac, Gregor Leicht, Guido Nolte, Christina Andreou, Till Schneider, Saskia Steinmann, Andreas Engel, Christoph Mulert
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aAttention: Auditory\/Tactile\/Motor<\/p>\n

Abstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/h4>\n

Auditory early evoked gamma-band magnetic fields were first described more than twenty years ago by Pantev and colleagues. Debener et al. (2003) have found stronger early auditory evoked gamma band response (aeGBR) to target than to the standard stimuli in the oddball paradigm using EEG. Furthermore, they emphasized the importance of the aeGBR in the top-down attentional processing of an auditory stimuli. It was also shown that the power of the aeGBR is increased with task difficulty. Our group has described BOLD correlates of the aeGBR in the auditory cortex and the dorsal anterior cingulate cortex (dACC) using simultaneous EEG-fMRI methodology (Mulert et al., 2010). Now we were interested in the functional connectivity between auditory cortices and dACC using MEG.
\nMethods:
\nWe investigated the aeGBR in 13 healthy participants using a 275-channel CTF-MEG system. The experimental paradigms were two auditory choice reaction tasks. The first task (difficult condition-DC) consisted of three tones (~100 ms; 80 dB) of different pitch: the low (800 Hz), the medium (1000 Hz) and the high (1200 Hz). Each of these tones were presented in pseudorandomized sequence and ISI: 2.5\u20137.5 s, mean: 5 s. Participants were told to respond as fast as possible with the left or right button press to the low tone or the high tone, respectively. The middle tone wasn’t target for button press. The second task (easy condition-EC) contained only low pitch tone (ISI: 2.5\u20137.5 s, mean: 5 s). Again subjects were asked to respond promptly to this tone with left button press. These tasks differ in attentional demand.
\nResults:
\nResults: Using the eLORETA algorithm we localized the aeGBR in both auditory cortices and midline structures. Furthermore, we found significantly increased power in dACC during the DC compared to the EC (Figure). In addition, the functional connectivity (lagged phase synchronization) between auditory cortices and dACC was significantly stronger during DC compared to EC.
\n 
\nConclusions:
\nThese findings provide further evidence for the interaction of the dACC and auditory areas during auditory attentional processes.
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u767a\u8868\u306fMEG\u3092\u7528\u3044\u3066\uff0c\u96e3\u3057\u3044\u6761\u4ef6\u3068\u6613\u3057\u3044\u6761\u4ef6\u9593\u306e\u6d3b\u6027\u304c\u3069\u306e\u3088\u3046\u306b\u7570\u306a\u308b\u304b\u3068\u3044\u3046\u3053\u3068\u3092\u7814\u7a76\u3057\u3066\u3044\u308b\u3082\u306e\u3067\u3059\uff0e\u7d50\u679c\u306f\uff0c\u96e3\u3057\u3044\u6761\u4ef6\u304c\u6613\u3057\u3044\u6761\u4ef6\u3088\u308a\u3082\u6d3b\u6027\u91cf\u304c\u5927\u304d\u3044\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u79c1\u306e\u7814\u7a76\u3068\u3082\u8fd1\u3044\u5185\u5bb9\u3067\u3042\u308a\uff0c\u3068\u3066\u3082\u8208\u5473\u6df1\u304b\u3063\u305f\u3067\u3059\uff0e\u307e\u305fMEG\u306e\u7d50\u679c\u3092\u793a\u3057\u305f\u4e0a\u56f3\u304c\u7f8e\u3057\u304b\u3063\u305f\uff0e\u524d\u90e8\u5e2f\u72b6\u56de\u306b\u7740\u76ee\u3057\u3066\u304a\u308a\uff0c\u79c1\u304cNIRS\u3067\u8a08\u6e2c\u3067\u304d\u3066\u3044\u306a\u3044\u90e8\u4f4d\u306b\u304a\u3044\u3066\u3082\u96e3\u6613\u5ea6\u306e\u9055\u3044\u304c\u898b\u3089\u308c\u308b\u3053\u3068\u304c\u5206\u304b\u308a\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aVerbal and executive abilities enhanced by cortical signal complexity post short-term music training\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSarah Carpentier, Sylvain Moreno, Anthony McIntosh
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Music
\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Introduction:
\nIt has been previously suggested that brain signal variability, or “complexity,” can serve as a measure of an individual’s functional repertoire, where higher variability supports a wider range of dynamic configurations and is associated with a more adaptable neural system (McIntosh, 2008). Therefore, higher complexity in the human brain might promote general, and music specific, cognition (McIntosh, 2008; Tononi, 1998). Music training has been previously associated with transfer to improvements on non-musical behaviours (Moreno, 2009). Recently, short-term musical training was associated with increased signal complexity, during a passive verbal task, in auditory and domain-general cortex important for ‘executive’ cognition (Carpentier, in prep), and interregional cortical communication (Hagmann, 2008). Participants in the present study were children that displayed improvements in verbal intelligence and executive task performance following only 20 days of musical training, compared to no changes observed in children who received similar visual art training (Moreno, 2011). We propose that these behavioural improvements are associated with increased neural complexity.
\nMethods:
\nParticipants were 64 children, 32 (18 girls) who received visual-art training and 32 (20 girls) who received music training. Nice children did not complete EEG recording, and 7 participants were excluded because of excessive noise in the EEG signal (N=48 participants, n= 24 in each training group). Training curricula and tasks are detailed in Moreno et al., 2011. Training sessions were 1 hours, twice a day, for 20 days. All children completed the WPPSI-III Vocabulary subtest (Wechsler, 2002) and a visual Go\/No-go task (Moreno, 2011) before and after training. EEG was recorded during Go\/No-go task performance.
\nEEG was recorded using an 64+8 ActiveTwo system (Biosemi) at a sampling rate of 512 Hz. Because interactions due to both local dense interconnectivity and sparse long-range projections give rise to the outputs of neuronal networks (Tononi, 1994), the resulting dynamics could be expected to operate at multiple time scales. Multiscale Entropy calculates sample entropy (Richman, 2000) of a signal at different time scales (Costa, 2002) and was used to measure the complexity of the brain signal in the present study.
\nPartial Least Squares (PLS; McIntosh, 2004) is a multivariate statistical technique similar to canonical correlation and was used to extract commonalities between the MSE of the brain activity, the experimental design (musical training vs. visual-art training), and the behavioural measures (Vocabulary and Go\/No-go scores). The statistical significance of each latent variable was determined using permutation tests, and bootstrap ratios were used to determine reliability.
\nResults:
\nBehavioural PLS analysis revealed that brain signal complexity (MSE) increased from pre- to post-training in the music group, and this effect was associated with Vocabulary and Go\/No-go behaviour improvements (p < .05). Similar brain and behaviour changes were not displayed after visual-art training.
\nConclusions:
\nChildren displayed experience-dependent changes in cortical signal complexity after only four weeks of musical training. Consistent with previous behavioural evidence (Moreno, 2009), this neuroplasticity was associated with transfer effects to linguistic and executive control behaviours. Higher brain complexity is indicative of increased functional network diversity, higher processing capacity and enhanced cognition (McIntosh, 2008). The results of the present longitudinal study support the claim that music-training increases information processing capacities in multiple functional neural networks (Carpentier, in prep), and this neuroplasticity supports cognitive and behavioural improvements in non-musical domains.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u7814\u7a76\u3067\u306fGO\/NOGO\u8ab2\u984c\u3092\u7528\u3044\u3066\uff0c\u97f3\u697d\u7642\u6cd5\u306b\u3088\u308b\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3092\u884c\u3044\uff0c\u305d\u306e\u63a8\u79fb\u3092\u691c\u8a0e\u3057\u3066\u3044\u307e\u3059\uff0e\u7d50\u679c\u306f\u97f3\u697d\u7642\u6cd5\u306b\u3088\u308b\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3092\u884c\u3063\u305f\u88ab\u9a13\u8005\u306f\u97f3\u697d\u7642\u6cd5\u3092\u884c\u3063\u3066\u3044\u306a\u3044\u88ab\u9a13\u8005\u3088\u308a\u3082\u8a8d\u77e5\u3084\u884c\u52d5\u529b\u304c\u5411\u4e0a\u3057\u3066\u3044\u308b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u7814\u7a76\u3067\u306fGO\/NOGO\u8ab2\u984c\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3092\u3059\u308b\u3053\u3068\u306b\u3088\u3063\u3066\u6210\u7e3e\u304c\u5411\u4e0a\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u660e\u78ba\u306b\u306a\u3063\u3066\u3044\u308b\u306e\u3067\uff0c\u79c1\u306e\u7814\u7a76\u3067\u3082\u8ab2\u984c\u306e\u6210\u7e3e\u306f\u500b\u4eba\u306eGO\/NOGO\u8ab2\u984c\u306b\u5bfe\u3059\u308b\u6163\u308c\u306e\u8981\u56e0\u304c\u95a2\u4fc2\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u8003\u3048\u3089\u308c\u307e\u3059\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000PpTMS reveals probability-dependent changes in connectivity between rIFC-M1 on go\/nogo task\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aDilene van Campen, Franz-Xaver Neubert, Wery van den Wildenberg, K. Richard Ridderinkhof, Rogier Mars
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a.Decision Making<\/p>\n

Abstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction:<\/h4>\n

The functional role of the right inferior frontal cortex (rIFC) in mediating human behavior is the subject of ongoing debate. Activation of the rIFC has been associated with both response inhibition and with signaling action adaptation demands resulting from unpredicted events (Garavan et al., 1999; Ridderinkhof et al. 2011; Vossel et al. 2011). The goal of this study is to investigate the role of rIFC by combining a go\/no-go paradigm with paired-pulse transcranial magnetic stimulation (ppTMS) over rIFC and the primary motor cortex (M1) to probe the functional connectivity between these brain areas. We hypothesized that if rIFC is involved primarily in response inhibition, then rIFC should exert an inhibitory influence over M1 on no-go (inhibition) trials regardless of no-go probability. If, by contrast, rIFC has a role on unexpected trials other than just response inhibition then rIFC should influence M1 on infrequent trials regardless of response demands.
\nMethods:
\nIn total twelve participants performed a go\/no-go task with 20% or 80% of the trials requiring response inhibition (no-go trials) in a classic and a reversed version of the task, respectively. To probe the influence of rIFC on the motor cortex, the functional connectivity between rIFC and M1 was assessed using paired-pulse transcranial magnetic stimulation (ppTMS). In this procedure, a single “test” TMS pulse is delivered over the hand representation of left M1 to elicit a motor-evoked potential (MEP) in the EMG recorded from the effector muscle. On half of the trials, a “conditioning” TMS pulse over rIFC precedes the test pulse over M1. By calculating the ratio of the MEP amplitude recorded on paired-pulse and single-pulse trials, the influence of rIFC on the motor cortex is assessed (Buch et al., 2010; Neubert et al., 2010). This is reported as the paired pulse effect (PPE). TMS pulses were delivered at one of three time intervals after stimulus onset, namely 75, 125, or 175 ms. Overall, for each SOA there were 32 single-pulse trials (sp) and 32 paired-pulse trials (pp), resulting in a total of 192 TMS pulse trials distributed over go and no-go trials per experiment.
\nResults:
\nBehaviorally, responses were slower to infrequent compared to frequent go trials (431 ms vs. 333 ms), while commission errors were more prevalent to infrequent compared to frequent no-go trials (20.8% vs. 0.3%).
\nOverall, differences in MEP amplitudes between the experiments were found indicating a different pattern of activation. Most important, facilitatory PPEs were observed not only on infrequent no-go trials, but also on infrequent go trials. The time difference between these PPEs (maximal at 125 and 175 ms after stimulus presentation, respectively) likely reflects the corresponding difference in response speed between the two contexts. Additionally, in case of frequent no-go trials, an inhibitory PPE was found that peaked around 125 ms after stimulus presentation
\nConclusions:
\nWe observed that rIFC suppressed M1 excitability during frequent no-go trials, but not during infrequent no-go trials, suggesting that the role of rIFC in response inhibition is context dependent rather than generic. Importantly, rIFC was found to facilitate M1 excitability on all low frequent trials, irrespective of whether the infrequent event involved response inhibition, a finding more in line with a predictive coding framework of cognitive control.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u7814\u7a76\u3067\u306fGO\/NOGO\u8ab2\u984c\u6642\u306eNOGO\u523a\u6fc0\u306e\u983b\u5ea6\u306b\u3088\u308a\u53cd\u5fdc\u6642\u9593\u304c\u3069\u306e\u3088\u3046\u306b\u7570\u306a\u308b\u304b\u306b\u3064\u3044\u3066\u7740\u76ee\u3057\uff0cIFC\u3068\u904b\u52d5\u91ce\u306e\u95a2\u4fc2\u306b\u3064\u3044\u3066\u691c\u8a0e\u3057\u3066\u3044\u307e\u3059\uff0eNOGO\u4fe1\u53f7\u306e\u983b\u5ea6\u304c\u6e1b\u5c11\u3059\u308b\u3068\uff0c\u53cd\u5fdc\u6642\u9593\u306f\u9577\u304f\u306a\u308a\uff0c\u307e\u305f\u8133\u6ce2\u306e\u30d4\u30fc\u30af\u306b\u3082\u5f71\u97ff\u304c\u51fa\u308b\u3068\u3044\u3046\u3053\u3068\u3067\u3057\u305f\uff0e\u307e\u305f\u30c7\u30fc\u30bf\u51e6\u7406\u65b9\u6cd5\u306b\u95a2\u3057\u3066\uff0c\u6a19\u6e96\u5316\u306e\u65b9\u6cd5\u306fZscore\u3092\u7528\u3044\u3066\u3044\u305f\u306e\u3067\uff0c\u6a19\u6e96\u5316\u3067\u4e00\u822c\u7684\u306a\u3082\u306e\u304cZscore\u306a\u306e\u304b\u306a\u3068\u3044\u3046\u5370\u8c61\u3092\u62b1\u304d\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Attentional load affects task-related brain activation but not task decoding\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aJason Chan, Aaron Kucyi, Joseph DeSouza
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aExecutive Function
\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Introduction:
\nNeural resources are limited, and performing multiple tasks concurrently places a load on attention and results in disrupted task performance. While human neuroimaging studies have investigated the neural correlates of attentional load, how attentional load affects task processing is poorly understood. Here, we created an attentional load using a dual task paradigm, and examined task-related neural activity using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) with conventional univariate analysis and multivoxel pattern analysis (MVPA).
\nMethods:
\nBOLD fMRI scans (3.0T, T2*-weighted echo planar imaging, TR = 1970 ms, TE = 2.6 ms, flip angle = 78\u00b0, 64 x 64 matrix, 32 slices, voxel dimensions 3.3 x 3.3 x 3.3 mm) were acquired in 8 healthy adult subjects (4 females; mean age 26.6). Subjects performed blocks of pro-saccades and anti-saccades in alternation with fixation blocks (DeSouza et al., 2003), while a rapid serial visual presentation (RSVP) task was simultaneously presented during the pro-saccade and anti-saccade instruction cues to create an attentional load (Joseph et al., 1997; Chan and DeSouza, 2013). On 3 out of 6 total runs, subjects were instructed to ignore the RSVP task (i.e. pro-saccades and anti-saccades without RSVP). Subjects also performed an event-related pro-\/anti-saccade task with RSVP to define our regions of interest (ROIs): frontal eye fields (FEF), supplementary eye fields (SEF), intraparietal sulcus (IPS), and higher visual cortex (HVC). Neural activity related to pro-saccade and anti-saccade performance, in the absence and presence of an attentional load, was characterized using univariate analysis and MVPA. All preprocessing was performed in FSL (v5.0.1). Univariate general linear model analysis was used to assess mean activation levels within ROIs, for pro-saccades and anti-saccades, without and with RSVP. Mean percent signal change was compared between conditions using paired two-tailed t-tests with Bonferroni correction. MVPA was performed with the Pattern Recognition for Neuroimaging data Toolbox (PRoNTo v1.1) (Schrouff et al., 2013) using a support vector machine binary classifier. Pro-saccades were classified versus anti-saccades, without and with RSVP, for each ROI using a “leave-one-stimulus-pair-out” cross validation approach. To determine whether pro-saccades and anti-saccades were coded using similar activation patterns without RSVP compared to with RSVP, cross-trial type MVPA was also conducted. Decoding significance was tested with two-tailed t-tests versus 50% chance decoding with Bonferroni correction.
\nResults:
\nWhen pro-saccades and anti-saccades were performed without RSVP, activations in the L-IPS and R-IPS were significantly greater for anti-saccades compared to pro-saccades (p < 0.05), and there was a trend for activation to be greater for anti-saccades in the FEF and SEF. Task identity was significantly decoded in the L-FEF, L-IPS, and R-IPS (p < 0.05). When pro-saccades and anti-saccades were performed with RSVP, activations in almost all ROIs were significantly lower compared to saccade performance without RSVP (p < 0.05). In addition, pro-saccades and anti-saccades could not be differentiated based on mean activation in the FEF, SEF, or IPS. However, saccade task identity was significantly decoded in the R-FEF, L-IPS, R-IPS, and L-HVC (p < 0.05). Cross-trial type decoding revealed that task encoding without RSVP was similar to task encoding with RSVP, in the R-FEF, L-IPS, and R-IPS (p < 0.05).
\nConclusions:
\nIn this study, we demonstrated that attentional load affects mean activation, but not activation patterns, in brain areas commonly associated with pro-saccade and anti-saccade performance. These results suggest that attentional load may disrupt the strength of task-related neural activity, rather than the selection and identity of task representations.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u3053\u306e\u7814\u7a76\u3067\u306f2\u91cd\u8ab2\u984c\u6642\u306e\u8133\u6d3b\u52d5\u3092MRI\u3092\u7528\u3044\u3066\u691c\u8a0e\u3057\u3066\u3044\u307e\u3059\uff0e\u7d50\u679c\u306f\u753b\u9762\u306b\u63d0\u793a\u3055\u308c\u308b\u65b9\u5411\u3068\u53cd\u5bfe\u306e\u53cd\u5fdc\u3092\u793a\u3059\u8ab2\u984c\u306b\u304a\u3044\u3066\u306f\uff0c\u753b\u9762\u306e\u65b9\u5411\u306b\u53cd\u5fdc\u3092\u793a\u3059\u8ab2\u984c\u3088\u308a\u3082\u6d3b\u6027\u91cf\u304c\u5927\u304d\u3044\u90e8\u4f4d\u304c\u591a\u3044\u3053\u3068\u304c\u5206\u304b\u308a\u307e\u3057\u305f\uff0e\u3057\u304b\u3057\u753b\u9762\u306e\u65b9\u5411\u306b\u53cd\u5fdc\u3092\u793a\u3059\u8ab2\u984c\u306e\u307b\u3046\u304c\u6d3b\u6027\u91cf\u304c\u5927\u304d\u3044\u90e8\u4f4d\u3082\u5b58\u5728\u3059\u308b\u3088\u3046\u3067\uff0c\u4e00\u6982\u306b\u8ab2\u984c\u306e\u96e3\u6613\u5ea6\u306b\u3088\u308a\u6d3b\u6027\u91cf\u304c\u6c7a\u5b9a\u4ed8\u3051\u3089\u308c\u308b\u306e\u3067\u306f\u306a\u3044\u3068\uff0c\u79c1\u306e\u7814\u7a76\u306b\u304a\u3051\u308b\u90e8\u4f4d\u306e\u9055\u3044\u306b\u3088\u308b\u6d3b\u6027\u91cf\u306e\u9055\u3044\u306e\u691c\u8a0e\u304c\u6b63\u3057\u3044\u3053\u3068\u304c\u88cf\u3064\u3051\u3089\u308c\u305f\u3088\u3046\u306b\u601d\u3044\u307e\u3057\u305f\uff0e\u8a8d\u77e5\u6a5f\u80fd\u306e\u7814\u7a76\u306b\u304a\u3044\u3066\uff0c\u7570\u306a\u308b\u8ab2\u984c\u3067\u7814\u7a76\u3092\u884c\u3063\u3066\u3044\u3066\u3082\uff0c\u65b9\u5411\u6027\u304c\u540c\u3058\u3082\u306e\u304c\u591a\u304f\u3042\u308a\uff0c\u3068\u3066\u3082\u8208\u5473\u6df1\u304b\u3063\u305f\u3067\u3059\uff0e
\n 
\n\u30fb\u767a\u8868\u30bf\u30a4\u30c8\u30eb\uff0c\u8457\u8005\uff0c\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\uff0c\u6284\u9332\u3092\u66f8\u304f
\n\u30fb\u305d\u306e\u30ec\u30d3\u30e5\u30fc\u3092\u66f8\u304f
\n 
\n\u53c2\u8003\u6587\u732e
\n1)\u00a0\u00a0\u00a0\u00a0 Organization for Human Brain Mapping, http:\/\/www.humanbrainmapping.org\/i4a\/pages\/index.cfm?pageID=3565
\n 
\n\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
\u00a0<\/strong>
\n\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n		 
\n\u5c07\u7a4d\u5f69\u82bd<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u97f3\u74b0\u5883\u304c\u6570\u5b57\u8a18\u61b6\u8ab2\u984c\u306e\u6210\u7e3e\u3068\u8133\u8840\u6d41\u5909\u5316\u306b\u53ca\u307c\u3059
\n\u5f71\u97ff\u306e\u7537\u5973\u5dee\u306e\u691c\u8a0e<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nGender difference in performance and brain function during memorizing task under influence of sound<\/td>\n<\/tr>\n
\u8457\u8005<\/strong><\/td>\n\u5c07\u7a4d\u5f69\u82bd, \u5c71\u672c\u8a69\u5b50\uff0c\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/strong><\/td>\nOHBM<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nOHBM2014<\/td>\n<\/tr>\n
\u4f1a\u5834<\/strong><\/td>\nCongress Center in Humburg<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2014\/06\/08-2013\/06\/12<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n 
\n1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30
\n2014\u5e746\u67088\u65e5\u304b\u308912\u65e5\u306b\u304b\u3051\u3066Congress Center in Humburg\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fOHBM2014\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\uff0c\u795e\u7d4c\u79d1\u5b66\u5206\u91ce\u3067\uff0c\u6700\u65b0\u306e\u795e\u7d4c\u79d1\u5b66\u5206\u91ce\u306e\u60c5\u5831\u3092\u5f97\u3089\u308c\u308b\u5834\u3068\u3055\u308c\u3066\u3044\u307e\u3059\uff0e\u8fd1\u5e74\uff0c\u6a5f\u80fd\u7684\u78c1\u6c17\u5171\u9cf4\u753b\u50cf(fMRI)\u3084\u8133\u78c1\u56f3(MEG)\u306a\u3069\u3092\u7528\u3044\uff0c\u8133\u6a5f\u80fd\u3092\u7406\u89e3\u3059\u308b\u8a66\u307f\u3092\u4fc3\u9032\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5c71\u672c\u5148\u751f\uff0c\u6728\u6751\uff0c\u6749\u7530\uff0c\u4e95\u4e0a\uff0c\u5927\u897f\uff0c\u771f\u5cf6\uff0c\u65e9\u5ddd\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
\n 
\n2. \u7814\u7a76\u767a\u8868
\n2.1. \u767a\u8868\u6982\u8981
\n\u79c1\u306f6\u67089\u65e5\u306e\u5348\u5f8c\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u201dOptical Imaging\/NIIRS\u201d\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c2\u6642\u9593\u30dd\u30b9\u30bf\u30fc\u306e\u524d\u306b\u7acb\u3061\uff0c\u6765\u305f\u4eba\u306b\u8aac\u660e\u3059\u308b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e
\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u201d Gender difference in performance and brain function during memorizing task under influence of sound\u201d\u3068\u3044\u3046\u30bf\u30a4\u30c8\u30eb\u3067\u884c\u3044\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
[Introduction]
\nThe sound environments affect the results of intellectual works and the CBF(cerebral blood flow changes) was elucidated by the research using fNIRS(functional near infrared spectroscopy[1]. Furthermore, some psychological researches reported that there is a gender difference in performances under the influence of environment, and also in the sound which a person feels pleasant or unpleasant[2]. Since the previous study was conducted by 8 male subjects, the gender difference in the influence of sound environments was not under review. In this research, we investigated the gender difference in the influence of sound environments on intellectual work and brain functions during memory tasks. The experiment was conducted by 10 subjects, which consisted of 5 males and 5 females.
\n[Methods]
\nIn this experiment, three sound environment was used; silence, pink noise, and white noise. The sounds were presented while the subjects were performing an intellectual work. The intellectual work in this experiment was the task to memorize numerical strings; A subject memorize 8 numbers displayed in a circle in 3 seconds, and input them in the correct order within 7 seconds. A subject repeated this task 30 times. As the results of performance, the number of correct characters answered was counted. The influences of the sound environments on the performance were examined by measuring the CBF using fNIRS. After the experiment, questionnaires were completed by the subjects to investigate psychological factors. VAS (Visual Analogue Scale) was used as the measurement of feelings. The subjects marked the scale from 0 to 10 to illustrate their pleasantness.
\n[Results]
\nThe male subjects showed the better performance in the following order; silence, white noise, and pink noise, while the female subjects showed the better performance in the following order; white noise, silence, and pink noise. From the results of t-test, a significant difference between male subjects and female subjects was observed at the 5% level only under the white noise. A significant difference of the CBF between a rest and a task was found in more than a half of subjects under every sound environment, and it was observed near inferior frontal gyrus of left temporal region. In this area, the CBF was increased under the sound environments that subjects showed the better performance. From the results of questionnaires, the order of sound environments that a subject felt pleasant was just the same as the order of sound environments that he or she performed well. According to a psychological study, female are tend to find a white noise pleasant, while male finds it unpleasant. In this experiment, males found silence pleasant, and females found white noise pleasant. From these results, it was considered that the sound environment which a subject felt pleasant made their ability of concentration increased, so that a subject could show high performance and his\/her CBF was increased. Furthermore, since white noise has the effect of masking, it might mask the operating noises of the fNIRS. The inferior frontal gyrus of left temporal region is known to be related to working memory. Therefore, in this experiment, it is considered that the CBF was increased in this area, because this task requires memorizing and retaining the information.
\n[Conclusions]
\nThis research is aimed to investigate the gender differences in performances and brain functions during memorizing task under the influence of sounds. In the experiment, the subjects performed the task under the three sound environments; silence, pink noise, and white noise. Then the significant difference between genders was observed under the white noise. The sound environments a subject found pleasant were different between genders, and under that sound he\/she achieved the better score. The activated area was inferior frontal gyrus of left temporal region, and CBF were increased greatly under the sound environment in which the subject showed the better performance.
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
\n2.2. \u8cea\u7591\u5fdc\u7b54
\n\u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>1<\/strong>
\nPusan National University \u6240\u5c5e\u306eMalik Muhammad Naeem Mannan\u3055\u3093\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0eVAS\u306f\u4f55\u306e\u76ee\u7684\u3067\u6e2c\u3063\u305f\u306e\u304b\uff0c\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u97f3\u74b0\u5883\u306b\u5bfe\u3057\u3066\u88ab\u9a13\u8005\u304c\u6301\u3064\uff0c\u5feb\u3084\u4e0d\u5feb\u3068\u3044\u3046\u5fc3\u7406\u72b6\u614b\u3092\u8abf\u67fb\u3059\u308b\u305f\u3081\u3060\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
\nPusan National University \u6240\u5c5e\u306eMuhammad Ahmad Kamran\u3055\u3093\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u8840\u6d41\u306e\u30c7\u30fc\u30bf\u306f\u3069\u306e\u3088\u3046\u306b\u51e6\u7406\u3057\u305f\u304b\uff0c\u8840\u6d41\u306f\u4f55\u4eba\u5206\u306e\u30c7\u30fc\u30bf\u306a\u306e\u304b\uff0c\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u8840\u6d41\u30c7\u30fc\u30bf\u306f\uff0c\u5897\u6e1b\u91cf\u3092\u6bd4\u8f03\u3059\u308b\u305f\u3081\u306e\uff0c\u30bf\u30b9\u30af\u958b\u59cb\u70b9\u306b\u304a\u3051\u308b\u30bc\u30ed\u70b9\u88dc\u6b63\u306e\u307f\u3067\u3042\u308b\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u5149\u8def\u9577\u304c\u88ab\u9a13\u8005\u9593\u3067\u7570\u306a\u308b\u305f\u3081\u5e73\u5747\u306f\u3057\u3066\u304a\u3089\u305a\uff0c\u30dd\u30b9\u30bf\u30fc\u306b\u306f\u4ee3\u8868\u8005\u306e\u30c7\u30fc\u30bf\u3092\u8f09\u305b\u3066\u3044\u308b\u3053\u3068\uff0c\u307b\u3068\u3093\u3069\u306e\u88ab\u9a13\u8005\u306e\u7d50\u679c\u304c\u540c\u3058\u50be\u5411\u306b\u3042\u3063\u305f\u3053\u3068\u3092\u8aac\u660e\u3057\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
\n\u65e5\u672c\u533b\u79d1\u5927\u5b66\u6240\u5c5e\u306e\u80a5\u7530\u9053\u5f66\u3055\u3093\u304b\u3089\u306f\uff0c\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\u3068\u30db\u30ef\u30a4\u30c8\u30ce\u30a4\u30ba\u306f\u3069\u306e\u3088\u3046\u306b\u9055\u3046\u306e\u304b\uff0c\u3068\u3044\u3046\u8cea\u554f\u3092\u9802\u304d\u307e\u3057\u305f\uff0e\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\u306f\u97f3\u306e\u30d1\u30ef\u30fc\u30b9\u30da\u30af\u30c8\u30eb\u304c\u5468\u6ce2\u6570\u306b\u53cd\u6bd4\u4f8b\u3059\u308b\u97f3\u3067\u3042\u308b\u306e\u306b\u5bfe\u3057\uff0c\u30db\u30ef\u30a4\u30c8\u30ce\u30a4\u30ba\u306f\u30d1\u30ef\u30fc\u30b9\u30da\u30af\u30c8\u30eb\u304c\u5168\u3066\u306e\u5468\u6ce2\u6570\u306b\u5bfe\u3057\u3066\u7b49\u3057\u3044\u97f3\u3067\u3042\u308b\uff0c\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\u3068\u30db\u30ef\u30a4\u30c8\u30ce\u30a4\u30ba\u306f\u30ab\u30e9\u30fc\u30c9\u30ce\u30a4\u30ba\u3068\u3044\u3046\u3082\u306e\u306e\u4e00\u7a2e\u3067\u3042\u308a\uff0c\u4ed6\u306b\u3082\u30d1\u30fc\u30d7\u30eb\u30ce\u30a4\u30ba\u3084\u30d6\u30e9\u30a6\u30cb\u30a2\u30f3\u30ce\u30a4\u30ba\u306a\u3069\u5468\u6ce2\u6570\u7279\u6027\u304c\u7570\u306a\u308b\u7a2e\u985e\u304c\u3042\u308b\u3053\u3068\u3092\u4f1d\u3048\u307e\u3057\u305f\uff0e\u5b9f\u969b\u306b\u30d1\u30bd\u30b3\u30f3\u3067\u97f3\u3082\u805e\u3044\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\u304c\uff0c\u9055\u3044\u306f\u307b\u3068\u3093\u3069\u5206\u304b\u3089\u306a\u3044\uff0c\u3068\u3044\u3046\u611f\u60f3\u3092\u9802\u304d\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>4<\/strong>
\nRyerson University\u6240\u5c5e\u306eMartin Merener\u3055\u3093\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u88ab\u9a13\u8005\u306f\u5065\u5e38\u8005\u306a\u306e\u304b\uff0c\u5b66\u751f\u306a\u306e\u304b\uff0c\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u4eca\u306f\u540c\u3058\u7814\u7a76\u5ba4\u306e\u5b66\u751f\u3092\u88ab\u9a13\u8005\u3068\u3057\u3066\u3044\u308b\u304c\uff0c\u4eca\u5f8c\u306f\u5e74\u9f62\u5dee\u306e\u5f71\u97ff\u306a\u3069\u3082\u8abf\u67fb\u3057\u3066\u3044\u304f\u5fc5\u8981\u304c\u3042\u308b\u3068\u8003\u3048\u3089\u308c\u308b\uff0c\u3068\u3044\u3046\u5185\u5bb9\u3067\u7b54\u3048\u307e\u3057\u305f\uff0e
\n 
\n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>5<\/strong>
\n\u8133\u306e\u5b66\u6821\u6240\u5c5e\u306e\u52a0\u85e4\u4fca\u5fb3\u3055\u3093\u304b\u3089\u9802\u3044\u305f\u8cea\u554f\u3067\u3059\uff0e\u5de6\u5074\u982d\u90e8\u304c\u6d3b\u6027\u3057\u3066\u3044\u305f\u306e\u306f\u306a\u305c\u306a\u306e\u304b\uff0c\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u6570\u5b57\u8a18\u61b6\u8ab2\u984c\u304c\u6570\u5b57\u3092\u8a18\u61b6\u3059\u308b\u3082\u306e\u3067\u3042\u308b\u3053\u3068\uff0c\u5165\u529b\u3059\u308b\u3068\u3044\u3046\u52d5\u4f5c\u3092\u542b\u3080\u3053\u3068\uff0c\u6570\u5b57\u3092\u5531\u3048\u3066\u8a18\u61b6\u3057\u305f\u305f\u3081\u8a00\u8a9e\u9818\u57df\u3068\u95a2\u4fc2\u3057\u305f\u3053\u3068\u304c\u8003\u3048\u3089\u308c\uff0c\u5de6\u5074\u982d\u90e8\u306e\u4e0b\u524d\u982d\u56de\u4ed8\u8fd1\u304c\u6d3b\u6027\u3057\u305f\u3068\u8003\u5bdf\u3057\u305f\uff0c\u3068\u3044\u3046\u5185\u5bb9\u3067\u7b54\u3048\u307e\u3057\u305f\uff0e
\n 
\n2.3. \u611f\u60f3
\n\u524d\u56de\u306e\u56fd\u969b\u5b66\u4f1a\u3067\u306f\uff0c\u81ea\u5206\u304b\u3089\u8a71\u3057\u304b\u3051\u308b\u3053\u3068\u304c\u3042\u307e\u308a\u3067\u304d\u306a\u304b\u3063\u305f\u3053\u3068\u304c\u53cd\u7701\u70b9\u3067\u3057\u305f\uff0e\u4eca\u56de\u306f\u81ea\u5206\u304b\u3089\u7a4d\u6975\u7684\u306b\u8a71\u3057\u304b\u3051\u308b\u3053\u3068\u3067\uff0c\u7814\u7a76\u5185\u5bb9\u3092\u805e\u3044\u3066\u9802\u304d\uff0c\u8cea\u554f\u3092\u9802\u304d\uff0c\u30c7\u30a3\u30b9\u30ab\u30c3\u30b7\u30e7\u30f3\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u8aac\u660e\u3092\u5206\u304b\u3063\u305f\u3068\u8a00\u3063\u3066\u9802\u304f\u3053\u3068\u304c\u3067\u304d\uff0c\u307e\u305f\uff0c\u53d7\u3051\u305f\u8cea\u554f\u306b\u3082\u304d\u3061\u3093\u3068\u81ea\u5206\u306a\u308a\u306b\u82f1\u8a9e\u3067\u7b54\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u3066\u826f\u304b\u3063\u305f\u3067\u3059\uff0e\u305d\u3057\u3066\uff0c\u7537\u6027\u3068\u3057\u3066\u306f\u5973\u6027\u304c\u30db\u30ef\u30a4\u30c8\u30ce\u30a4\u30ba\u3067\u6210\u7e3e\u304c\u826f\u304f\u306a\u308b\u306e\u306f\u7406\u89e3\u3067\u304d\u306a\u3044\uff0c\u305d\u3093\u306a\u3053\u3068\u304c\u8d77\u3053\u308b\u306e\u304b\uff0c\u3068\u3044\u3046\u611f\u60f3\u3092\u3084\u306f\u308a\u591a\u304f\u9802\u304d\u307e\u3057\u305f\u304c\uff0c\u591a\u304f\u306e\u65b9\u306b\u304a\u3082\u3057\u308d\u3044\u7d50\u679c\u3060\u3068\u8a00\u3063\u3066\u9802\u304f\u3053\u3068\u304c\u3067\u304d\u305f\u306e\u3067\u826f\u304b\u3063\u305f\u3067\u3059\uff0e\u4e00\u65b9\u3067\uff0c\u8003\u5bdf\u306e\u8a70\u3081\u304c\u8db3\u308a\u306a\u3044\u3053\u3068\u3092\u5b9f\u611f\u3057\uff0c\u307e\u305f\uff0c\u97f3\u306e\u5468\u6ce2\u6570\u89e3\u6790\u306a\u3069\uff0c\u3084\u3089\u306a\u3051\u308c\u3070\u3070\u3089\u306a\u3044\u8ab2\u984c\u304c\u305f\u304f\u3055\u3093\u898b\u3064\u304b\u308a\u307e\u3057\u305f\uff0e\u4fee\u58eb\u8ad6\u6587\u307e\u3067\u306b\u7814\u7a76\u3092\u3055\u3089\u306b\u6df1\u3081\u3066\u3044\u304d\u305f\u3044\u306a\u3068\u611f\u3058\u307e\u3057\u305f\uff0e
\n 
\n3. \u8074\u8b1b
\n\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e5\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Gender Differences in Automatic Motor Responses to Infant Cries
\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIrene Messina, Luigi Cattaneo, Nicola De Pisapia, Paola Venuti
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Social Interaction
\nAbstract \uff1aIntroduction:
\nDue to the biological relevance of infant-related stimuli for newborn survival and reproductive success, it has been suggested that infant-related stimuli should capture adult attention and automatically trigger physiological responses to prepare for action (Brosch et al., 2007). Recent functional magnetic resonance imaging (fMRI) studies have revealed increased activity in the premotor cortex in response to infant-related sensory stimulation (Caria et al., 2012; De Pisapia et al., 2013; Venuti et al., 2012). This finding was interpreted as the loading of an appropriate and specific behavioural\/motor program response to the alerting stimuli.
\nHowever, neuroimaging lacks the temporal resolution to determine whether these motor activations are the product of early automatic responses or of late, cognitively mediated responses. Indeed, physiological signatures of automatic bottom-up responses can be observed in very early phases of stimulus processing, between 100 and 250 ms after stimulus onset (Barchiesi and Cattaneo, 2012).
\nIn order to verify the hypothesis that affiliative stimuli automatically evoke motor plans, in the present study, we measured the presence and the time course of covert modulation of motor cortex excitability by recording the motor evoked potentials (MEPs) associated to single-pulse Transcranial Magnetic Stimulation (TMS), in an event-related paradigm. Such paradigm allows to collect data with high temporal resolution and to disentangle bottom-up automatic responses from top-down cognitively mediated ones.
\nMethods:
\nWe applied single-pulse TMS (spTMS) to participants’ motor cortex, time-locked to the audio presentation of infant cries, and we recorded motor evoked potentials (MEPs) from two upper-limb muscles. The time course of motor modulation was assessed from 0 to 250 ms from sound onset, in six steps of 50 ms in 10 females and 10 male non-parent subjects aged 25-38 years. Responses were recorded from a proximal muscle (biceps brachii – BB) and a distal muscle (first interosseus dorsalis – 1DI) of the right upper limb. Stimuli were five different baby cries sounds and ten control sounds obtained increasing baby cries in pitch by 200 and 400 Hz. Moreover, a post-hoc control experiment was realized to better control for the specificity of infant cries. In this case, a different group of 10 non-parent female participants (age range 18-39) were exposed to control stimuli obteined through the scrambling of the original raw and pitch-modified baby cries used in the main experiment.
\nResults:
\nThe ANOVA on the data from the ID1 muscle showed a Sex*Isi*Cry 3-way interaction, F(10, 180)=2.80, p=0.003. To investigate this interaction, the design was split in two Isi*Cry ANOVAs, each with data from one sex only. The analysis of males yielded only a main effect of ISI, F(5, 45)=4.1570, p=0.003. By contrast, the analysis performed on females showed a main effect of ISI, F(5, 45)=6.02, p<0.001 and a 2-way Isi*Cry interaction F(10, 90)=5.23, p<0.001. Using the control experiment data, the ANOVA on the ID1 muscle yielded a significant 3-way interaction between Group (experimental stimuli versus scrambled experimental stimuli) * Isi * Cry (F(10, 180)=2.67, p=0.005). The analysis on the group who listened to scrambled cries by means of a 2-way ISI*CRY ANOVA did not show any significant result.
\nConclusions:
\nThe data of the present study documented the presence of early motor responses that are specific to baby cries in adult non-parents. Such finding is in accord with the literature on mutual inter-subjectivity that typically regulates parent-infant interaction (Beebe, 2000)
\nThe finding was restricted to female participants. Finding automatic responsiveness to baby cries in nullipara women lends further support to the idea of an “alloparental care” predisposition in females, but not in males, similar to several mammalian species which feature cooperation in infant care (Briga et al., 2012).
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e73\u5150\u306e\u6ce3\u304d\u58f0\u306b\u5bfe\u3059\u308b\u4e21\u89aa\u306e\u53cd\u5fdc\u306e\u7537\u5973\u5dee\u306b\u3064\u3044\u3066\u306e\u7814\u7a76\u3067\u3057\u305f\uff0e\u30a2\u30ed\u30d1\u30ec\u30f3\u30bf\u30eb\u30b1\u30a2\u3068\u3044\u3046\u52b9\u679c\u306b\u3088\u308a\uff0c\u5973\u6027\u306f\u6ce3\u304d\u58f0\u306b\u654f\u611f\u306b\u53cd\u5fdc\u3059\u308b\u304c\uff0c\u7537\u6027\u306f\u53cd\u5fdc\u304c\u920d\u3044\u3068\u3044\u3046\u7d50\u679c\u3067\u3057\u305f\uff0e\u3057\u304b\u3057\uff0c\u305d\u306e\u30a2\u30ed\u30d1\u30ec\u30f3\u30bf\u30eb\u30b1\u30a2\u306e\u767a\u751f\u8981\u56e0\u306f\u672a\u89e3\u660e\u3060\u3068\u3044\u3046\u3053\u3068\u3067\uff0c\u7537\u5973\u5dee\u304c\u767a\u751f\u3059\u308b\u539f\u56e0\u3092\u79c1\u306f\u8aac\u5f97\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u305f\u3044\u3068\u611f\u3058\u307e\u3057\u305f\uff0e
\n 
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSex differences in the neuromagnetic response to body motion
\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMarina Pavlova, Alexander Sokolov, Christel Bidet-Ildei
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Social Cognition
\nAbstract \uff1a\u3000Introduction:
\nVisual sensitivity to human body motion may be considered as a hallmark of daily-life social cognition, and a basis for nonverbal communication and social competence. It appears that visual processing of biological motion engages a specialized neural network with a key node in the right temporal cortex (see Pavlova, Cerebral Cortex 2012, for review) where it topographically overlaps and likely communicates with the neural circuitry underpinning visual social cognition. It is unclear, however, whether the social brain sex-specific. There is a paucity of research examining sex differences at a neurobiological level. The motivation of the present work was to uncover sex-specific alterations in the time-course and dynamic topography of the entire cortical network underpinning visual processing of point-light human locomotion.
\nMethods:
\nWe focused on analyses of the whole-head magnetoencephalographic (MEG) response to biological motion during performance of a one-back-repetition task with canonical and spatially scrambled point-light displays. By uncovering changes in root-mean-squire (RMS) of evoked MEG activity, we examined sex-related differences in cortical MEG activation in healthy adult females and males.
\nResults:
\nThe outcome indicates that in the absence of behavioral differences, sex of observers impacts the cortical evoked RMS response to human locomotion: (i) Sex differences in the cortical MEG response to biological motion occur mostly over the right brain hemisphere; (2) At early latencies (200-250 ms from stimulus onset), difference in RMS amplitude between canonical and scrambled biological motion displays was higher in female as compared to male participants over the right parietal cortex, left temporal cortex, and over the right temporal cortex; and (3) At later latencies, difference in RMS amplitude was higher in males as compared to females over the right frontal lobe at a latency of 250-300 ms, and at a latency of 350-400 ms. Over the right occipital cortex, males display a greater RMS amplitude in response to biological motion at a latency of 400-450 ms.
\nConclusions:
\nThe findings deliver the first evidence for gender dependent modes in time-course and topography of the neural circuitry underpinning visual processing of biological motion. Most remarkable outcome of this work is that females exhibit greater activity over the right temporal cortex, a key of the social brain, where the network specialized for biological motion processing topographically overlaps and communicates with the neural circuitry underpinning visual social cognition (revealing social properties of others such as intentions, emotions, and expectations). Gender-related dimorphism in the cortical response may prevent behavioral differences if they are maladaptive. The outcome represents a framework for studying sex differences in the social brain in psychiatric and neurodevelopmental disorders.
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u8996\u899a\u523a\u6fc0\u306b\u5bfe\u3057\u3066\u3059\u3070\u3084\u304f\u53cd\u5fdc\u3059\u308b\u5b9f\u9a13\u306b\u304a\u3044\u3066\uff0c\u5973\u6027\u306f\u7537\u6027\u3088\u308a\u3082\u512a\u308c\u305f\u53cd\u5fdc\u3092\u793a\u3057\uff0c\u307e\u305f\uff0cMEG\u3092\u7528\u3044\u305f\u8a08\u6e2c\u306e\u7d50\u679c\uff0c\u8133\u306e\u53f3\u534a\u7403\u306b\u304a\u3044\u3066\u6709\u610f\u306a\u7537\u5973\u5dee\u304c\u751f\u3058\u305f\uff0c\u3068\u3044\u3046\u7814\u7a76\u3067\u3057\u305f\uff0e\u3053\u306e\u7814\u7a76\u3067\u306f\uff0c\u4eca\u5f8c\u7537\u5973\u5dee\u306e\u539f\u56e0\u3092\u8abf\u67fb\u3057\u3066\u3044\u304f\u3068\u3055\u308c\u3066\u3044\u305f\u305f\u3081\uff0c\u79c1\u3082\u540c\u3058\u3088\u3046\u306b\u8abf\u67fb\u3092\u9032\u3081\u3066\u3044\u304d\u305f\u3044\u3067\u3059\uff0e
\n 
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aThe influence of rhythm structure on auditory-motor interaction during listening to simple singing
\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMonika Jungblut, Monika Pustelniak, Ralph Schnitker,
\nWalter Huber
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Music
\nAbstract \uff1a\u3000Introduction:
\nThe greater bihemispheric organization of singing compared to speech is one obvious reason for the implementation of singing instructions in the treatment of patients suffering from motor speech disorders as well as aphasia. Meanwhile the fact that listening to musical rhythms, speech, perceptual discrimination or vocal imagery recruits motor regions of the brain is well documented.
\nOur objective was to investigate if auditory-motor interactions during action-related listening to simple singing also vary according to rhythm structure as we recently demonstrated for singing production.
\nSubjects listened to vowel changes with differing rhythm complexity in anticipation of repeating the heard stimuli during the latter portion of the experiment. Stimuli consisted of vowel changes with regular groupings (1), regular groupings with rests (2), and irregular groupings (3), in contrast to single isochronously chanted vowel repetitions as control condition.
\nMethods:
\n17 male and 13 female, right-handed non-musicians took part in this study on a 3T Siemens Trio MRI-system. We used a T2*-weighted EPI sequence (TR 2200ms, TE 30ms, FA 90\u00b0); 41 transversal slices with a thickness of 3.4 mm were acquired covering the whole brain.
\nThe experiment was conducted in an event-related design. Stimuli were presented in a pseudo-randomized order and jittered around an interstimulus interval (ISI) of 9 sec. Stimuli were presented over headphone. Imaging data were analyzed using SPM8.
\nResults:
\nResults were derived from random effects group analysis (FWE .05, extend threshold 10 voxel).
\nWhile subtraction (2) minus (1) yielded additional activation in the left precentral gyrus (BA6,9) both subtractions from condition (3) resulted in additional activation of bilateral putamen and caudate.
\nOnly subtraction (3) minus (1) yielded additional activation of bilateral pre-SMA and precentral gyrus (BA6,9) more distinct in the left hemisphere. Middle, superior, and transverse temporal gyrus (BA22,42,41), ventrolateral prefrontal cortex (BA47,45) and insula (BA13) were activated most prominent in the left hemisphere. Inferior and superior parietal gyrus (BA40,7) and anterior cingulate gyrus (BA32,24) were activated most prominent in the right hemisphere.
\nConclusions:
\nOur findings are in line with the studies mentioned above concerned with auditory-motor interaction, although listening to rhythmically structured singing has not been investigated up to now. Rhythm structure seems to be a decisive factor which induces specific activations with increasing demands on cognitive capacities e.g. working memory and sequential processing. The more explicit segmentation is required the more distinct and left lateralized temporal, premotor, and prefrontal activation occurs during action-related listening to chanted vowel changes. If it was possible to support programming and planning of articulatory gestures also by listening to directed vocal exercises this might be relevant for therapy interventions with patients mentioned above.
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u697d\u66f2\u3092\uff0c\u97f3\u58f0\u60c5\u5831\u306a\u3057\u306e\u97f3\u697d\u306e\u307f\u3068\u97f3\u58f0\u3042\u308a\u3067\u805e\u3044\u305f\u5834\u5408\uff0c\u8133\u6d3b\u52d5\u306f\uff0c\u5de6\u534a\u7403\u306e\u307f\u3067\u5dee\u7570\u304c\u898b\u3089\u308c\u308b\u3068\u3044\u3046\u7814\u7a76\u3067\u3057\u305f\uff0e\u97f3\u523a\u6fc0\u306b\u3082\u8272\u3005\u306a\u8981\u7d20\u304c\u3042\u308a\uff0c\u79c1\u306e\u7814\u7a76\u306e\u5834\u5408\u306f\uff0c\u5468\u6ce2\u6570\u3092\u5909\u5316\u3055\u305b\u3066\u5b9f\u9a13\u3057\u3066\u307f\u308b\u3068\u7570\u306a\u308b\u7d50\u679c\u304c\u898b\u3089\u308c\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u8003\u3048\u3089\u308c\u307e\u3057\u305f\uff0e\u4eca\u5f8c\u306f\u5468\u6ce2\u6570\u306e\u5909\u5316\u3082\u691c\u8a0e\u3057\u3066\u3044\u304d\u305f\u3044\u3067\u3059\uff0e
\n 
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Syntactic priming effect during second language sentence production by Japanese learners of English: An fMRI study
\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aLejian Huang, Melissa Farmer, Marwan Baliki,
\nA. Vania Apkarian
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Resting state
\nAbstract \uff1a\u3000Introduction:
\nThe Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Network is conducting collaborative research on urological chronic pelvic pain disorders. For the MRI section, 5 research centers around the US are participating, all using the same imaging protocol. As scanner-related variability may introduce noise, careful investigation of the effects of center on T1, DTI, and Resting(R)-fMRI data analysis are necessary. Furthermore, as gender and age effects are also critical in the statistical analysis and interpretation of results, we investigate possible effects of these parameters.
\nMethods:
\nFor the T1 study, 52, 85, 60, 26, and 40 subjects were scanned at Northwestern Univ. (NW), UCLA, the Univ. of Michigan (Michigan), Stanford Univ. (Stanford), and the Univ. of Alabama (UAB), respectively. All T1s passed through a quality control pipeline. Residual neck voxels were removed for the purpose of better segmentation before peripheral gray matter (GM) volume was calculated using FSL-SIENAX. Differences of GM volume across centers and between genders were computed using a one-way ANOVA. The correlations between GM volume and age were calculated before and after center and age corrections. For the DTI study, 53, 92, and 6 subjects were scanned at NW, UCLA, and Stanford, respectively. All DTI images were corrected using eddy correct in FSL. Following the corrections, a diffusion tensor model was fitted at each voxel using fslfit in FSL, generating a Fractional Anisotropy (FA) map for each subject. Then, all FA images were nonlinearly registered to MNI152_1mm, creating the mean FA image, which was skeletonized. Mean FA value on the skeleton was calculated. Differences of mean FA across centers and genders were computed using a one-way ANOVA. The correlations between mean FA and age were calculated before and after center and age corrections. For the R-fMRI analysis, 52, 85, 60, 26, and 40 subjects were scanned at NW, UCLA, Michigan, Stanford, and UAB, respectively. All data were preprocessed. Degree differences for degree density at 0.1 for center\/age\/gender were computed voxel-wise using a three way ANOVA for the ROIs of GM and default mode network (DMN), individually. All multiple comparisons were corrected using a false positive discovery technique.
\nResults:
\nFor the T1 study (see fig. 1): A) GM volume showed a significant dependence on center; B) There were no differences between males and females for GM volume; C) GM volume showed a high negative correlation with age (left panel). The correlation between GM volume and age increased when the GM volumes were corrected for both center and gender effects (right panel). On average, GM volume decreased by 2 c.c. for every year of aging. For the DTI study (fig. 2): A) The mean FA skeleton (green); B) Mean FA values showed a significant center effect; C) Mean FA values did not show any significant gender effects across all subjects. D) Mean FA values showed a significant negative correlation with age (left scatter plot). This correlation persisted when the FA values were corrected for center effect (right scatter plot). For R-fMRI study (fig. 3): Brain images show the mean voxel-wise degree for resting state scans across all subjects; B) Brain images show the center effect for the degree maps. There was a highly significant center effect. C) Degree maps showed a significant dependency of age (young vs. old). There were no differences in degree distribution for gender (male vs. female). D) Brain images show the mean DMN computed across all subjects. E) Brain images show the center effect on the DMN. There was a significant center effect. There were no significant age or gender effects.
\nConclusions:
\nWe confirm that center effects are significant for all data types. Therefore, it is necessary to correct for center effects prior to further analysis. Additionally, negative correlation between GM volume and mean FA, as well as between GM volume and age, were found. However, there is no effect of gender on any data
\n 
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u5b89\u9759\u72b6\u614b\u306b\u304a\u3044\u3066T1\u3068DTI\u30c7\u30fc\u30bf\u306e\u7537\u5973\u5dee\uff0c\u5e74\u9f62\u5dee\u3092\u8abf\u67fb\u3057\u305f\u7d50\u679c\uff0c\u6709\u610f\u306a\u5dee\u306f\u898b\u3089\u308c\u306a\u304b\u3063\u305f\uff0c\u3068\u3044\u3046\u7814\u7a76\u3067\u3057\u305f\uff0e\u666e\u6bb5\uff0c\u7537\u5973\u9593\u306e\u6210\u7e3e\u3084\u8133\u8840\u6d41\u5909\u5316\u306b\u6709\u610f\u5dee\u304c\u898b\u3089\u308c\u308b\u3053\u3068\u3092\u671f\u5f85\u3057\u306a\u304c\u3089\u7814\u7a76\u3057\u3066\u3044\u307e\u3059\u304c\uff0c\u7814\u7a76\u3092\u3059\u308b\u524d\u63d0\u6761\u4ef6\u3068\u3057\u3066\uff0c\u5b89\u9759\u6642\u306b\u5dee\u304c\u306a\u3044\u3053\u3068\u3092\u793a\u3059\u3053\u3068\u3082\uff0c\u5927\u5207\u3060\u3068\u611f\u3058\u307e\u3057\u305f\uff0e
\n <\/p>\n\n\n\n
\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSex Differences in BOLD Response During Virtual Navigation: Different Routes to the Same Destination
\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aNicole Nowak, Wendy Elkins, Susan Resnick, Scott Moffat
\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Behavior
\nAbstract \uff1a\u3000Introduction:
\nA male advantage is often reported for measures of visuospatial performance, including measures of spatial navigation (for review, see Collucia & Louse, 2004); however, few papers have addressed sex differences in brain activity during performance of these navigation tasks (Gr\u00f6n et al. 2000). Moreover, because men and women often differ in performance, it is difficult to determine whether resulting brain activation differences are due to sex per se, or brain activation differences in good versus poorer performers. We designed a virtual environment that provokes robust navigation-related brain activations but in which men and women perform equally well. We then used functional MRI to compare the brain activation between men and women during performance in a virtual environment who were well-matched in navigation performance.
\nMethods:
\nThirty healthy participants (15 men) aged 18-39 years participated. The virtual maze used in this task was a combination of interconnected hallways and rooms, where there were six common objects placed throughout. During the encoding phase participants were required to actively explore the virtual maze and learn the location of six objects, the interconnections of the hallways, and the general layout of the maze. The fMRI navigation phase required participants to remember and actively navigate to the locations of the six objects encountered during the encoding phase and to move from object to object as quickly and as accurately as possible using the shortest possible route. Behavioral outcomes included the number of correct hits, number of errors, speed, and total percent correct. A block design was employed and consisted of alternating conditions of navigation versus control. There were a total of 10 blocks (5 navigation; 5 control), which alternated every 60 s.
\nImages were acquired on a 1.5 Tesla Phillips Gyroscan NT Intera parallel to the plane containing the anterior and posterior commissures. Functional images were obtained using echo-planar imaging (TR = 3000 ms; TE = 30 ms; FOV= 64\u00d764; voxel size= 3.75mm\u00d73.75mm\u00d75.5 mm). Statistical analysis was performed using SPM8 (Wellcome Department of Cognitive Neurology, London, UK). All images were motion corrected by realigning to the first image of each participant and were spatially normalized to a standard template which is based on the reference brain provided by the Montreal Neurological Institute.
\nResults:
\nA one-sample t-test comparing the navigation and control condition was used to determine brain regions associated with navigation for the whole sample. This analysis revealed robust navigation-related activations in the posterior parahippocampal gyrus, retro-splenial cortex and parietal lobe which replicate previous findings.
\nFor comparisons between men and women during navigation, analysis of covariance was performed with sex as a grouping variable and speed of movement through the maze as a covariate. For all random effects analyses, height threshold was set at p < 0.01 with a spatial extent threshold of 25 voxels to control for type I error. Men and women did not differ in navigation accuracy, but sex differences were nevertheless apparent in the functional neuroanatomical correlates of navigation. Where men and women differed in brain activation, men activated more posterior brain regions and women more anterior regions. Specifically, there was significantly increased activation of the parahippocampal gyrus and posterior cingulate cortex in men, and superior frontal gyrus and head of the caudate nucleus in women.
\nConclusions:
\nOur results demonstrate that even when men and women are well-matched on navigation performance, they appear to use different brain mechanisms to achieve the same behavioral end point. The results are interpreted within the framework of men and women approaching navigation tasks in a different way that elicits different patterns of brain activation.
\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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\n 
\n 
\n\u53c2\u8003\u6587\u732e
\n1)\u00a0\u00a0\u00a0\u00a0 OHBM2014\u3000\u30db\u30fc\u30e0\u30da\u30fc\u30b8
\nhttps:\/\/ww4.aievolution.com\/hbm1401\/index.cfm?do=abs.pubSearchOptions&style=0&abstractParentID=<\/p>\n","protected":false},"excerpt":{"rendered":"

2014\u5e746\u67088\u65e5~12\u65e5\u306b\u304b\u3051\u3066\uff0c\u30c9\u30a4\u30c4\u306e CCH-Congress Center in Hamburg\u306b\u3066\u958b\u50ac\u3055\u308c\u305fOHBM2014\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\uff0c\u5c71\u672c\u5148\u751f\uff0c\u6a2a\u5185\u5148\u751f\uff0c\u6728\u6751\u831c\uff08M2\uff09\uff0c\u6749\u7530\u51fa\u5f25\uff08M2 … <\/p>\n

“OHBM2014” \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-2325","post","type-post","status-publish","format-standard","hentry","category-10"],"_links":{"self":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/2325","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2325"}],"version-history":[{"count":0,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/2325\/revisions"}],"wp:attachment":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2325"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2325"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2325"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}