{"id":3074,"date":"2015-10-22T21:01:50","date_gmt":"2015-10-22T12:01:50","guid":{"rendered":"http:\/\/www.is.doshisha.ac.jp\/news\/?p=3074"},"modified":"2015-10-22T21:01:50","modified_gmt":"2015-10-22T12:01:50","slug":"%e3%80%90%e9%80%9f%e5%a0%b1%e3%80%91neuroscience-2015","status":"publish","type":"post","link":"https:\/\/is.doshisha.ac.jp\/news\/?p=3074","title":{"rendered":"\u3010\u901f\u5831\u3011Neuroscience 2015"},"content":{"rendered":"

Neuroscience 2015<\/a> \u304c\u3001October 17-21\u306e\u65e5\u7a0b\u3067\u3001Chicago \u3000\u30de\u30b3\u30fc\u30df\u30c3\u30af\u30d7\u30ec\u30a4\u30b9\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\u3002
\n\u4e0b\u8a18\u306e\uff14\u4ef6\u306e\u767a\u8868\u3092\u884c\u3044\u307e\u3057\u305f\u3002
\nExamination of the effect of light environment on brain activity during visual search task by fNIRS.
\nH. TANAKA*; T. HIROYASU
\nCross-modal processing in the auditory and visual cortex: FNIRS study with a double-flash
\nillusion.
\nS. SHIGARAKI; K. HACHISUKA; E. OKUNO; T. HIROYASU*.
\nSuggestion of the analysis method to extract the relationship between the brain activity and salivary metabolites during acute psychosocial stress.
\nT. OKAMURA*; T. HIROYASU.
\nStudy of working memory capacity by cerebral blood flow changes : Study using reading span test.
\nK. TAKI*; T. HIROYASU.
\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\u4fe1\u697d\u6167<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u8996\u8074\u899a\u76ae\u8cea\u306b\u304a\u3051\u308b\u611f\u899a\u9593\u76f8\u4e92\u4f5c\u7528\uff1a\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u6642\u306efNIRS\u3092\u7528\u3044\u305f\u7814\u7a76<\/td>\n<\/tr>\n
\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nCross-modal processing in the auditory and visual cortex: a fNIRS study with a double-flash illusion<\/td>\n<\/tr>\n
\u8457\u8005<\/strong><\/td>\n\u4fe1\u697d\u6167\uff0c\u8702\u9808\u8cc0\u5553\u4ecb\uff0c\u5965\u91ce\u82f1\u4e00\uff0c\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
\u4e3b\u50ac<\/strong><\/td>\nSOCIETY for NEUROSCIENCE<\/td>\n<\/tr>\n
\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nNeuroscience2015<\/td>\n<\/tr>\n
\u4f1a\u5834<\/strong><\/td>\nMcCormick Place<\/td>\n<\/tr>\n
\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2015\/10\/14~2015\/10\/21<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 
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  1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n

    2015\/10\/14~2015\/10\/21\u306b\u30a2\u30e1\u30ea\u30abMcCormick Place\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fNeuroscience2015\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e Neuroscience\u3068\u306f\uff0c\u751f\u4f53\u306b\u95a2\u3059\u308b\u7814\u7a76\u5168\u822c\u3092\u5bfe\u8c61\u3068\u3057\u305f\u5b66\u8853\u96c6\u4f1a\u3067\uff0c4000\u3092\u8d85\u3048\u308b\u30dd\u30b9\u30bf\u30fc\u6570\u3092\u8a87\u308b\u30dd\u30b9\u30bf\u30fc\u30bb\u30c3\u30b7\u30e7\u30f3\u7b49\u3068\u3066\u3082\u5927\u898f\u6a21\u306a\u5b66\u8853\u96c6\u4f1a\u3067\u3059\uff0e
    \n\u79c1\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u6edd\u3055\u3093\uff0c\u5ca1\u6751\u3055\u3093\uff0c\u7530\u4e2d\u52c7\u4eba\u304f\u3093\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
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    1. \u7814\u7a76\u767a\u8868\n
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      • \u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

        \u672c\u5b66\u4f1a\u306b\u304a\u3044\u3066\uff0c\u79c1\u306f2015\/10\/20\u306e13\u664200\u5206\u304b\u3089\u30dd\u30b9\u30bf\u30fc\u30bb\u30c3\u30b7\u30e7\u30f3\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\uff0c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306e\u307f\u3067\u3057\u305f\uff0e
        \n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0cCross-modal processing in the auditory and visual cortex: a fNIRS study with a double-flash illusion\u3068\u3044\u3046\u984c\u76ee\u3067\uff0c\u932f\u899a\u306e\u6709\u7121\u306b\u3088\u308a\u88ab\u9a13\u8005\u3092\u5206\u3051\u308b\u3053\u3068\u306b\u3088\u3063\u3066\u932f\u899a\u306e\u6a5f\u80fd\u3092\u6301\u3064\u8133\u90e8\u4f4d\u3092\u691c\u8a0e\u3057\u3066\u767a\u8868\u3057\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u3044\u305f\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
        [Purpose] The senses have the sense of hearing and sight. A brain finally processes information from the senses. In everyday life, people get interacting information. We need to get the details of cross-modal interactions to clarify the mechanism of sensory information processing. We measure the auditory and visual interaction with fNIRS(functional Near Infrared Spectroscopy). [Method] We analyzed information of behavior and brain functions with a double-flash illusion. We used the block design that has three tasks. Each tasks have the different number of flashes. One task had some stimuli that had one flash and two beeps. Another had some stimuli that had one flash and one beep. The other had some stimuli that had two flashes and two beeps. One task had a kind of stimuli. In the task, we applied ten stimuli. We used fNIRS that was manufactured by Hitachi medical and measured cerebral blood flow at the whole brain.\uff08The subjects were thirteen healthy adults. They were 22-24 years old. \uff09[Result] According to t \u2013 test (p<.05), we measured number of times of perception of visual stimuli. In this result, the subjects were divided into three groups. One group was defined as the group in which the subjects strongly got illusory impression. Another was defined as the group in which the subjects got weakly illusory impression. The other was defined as the group in which the subjects didn\u2019t get illusory impression. We tested whether a change of cerebral blood flow in a task was significantly different from in a rest. If a change of cerebral blood flow in a task had been significantly different from in a rest, we decided that the part of brain was active. We hypothesized that a subject got illusory impression to resolve the conflict of auditory and visual information. We tested whether the hypothesis was true or not. The subjects who strongly got illusory impression had some active areas in Superior Temporal Sulcus, which was said to be an integration site, and Intraparietal Sulcus, which was said to be the integration site of somatic and visual sensation. As a result, it was suggested that Intraparietal Sulcus might have a function of the integration site of auditory and visual sensation.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

         <\/p>\n

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        • \u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n

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          \n 
          \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>1<\/strong>
          \n\u540c\u5fd7\u793e\u5927\u5b66\u306e\u5c0f\u6797\u5148\u751f\u304b\u3089\u306e\u3054\u8cea\u554f\u3067\u3059\uff0e\u3053\u3061\u3089\u306e\u3054\u8cea\u554f\u306f\uff0c\u300c\u30d5\u30e9\u30c3\u30b7\u30e5\u306e\u63d0\u793a\u8996\u91ce\u3092\u5909\u3048\u3066\u307f\u308b\u3068\u3069\u3046\u304b\uff1f\u5468\u8fba\u8996\u91ce\u3067\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u3092\u3057\u3066\u307f\u305f\u304b\uff1f\u300d\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u300c\u307e\u3060\u305d\u306e\u3088\u3046\u306a\u5b9f\u9a13\u8a2d\u8a08\u3067\u5b9f\u9a13\u3092\u884c\u3063\u305f\u4e8b\u304c\u3042\u308a\u307e\u305b\u3093\uff0e\u5468\u8fba\u8996\u91ce\u306b\u95a2\u3057\u307e\u3057\u3066\u306f\uff0c\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u304c\u3088\u308a\u751f\u3058\u3084\u3059\u3044\u3068\u601d\u3046\u306e\u3067\uff0c\u4e88\u5099\u5b9f\u9a13\u3068\u3057\u3066\u5c11\u3057\u884c\u3063\u3066\u307f\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e\u300d\u3068\u8fd4\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
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          \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
          \n\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u300cEEG\u3092\u7528\u3044\u305f\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u306e\u5b9f\u9a13\u3067\u306f\uff0c\u03b1\u6ce2\u304c\u4e0a\u5074\u982d\u6e9d\u5f8c\u90e8\u3067\u8a08\u6e2c\u3055\u308c\u308b\u4e8b\u3092\u77e5\u3063\u3066\u3044\u308b\u304b\uff1f\u300d\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u300c\u77e5\u308a\u307e\u305b\u3093\u3067\u3057\u305f\uff0e\u3042\u308a\u304c\u3068\u3046\u3054\u3056\u3044\u307e\u3059\uff0e\u305d\u306e\u8ad6\u6587\u3092\u8aad\u3093\u3067\u307f\u307e\u3059\uff0e\u300d\u3068\u8fd4\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
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          \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
          \n\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u300c\u982d\u9802\u9593\u6e9d\u3092\u6291\u5236\u3059\u308b\u3068\u932f\u899a\u304c\u8d77\u3053\u3089\u306a\u304f\u306a\u308b\u306e\u304b\uff1f\u300d\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u300c\u6a5f\u80fd\u3092\u6291\u5236\u3059\u308b\u5b9f\u9a13\u7b49\u306f\u884c\u3063\u3066\u304a\u308a\u307e\u305b\u3093\uff0e\u305f\u3060\uff0c\u79c1\u306e\u4e88\u60f3\u3067\u306f\u982d\u9802\u9593\u6e9d\u3092\u6291\u5236\u3059\u308b\u3068\u932f\u899a\u306f\u8d77\u3053\u3089\u306a\u304f\u306a\u308b\uff0c\u53c8\u306f\u9055\u3046\u7d50\u679c\u306e\u932f\u899a\u3068\u306a\u308b\u3068\u601d\u3044\u307e\u3059\uff0e\u300d\u3068\u8fd4\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
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          \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>4<\/strong>
          \n\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u300cResult\u306eStrong illusion group\uff0cWeak illusion group\u306e\u7d50\u679c\u304c\u3068\u3066\u3082\u9762\u767d\u3044\uff0e\u4eca\u5f8c\u88ab\u9a13\u8005\u306f\u5897\u3084\u3059\u3064\u3082\u308a\u306a\u306e\u304b\uff1f\u300d\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e \u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u300c\u79c1\u3082\u3053\u306e\u7d50\u679c\u306f\u8208\u5473\u6df1\u3044\u3082\u306e\u3060\u3068\u601d\u3063\u3066\u3044\u307e\u3059\uff0e\u4eca\u5f8c\u306f\u3053\u306e\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u3067\u305d\u308c\u305e\u308c\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u88ab\u9a13\u8005\u3092\u5897\u3084\u3057\u3066\u3044\u304d\u305f\u3044\uff0e\u300d\u3068\u56de\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
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          \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>5<\/strong>
          \n\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u300c\u3069\u3046\u3057\u3066Strong illusion group\uff0cWeak illusion group\u306a\u3069\u306e\u3088\u3046\u306a\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u3092\u3057\u305f\u306e\u304b\uff1f\u300d\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e \u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u79c1\u306e\u56de\u7b54\u306f\uff0c\u300c\u4eca\u56de\u540c\u3058\u932f\u899a\u523a\u6fc0\u3092\u4e0e\u3048\u3066\u3044\u308b\u306b\u3082\u95a2\u308f\u3089\u305a\uff0c\u88ab\u9a13\u8005\u5185\u306b\u304a\u3044\u3066\u3082\u932f\u899a\u304c\u8d77\u3053\u308b\u30bf\u30b9\u30af\uff0c\u8d77\u3053\u3089\u306a\u3044\u30bf\u30b9\u30af\u304c\u3042\u3063\u305f\u305f\u3081\uff0c\u932f\u899a\u304c\u8d77\u3053\u3063\u305f\u30bf\u30b9\u30af\u306e\u6570\u3067\u88ab\u9a13\u8005\u3092\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u3057\u307e\u3057\u305f\uff0e\u300d\u3068\u56de\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
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              \u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\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\u3000Differential effects of auditory and visual alpha power in relation to concomitant haemodynamic response\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a G. Y. Bezgin\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Interactions between Auditory and Non-Auditory ModalitiesAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Sensory-related alpha activity (7-12 Hz) in early auditory and visual cortices has been a subject of debate. Even more obscure and contradictory is available evidence on relation between sensory alpha activity and blood oxygenation metabolism as measured by functional magnetic resonance imaging (fMRI). We addressed both issues with simultaneously acquired electroencephalography (EEG) and fMRI data under an audiovisual reaction time task. Alpha, as well as beta (16-30 Hz) and gamma (32-100 Hz) band powers were assessed in two ways: 1) overall band power in 1s pre- and 2s post-stimulus epochs, and 2) 1s post- minus 1s pre-stimulus power content. These metrics were correlated across trials with fMRI signal change, involving subtle stimulus-related fluctuations of the latter. Furthermore, these data were also correlated with stimulus response reaction time, as well as EEG signal complexity measured by multiscale entropy (MSE), involving both electrode-based and source-localised EEG activity, wherein the sources were informed by fMRI contrasts. We observed similarities and distinctions between auditory and visual modalities across applied metrics: both exhibited high and significant correlations between all three band powers (alpha in particular: correlation coefficient ranged from 0.76 to 0.96, p<0.0001 for all region pairs). The effects of reaction time and response accuracy on band powers were more pronounced in the auditory modality (average increase from r=0.14 for inaccurate trials to r=0.37 for accurate trials, p<0.0001). Visual alpha was systematically suppressed instantaneously after a correct stimulus response (correlation between overall power and post-stimulus modulation: r=-0.4, p<0.001). Significant correlations between subtle blood-oxygen level dependent (BOLD) fluctuations and stimulus-locked alpha-power were observed in both auditory (r=0.32, p<0.0001) and visual (r=0.2, p<0.0001) modalities. MSE was significantly correlated with beta power (visual: r=0.45; auditory: r=0.38). Overall, this study assesses the relation between fMRI and alpha power in the early auditory cortex and its visual counterpart, exploring effects of response accuracy and lateralisation. Importantly, it emphasises the advantage of using a combined EEG-fMRI setup in conjunction with a simple multisensory perception paradigm, assessed trial by trial – and thus offers a novel paradigm for multimodal experiments acquired with simultaneously combined neuroimaging techniques. <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u3053\u306e\u767a\u8868\u306f\uff0c\u611f\u899a\u306e\u03b1\u6d3b\u52d5\u3068fMRI\u306b\u3066\u8a08\u6e2c\u3055\u308c\u308bBOLD\u52b9\u679c\u306b\u3088\u308b\u8840\u6d41\u5909\u5316\u3068\u306e\u95a2\u4fc2\u3092\u8abf\u67fb\u3057\u305f\u3082\u306e\u3067\u3059\uff0e\u3053\u306e\u7814\u7a76\u304b\u3089\u306f\uff0c\u8074\u899a\u3068\u8996\u899a\u306b\u304a\u3051\u308b\u03b1\u6ce2\u304cfMRI\u306e\u5fae\u5999\u306a\u8840\u6d41\u5909\u5316\u306e\u3086\u3089\u304e\u306b\u76f8\u95a2\u306e\u3042\u308b\u3068\u3044\u3046\u4e8b\u304c\u308f\u304b\u308a\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u4eca\u56de\u306e\u5b66\u4f1a\u306b\u304a\u3044\u3066\uff0c\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u6642\u306bEEG\u3092\u7528\u3044\u3066\u8a08\u6e2c\u3057\u305f\u03b1\u6ce2\u304c\uff0cfMRI\u7b49\u3092\u7528\u3044\u3066\u8a08\u6e2c\u3057\u305f\u6d3b\u6027\u90e8\u4f4d\u3068\u4e00\u81f4\u3059\u308b\u3068\u3044\u3046\u4e8b\u3092\u77e5\u308a\u307e\u3057\u305f\uff0e\u3053\u308c\u3089\u306e\u4e8b\u304b\u3089\uff0cEEG\u8a08\u6e2c\u306b\u304a\u3051\u308b\u03b1\u6ce2\u304c\u5927\u304d\u304ffMRI\uff0cfNIRS\u8a08\u6e2c\u306a\u3069\u306b\u3088\u308b\u8840\u6d41\u5909\u5316\u306b\u95a2\u308f\u3063\u3066\u3044\u308b\u4e8b\u304c\u8003\u3048\u3089\u308c\u307e\u3059\uff0e\u3053\u306e\u767a\u8868\u306b\u3088\u308afNIRS\u3068EEG\u306e\u540c\u6642\u8a08\u6e2c\u3092\u3057\u3066\u307f\u308b\u3053\u3068\u3082\u9762\u767d\u3044\u3068\u611f\u3058\u307e\u3057\u305f\uff0e<\/p>\n\n\n\n
              \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Effect of tDCS on rubber hand illusion in relation to schizotypal parsonality\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a N. Yoda\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Perception and ImageryAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a The rubber hand illusion (RHI) is an illusion in the integration of visual and tactile stimuli of the self-body. It is known that the temporo-parietal junction (TPJ) is crucially involved in self-body representation and the occurrence of RHI. In this study, we applied transcranial direct current stimulation (tDCS) to left TPJ to investigate whether it modifies the quality of RHI in relation to the degree of schizotypal personality, which is characterized as a predisposition to schizophrenia. Thirty right-handed healthy subjects (7 female, aged 21.0 \u00b1 1.7) participated in the experiment. Subject’s level of schizotypal personality was examined by means of the Japanese version of the Schizotypal Personality Questionnaire (SPQ). The subjects put their right hand on the table, and the rubber hand was placed 15 cm leftward from their hand. The subjects watched delayed image (100, 300, or 500 ms) of the rubber hand that was filmed using a video camera. Two paintbrushes were used to simultaneously stroke the index finger of the subject\u2019s own hand and that of the rubber hand at approximately 0.5-1 Hz. The stimulation period was 3 min. After each session, subjects completed RHI questionnaire, which in 9 items, identical to that used in the previous study (Botvinick & Cohen, 1998). The subject first underwent a RHI session for each delay condition (pre-stimulation sessions), followed by 10 min tDCS stimulation (1 mA). The subject then underwent the second RHI session for each delay condition while applying tDCS throughout the session (post-stimulation sessions). Subjects were randomly assigned to the anodal, cathodal, or control ”sham” groups. The stimulation was induced with a pair of saline-soaked surface sponge electrodes (35cm2) and delivered by a battery-driven constant current stimulator. For the stimulation of the left TPJ, the anodal or cathodal electrode was placed over a point midway between T3 and P3 (international 10\/20 system). The reference electrode was placed over left prefrontal cortex (a point midway between F3 and FP1). The result on questionnaire data showed that differential (pre – post-stimulation) RHI score (item 2) showed a significant difference between the anodal and cathodal groups in the 500ms delay condition (t(18) = 2.28, p < 0.05). This indicates that the subject in the anodal group felt more RHI after stimulation. In addition, we found positive correlations between the RHI score (item 2) and a SPQ subscale score (”No Close Friends”) in the anodal group in 500ms delay condition (r = 0.75, p < 0.05). These results suggest that tDCS to left TPJ can alter the experience of RHI, which can be further modulated by schizotypal personality.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u3053\u306e\u767a\u8868\u306f\uff0c\u30e9\u30d0\u30fc\u30cf\u30f3\u30c9\u932f\u899a\u6642\u306b\u304a\u3044\u3066\u5074\u982d\u982d\u9802\u63a5\u5408\u90e8\uff08TPJ\uff09\u3092\u6291\u5236\u3059\u308b\u3053\u3068\u3067\uff0c\u30e9\u30d0\u30fc\u30cf\u30f3\u30c9\u932f\u899a\u306e\u77e5\u899a\u304c\u5909\u308f\u308b\u3068\u3044\u3046\u7814\u7a76\u3067\u3059\uff0e\u3053\u306e\u7814\u7a76\u3067\u306f\uff0c\u7d4c\u982d\u84cb\u76f4\u6d41\u523a\u6fc0\uff08tDCS\uff09\u306b\u3088\u3063\u3066\u96fb\u6c17\u523a\u6fc0\u3092TPJ\u306b\u4e0e\u3048\uff0c\u6a5f\u80fd\u3092\u6291\u5236\u3057\u305f\u72b6\u614b\u3067\u30e9\u30d0\u30fc\u30cf\u30f3\u30c9\u932f\u899a\u3092\u884c\u3063\u3066\u3044\u307e\u3059\uff0e\u3053\u306e\u7814\u7a76\u306b\u3088\u308b\u3068\uff0cTPJ\u3092\u6291\u5236\u3057\u305f\u3053\u3068\u306b\u3088\u308a\u30e9\u30d0\u30fc\u30cf\u30f3\u30c9\u932f\u899a\u306f\u8d77\u3053\u3089\u306a\u304f\u306a\u308b\u3068\u3057\u3066\u3044\u307e\u3059\uff0e\u8133\u306e\u3042\u308b\u90e8\u4f4d\u306e\u6a5f\u80fd\u3092\u96fb\u6c17\u523a\u6fc0\u306b\u3088\u3063\u3066\u6291\u5236\u3067\u304d\u308b\u3068\u3044\u3046\u3053\u3068\u304b\u3089\uff0c\u79c1\u304c\u7814\u7a76\u3057\u3066\u3044\u308b\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u306b\u304a\u3044\u3066\u3082\u982d\u9802\u9593\u6e9d\uff0c\u4e0a\u5074\u982d\u6e9d\u3092\u6291\u5236\u3059\u308b\u3053\u3068\u3067\u932f\u899a\u304c\u751f\u3058\u306a\u304f\u306a\u308b\u53ef\u80fd\u6027\u304c\u8003\u3048\u3089\u308c\u307e\u3059\uff0e\u73fe\u5728fNIRS\u3092\u7528\u3044\u3066\u982d\u9802\u9593\u6e9d\u306e\u65b0\u305f\u306a\u8133\u6a5f\u80fd\u306e\u53ef\u80fd\u6027\u3092\u767a\u898b\u3057\u3066\u3044\u308b\u3053\u3068\u304b\u3089\uff0c\u3053\u306etDCS\u3092\u7528\u3044\u305f\u4eee\u8aac\u306e\u88cf\u4ed8\u3051\u306a\u3069\u3082\u884c\u3048\u308b\u306e\u3067\u306f\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
              \n <\/p>\n\n\n\n
              \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Is the sound-induced double-flash illusion generated in primary visual\u3000cortex? Insights into multisensory integration from intracranial EEG recording in humans.\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a E.M. Yeagle\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Interactions between Auditory and Non-Auditory ModalitiesAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a A hallmark of cognition is the ability to assemble information from diverse sources, and to use the outcome to guide complex behavior. Here, we leverage a multisensory illusion paradigm to investigate the neural circuits underlying the assembly of information from visual and auditory modalities. In the sound-induced double flash illusion, judgments about a visual flash are influenced in a time-dependent way by auditory beeps. A single flash presented with two beeps often leads to the perception of a second flash, but only when the beeps are close together. Prior fMRI and extracranial EEG studies have localized correlates of this illusion to occipital cortex, but the illusion has not been studied in humans using intracranial recordings. We examined neural responses in this paradigm in three patients with intractable epilepsy, who had been implanted with intracranial electrodes covering occipital cortex in preparation for surgery to treat their seizures. To induce the illusion, subjects were presented with a single flash (16.67 ms) paired with two beeps. The first beep was simultaneous with the flash, while the second occurred after a variable interval (stimulus-onset asynchrony, SOA) of 50-500 ms. Control conditions presented single or double flashes without sound, a single flash paired with a concurrent beep, and a double flash paired with two concurrent beeps. Subjects identified each trial as presenting a single or double flash. As reported for healthy controls, our patients integrated the two modalities: they were more accurate for conditions with concordant visual and auditory stimuli than for visual-only conditions, they perceived the illusion, and they perceived the illusion more often for short SOA trials than for long SOA trials. For neural analysis, we selected the SOA for each subject that most closely produced 50% accuracy. We then compared neural responses on trials when the subject perceived the illusion (reported 2 flashes) to trials when they did not (reported 1 flash). We focused our analysis on early visual cortex. In contrast with earlier findings, we identified no significant difference between illusion and non-illusion trials in early visual cortex, in either the event-related potential or high-gamma power (65-175 Hz). However, preliminary findings suggest that a neural signature of the illusory flash may be present in extrastriate or later visual areas. These recordings may therefore offer greater resolution of the brain areas involved in multisensory integration, pointing to later stages of visual processing than.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u3053\u306e\u767a\u8868\u306f\uff0cEEG\u3092\u7528\u3044\u3066\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u6642\u304c\u4e00\u6b21\u8996\u899a\u91ce\u306b\u3088\u3063\u3066\u5f15\u304d\u8d77\u3053\u3055\u308c\u308b\u306e\u304b\u3069\u3046\u304b\u3092\u8abf\u3079\u305f\u3082\u306e\u3067\u3059\uff0e\u3053\u306e\u7814\u7a76\u3067\u306f\uff0cEEG\u3067\u4e8b\u8c61\u95a2\u9023\u96fb\u4f4d\uff0c\u03b3\u6ce2\uff0865~175 Hz\uff09\u3092\u8a08\u6e2c\u3057\uff0c\u932f\u899a\u6642\u3068\u975e\u932f\u899a\u6642\u306b\u4f4e\u6b21\u6a5f\u80fd\u306e\u8996\u899a\u91ce\u306b\u3066\u5dee\u7570\u304c\u78ba\u8a8d\u3067\u304d\u308b\u304b\u3092\u8abf\u3079\u3066\u3044\u307e\u3059\uff0e\u7d50\u679c\u3068\u3057\u3066\uff0cV1\u91ce\u306f\u932f\u899a\u3092\u53cd\u6620\u3057\u3066\u304a\u3089\u305a\uff0c\u3080\u3057\u308d\u3088\u308a\u9ad8\u6b21\u306a\u8996\u899a\u6a5f\u80fd\u3092\u6301\u3064\u90e8\u4f4d\uff0c\u305d\u3057\u3066\u8074\u899a\u91ce\u306b\u03b3\u6ce2\u304c\u95a2\u9023\u3092\u793a\u3057\u3066\u3044\u308b\u3068\u3044\u3046\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3057\u305f\uff0e\u3053\u306e\u7814\u7a76\u306b\u3088\u308a\uff0c\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u6642\u304a\u3044\u3066\u8996\u899a\u91ce\u3092\u8a08\u6e2c\u3059\u308b\u306e\u3067\u306f\u306a\u304f\uff0c\u8074\u899a\u91ce\u3084\u9ad8\u6b21\u8133\u6a5f\u80fd\u3092\u6301\u3064\u8996\u899a\u91ce\u3092\u691c\u8a0e\u3059\u308b\u3053\u3068\u304c\uff0c\u932f\u899a\u6a5f\u80fd\u3092\u691c\u8a0e\u3059\u308b\u4e0a\u3067\u3068\u3066\u3082\u91cd\u8981\u3060\u3068\u3044\u3046\u4e8b\u304c\u308f\u304b\u308a\u307e\u3057\u305f\uff0e
              \n <\/p>\n\n\n\n
              \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Audio-visual integration for motion perception\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a T. Omi\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Interactions between Auditory and Non-Auditory ModalitiesAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a The alternation of sound location induces illusory visual motion when vision cannot provide accurate spatial information. A visual stimulus blinking at a fixed location was perceived to be moving laterally when the flash onset was synchronized to an alternating left-right sound source. This illusory visual motion was strengthened with an increasing retinal eccentricity and occurred more frequently when the onsets of the audio and visual stimuli were synchronized. We investigated brain activity for the sound-induced illusory visual motion with a 7T fMRI. Strong activation was observed in hMT when subjects viewed apparent motion stimuli, but not when they viewed the stimulus blinking at a fixed location. However, the activation was also observed for the stimulus blinking at the fixed location when the flash onset was synchronized to an alternating left-right sound source. These results indicate that the hMT is responsible for the audio-visual integration for motion perception.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u3053\u306e\u767a\u8868\u306f\uff0c\u8996\u8074\u899a\u306b\u3088\u308b\u611f\u899a\u9593\u76f8\u4e92\u4f5c\u7528\u3092\u4f34\u3063\u305f\u8a98\u5c0e\u904b\u52d5\u932f\u899a\u6642\u306e\u8133\u6d3b\u52d5\u3092\u8abf\u3079\u305f\u3082\u306e\u3067\u3059\uff0e\u3053\u306e\u7814\u7a76\u306f\uff0cMRI\u3092\u7528\u3044\u3066\u8074\u899a\u523a\u6fc0\u306b\u3088\u3063\u3066\u5909\u308f\u308b\u904b\u52d5\u6027\u306e\u8996\u899a\u932f\u899a\u6642\u306e\u8133\u6d3b\u52d5\u3092\u8a08\u6e2c\u3057\u305f
              \n\u3082\u306e\u3067\u3059\uff0e\u3053\u306e\u7814\u7a76\u306e\u7d50\u679c\u306f\uff0c\u8996\u8074\u899a\u306e\u76f8\u4e92\u4f5c\u7528\u306b\u3088\u308b\u932f\u899a\u306f\uff0cMT\u91ce\u3084\u4e0a\u5074\u982d\u6e9d\u304c\u6709\u610f\u306b\u6d3b\u6027\u3092\u793a\u3057\u3066\u3044\u308b\u3068\u3044\u3046\u7d50\u679c\u3067\u3059\uff0e\u3053\u308c\u306b\u3088\u308a\uff0c\u79c1\u304c\u7814\u7a76\u3057\u3066\u3044\u308b\u8996\u8074\u899a\u7d71\u5408\u3092\u4f34\u3046\u30c0\u30d6\u30eb\u30d5\u30e9\u30c3\u30b7\u30e5\u932f\u899a\u306b\u304a\u3044\u3066\u3082MT\u91ce\u3084\u4e0a\u5074\u982d\u6e9d\u304c\u5927\u304d\u304f\u95a2\u308f\u3063\u3066\u3044\u308b\u3068\u3044\u3046\u53ef\u80fd\u6027\u304c\u793a\u3055\u308c\u307e\u3057\u305f\uff0e
              \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\u5ca1\u6751\u9054\u4e5f<\/td>\n<\/tr>\n
              \u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u6025\u6027\u30b9\u30c8\u30ec\u30b9\u6642\u306b\u304a\u3051\u308b\u8133\u6d3b\u52d5\u3068\u553e\u6db2\u5185\u4ee3\u8b1d\u7269\u8cea\u306e\u95a2\u4fc2\u89e3\u6790\u624b\u6cd5\u306e\u63d0\u6848<\/td>\n<\/tr>\n
              \u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nSuggestion of the analysis method to extract the relationship between the brain activity and salivary metabolites during acute psychosocial stress<\/td>\n<\/tr>\n
              \u8457\u8005<\/strong><\/td>\n\u5ca1\u6751\u9054\u4e5f\uff0c\u6749\u672c\u660c\u5f18\uff0c\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
              \u4e3b\u50ac<\/strong><\/td>\nSociety for Neuroscience<\/td>\n<\/tr>\n
              \u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nNeuroscience2015<\/td>\n<\/tr>\n
              \u4f1a\u5834<\/strong><\/td>\nMcCormick Place<\/td>\n<\/tr>\n
              \u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2015\/10\/17-2015\/10\/21<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

               
              \n <\/p>\n

                \n
              1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n

                2015\/10\/17-2015\/10\/21\u306b\u304b\u3051\u3066\uff0cMcCormick Place\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fNeuroscience2015\u306b\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
                \n\u672c\u5927\u4f1a\u306f\uff0c\u8133\u3068\u795e\u7d4c\u30b7\u30b9\u30c6\u30e0\u306b\u95a2\u3059\u308b\u4e16\u754c\u6700\u5927\u898f\u6a21\u306e\u7d44\u7e54\u3067\u3042\u308bSociety for Neuroscience\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u3066\u3044\u308b\u3082\u306e\u3067\u3059\uff0e\u4eca\u5e74\u5ea6\u306f78\u306e\u56fd\u3005\u304b\u308929033\u4eba\u3082\u306e\u53c2\u52a0\u8005\u304c\u96c6\u307e\u308a\uff0c517\u306e\u5c55\u793a\u4f01\u696d\u308413788\u3082\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u304c839\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u306b\u5206\u304b\u308c\u3066\u884c\u308f\u308c\u308b\u3068\u3044\u3046\u975e\u5e38\u306b\u5927\u304d\u306a\u3082\u306e\u3067\u3057\u305f\uff0e\u79c1\u306f\u5168\u3066\u306e\u65e5\u7a0b\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u6edd\uff0c\u4fe1\u697d\uff0c\u7530\u4e2d\u52c7\u4eba\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
                \n <\/p>\n

                  \n
                1. \u7814\u7a76\u767a\u8868\n
                    \n
                  • \u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

                    \u79c1\u306f21\u65e5\u306e\u5348\u524d\u306e\u30dd\u30b9\u30bf\u30fc\u30bb\u30c3\u30b7\u30e7\u30f3\u300cSomatic Correlates of Stress\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\u30dd\u30b9\u30bf\u30fc\u3092\u898b\u306b\u7acb\u3061\u5bc4\u3063\u3066\u304f\u308c\u305f\u65b9\u3005\u306b\u5bfe\u3057\u3066\uff0c\u79c1\u306e\u7814\u7a76\u306b\u3064\u3044\u3066\u306e\u8aac\u660e\u3084\u8b70\u8ad6\u3092\u884c\u3044\u307e\u3057\u305f\uff0e
                    \n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u6025\u6027\u30b9\u30c8\u30ec\u30b9\u6642\u306b\u304a\u3051\u308b\u8133\u6d3b\u52d5\u3068\u553e\u6db2\u5185\u4ee3\u8b1d\u7269\u8cea\u306e\u95a2\u4fc2\u306b\u3064\u3044\u3066\u3082\u306e\u3067\u3059\uff0e\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u306f\u300cSuggestion of the analysis method to extract the relationship between the brain activity and salivary metabolites during acute psychosocial stress\u300d\u3067\u3059\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
                    \u3010Objective\u3011In recent years, along with the development of the nerve imaging technology and the metabolome analysis technique, the kinds of data which are extracted from the living body increased, and the numbers became enormous. Therefore analysis method to extract the relationship of these data is required. In this study, suggestion of the method to extract the salivary metabolites related to a brain activity state is performed. As an evaluation experiment, brain activity and the salivary metabolites during acute psychosocial stress are measured, and a relationship between brain activity and the salivary metabolites are investigated using the proposed method.\u3010Proposed method\u3011The proposed method is summarized as follows. A target task is set, and the brain activity is measured using fMRI (functional Magnetic Resonance Imaging). Through the experiment, saliva samples are gathered to investigate metabolic information. Using brain activity information of plural subjects, the brain activity state is performed clustering and become the label. The brain activity information of each subject has each label. Saliva samples are analyzed using capillary electrophoresis-MS and density of salivary metabolites is acquired. The density of metabolites is the feature value.The discriminator which can classify the above-mentioned label is learned. SVM (Support Vector Machine) is employed to learning. Leave-one-out cross-validation is performed for all subjects, and a mean identification rate is obtained. The combination of analyzed metabolites which maximizes the mean identification rate is obtained using GA (genetic algorithm). It is found that the combination of metabolites provided in this way is metabolites related to the brain activity state for the target task.
                    \n\u3010Experimental method\u3011
                    \nA psychosocial stress experiment is carried out to verify the validity of the proposed method. Eight healthy young men (22\u00b11 years old) took part in this study. Psychological stress was induced using the Montreal Imaging Stress Task (MIST), where subjects are exposed to challenging mental arithmetic presented on a computer screen. Eight saliva samples were acquired, starting 35 min before the onset of the MIST until 45 min after the MIST.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                     <\/p>\n

                      \n
                    • \u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\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\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\u8133\u6d3b\u52d5\u306b\u3088\u308b\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u7d50\u679c\uff0c\u3069\u306e\u3088\u3046\u306a\u610f\u5473\u3092\u6301\u3064\u30b0\u30eb\u30fc\u30d7\u306b\u5206\u304b\u308c\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\uff0c\u4e00\u65b9\u306e\u30b0\u30eb\u30fc\u30d7\u306f\u30b9\u30c8\u30ec\u30b9\u306b\u95a2\u9023\u3059\u308b\u3068\u3055\u308c\u308b\u8133\u90e8\u4f4d\u306b\u5e83\u304f\u8ce6\u6d3b\u304c\u898b\u3089\u308c\uff0c\u3082\u3046\u4e00\u65b9\u306b\u306f\u898b\u3089\u308c\u306a\u304b\u3063\u305f\u3053\u3068\u304b\u3089\uff0c\u30b9\u30c8\u30ec\u30b9\u306e\u611f\u3058\u65b9\u304c\u7570\u306a\u308b\u30b0\u30eb\u30fc\u30d7\u3067\u5206\u3051\u3089\u308c\u305f\u3068\u8003\u3048\u3089\u308c\u308b\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e
                      \n 
                      \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
                      \n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3057\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u81e8\u5e8a\u5fdc\u7528\u3092\u3069\u306e\u3088\u3046\u306b\u8003\u3048\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\uff0c\u553e\u6db2\u304b\u3089\u30b9\u30c8\u30ec\u30b9\u6642\u306e\u8133\u6d3b\u52d5\u306e\u72b6\u614b\u3092\u63a8\u5b9a\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308c\u3070\uff0c\u7c21\u6613\u306a\u30b9\u30c8\u30ec\u30b9\u8a3a\u65ad\u306e\u6307\u6a19\u306b\u306a\u308b\u306e\u3067\uff0c\u305d\u308c\u3092\u76ee\u6a19\u306b\u8003\u3048\u3066\u3044\u308b\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e
                      \n 
                      \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
                      \n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3057\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u8133\u6d3b\u52d5\u3068\u95a2\u9023\u306e\u3042\u308b\u553e\u6db2\u5185\u4ee3\u8b1d\u7269\u8cea\u3092\u3069\u306e\u3088\u3046\u306b\u9078\u629e\u3057\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\uff0c\u4ee3\u8b1d\u7269\u8cea\u306e\u6fc3\u5ea6\u30921\u30641\u3064\u8abf\u67fb\u3057\uff0c\u8133\u6d3b\u52d5\u306e\u5206\u985e\u3068\u540c\u3058\u3088\u3046\u306b\u5206\u304b\u308c\u308b\u3088\u3046\u306a\u7269\u8cea\u3092\u9078\u629e\u3057\u305f\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e
                      \n\u00a0<\/strong>
                      \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>4<\/strong>
                      \n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3057\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\u88ab\u9a13\u8005\u9593\u3067\u884c\u52d5\u30c7\u30fc\u30bf\u306b\u9055\u3044\u306f\u3042\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\uff0c\u884c\u52d5\u30c7\u30fc\u30bf\u306f\u4e00\u5b9a\u306e\u7bc4\u56f2\u306b\u306a\u308b\u3088\u3046\u306b\u8abf\u6574\u3055\u308c\u3066\u3044\u308b\u306e\u3067\uff0c\u5dee\u306f\u306a\u3044\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e
                      \n <\/p>\n

                        \n
                      • \u611f\u60f3<\/li>\n<\/ul>\n

                        \u4eca\u56de\u306e\u767a\u8868\u3067\u306f\uff0cfMRI\u306e\u7814\u7a76\u3057\u3066\u3044\u308b\u65b9\u3084\u30e1\u30bf\u30dc\u30ed\u30fc\u30e0\u89e3\u6790\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u308b\u65b9\uff0c\u3069\u3061\u3089\u306e\u5206\u91ce\u3067\u3082\u306a\u3044\u65b9\u306a\u3069\uff0c\u69d8\u3005\u306a\u65b9\u3068\u304a\u8a71\u3057\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u307e\u3057\u305f\uff0e\u5206\u91ce\u306e\u9055\u3046\u65b9\u306b\u3082\u79c1\u306e\u7814\u7a76\u5185\u5bb9\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u3044\u305f\u3060\u3051\u305f\u3053\u3068\u306f\u975e\u5e38\u306b\u5b09\u3057\u304f\uff0c\u307e\u305f\u8a2a\u308c\u3066\u3044\u305f\u3060\u3044\u305f\u7686\u69d8\u3068\u8cb4\u91cd\u306a\u610f\u898b\u4ea4\u63db\u304c\u51fa\u6765\u3066\u3068\u3066\u3082\u305f\u3081\u306b\u306a\u308a\u307e\u3057\u305f\u3002
                        \n\u307e\u305f\u5b66\u4f1a\u3092\u901a\u3057\u3066\uff0c\u82f1\u8a9e\u3067\u7814\u7a76\u306b\u3064\u3044\u3066\u8b70\u8ad6\u3059\u308b\u3053\u3068\u306e\u96e3\u3057\u3055\u3092\u6539\u3081\u3066\u611f\u3058\u305f\u4e00\u65b9\u3067\uff0c\u4e16\u754c\u4e2d\u306e\u6700\u65b0\u306e\u7814\u7a76\u3092\u898b\u305f\u308a\uff0c\u305d\u308c\u306b\u3064\u3044\u3066\u8a71\u3057\u5408\u3044\u6700\u65b0\u306e\u52d5\u5411\u3092\u76f4\u63a5\u611f\u3058\u308b\u3068\u3044\u3046\u3053\u3068\u306f\uff0c\u7814\u7a76\u3092\u9032\u3081\u308b\u4e0a\u3067\u975e\u5e38\u306b\u91cd\u8981\u306a\u3053\u3068\u3060\u3068\u611f\u3058\u307e\u3057\u305f\uff0e
                        \n\u4eca\u56de\u306e\u767a\u8868\u3067\u3044\u305f\u3060\u3044\u305f\u30a2\u30c9\u30d0\u30a4\u30b9\u306f\u3082\u3061\u308d\u3093\u306e\u3053\u3068\uff0c\u8074\u8b1b\u3057\u305f\u4ed6\u306e\u65b9\u3005\u306e\u7814\u7a76\u5185\u5bb9\u3082\u81ea\u5206\u306e\u7814\u7a76\u306b\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u3057\uff0c\u3088\u308a\u3088\u3044\u7814\u7a76\u306b\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
                        \n <\/p>\n

                          \n
                        1. \u8074\u8b1b<\/li>\n<\/ol>\n

                          \u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\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\u3000Methylphenidate reduces anxiety effects on a working memory task in healthy subjects\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a M. ERNST, A. DAVIS, C. GRILLON; NIMH\/NIH, NIMH-NIH, Bethesda, MD\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Motivation and emotions: Fear, anxiety, and painAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aAnxiety affects two functional domains, cognitive (excessive worry) and physiological (hyperarousal), which are distinctly influenced by threat. The well-recognized modulatory effects of anxiety on cognitive function (such as working memory) and conversely, cognitive performance on anxiety (such as physiological startle), need to be better understood as they can provide insights into treatment. One way to examine this question is to manipulate separately cognitive function or anxiety level pharmacologically. We present data in 60 healthy adults on the effects of a single dose of 20mg methylphenidate (MPH), 40mg propanolol (PRO) or placebo (PLA) on startle response (ocular EMG) and working memory (n back task,1-, 2-, and 3-back) in a safe and anxiety-induced (threat of electrical shock) context. Compared to PLA, (1) MPH, a dopamine agonist used to treat attention deficit, was expected to improve memory performance and potentially decrease physiological anxiety, and (2) PRO, a beta-adrenergic receptor-blocking used to treat stage anxiety, was expected to reduce physiological anxiety, and potentially improve performance. MPH compared to PLA in the threat condition revealed better performance on the 3-back task, which was accompanied by stronger startle response. In contrast, PRO compared to PLA seemed to reduce startle, but did not affect performance. The amplification of the physiological response to anxiety (anxiety-potentiated startle) by MPH suggests that MPH impacts a component of the startle response that is different from the anxiety-related startle response. Subjective scores on anxiety and task difficulty will be analyzed to probe more specifically this question, as well as the potential role of physiological anxiety on performance.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                          \u3053\u306e\u767a\u8868\u306f\uff0c\u96fb\u6c17\u30b7\u30e7\u30c3\u30af\u306b\u3088\u308a\u88ab\u9a13\u8005\u306b\u4e0d\u5b89\u3092\u4e0e\u3048\u305f\u72b6\u614b\u3067\u8a00\u8a9eN-back\u8ab2\u984c\u3092\u3055\u305b\u307e\u3059\uff0e\u305d\u3057\u3066\uff0c\u5b9f\u9a13\u524d\u306b\u4e0d\u5b89\u3092\u6291\u5236\u3059\u308b\u85ac\u3092\u6295\u4e0e\u3055\u308c\u305f\u88ab\u9a13\u8005\u7fa4\u3068\u30d7\u30e9\u30bb\u30dc\u306e\u7fa4\u3067N-back\u306e\u6210\u7e3e\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\u306b\u3088\u3063\u3066\uff0c\u4e0d\u5b89\u3068Working-Memory\u306e\u95a2\u4fc2\u6027\u306b\u3064\u3044\u3066\u8abf\u67fb\u3057\u305f\u3082\u306e\u3067\u3057\u305f\uff0e
                          \n\u79c1\u306f\u30b9\u30c8\u30ec\u30c3\u30b5\u30fc\u3068\u3057\u3066\u8ab2\u984c\u3092\u63a1\u7528\u3057\u3066\u304a\u308a\uff0c\u30b9\u30c8\u30ec\u30b9\u72b6\u614b\u3092\u524d\u3082\u3063\u3066\u4f5c\u308a\u305d\u306e\u72b6\u614b\u3067\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u691c\u8a0e\u3057\u3066\u3044\u306a\u304b\u3063\u305f\u306e\u3067\uff0c\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\u00a0 \uff1aThe effect of threat on within-network functional connectivity across the entire human brain\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aN. L. BALDERSTON, E. HALE, S. TORRISI, A. HSIUNG, K. O’CONNELL, M. ERNST, C. GRILLON; Natl. Inst. of Mental Hlth., NIH, Bethesda, MD\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Motivation and emotions: Fear, anxiety, and painAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aAnxiety, which is characterized by a sustained increase in arousal in response to unpredictable stressors, is difficult to study with traditional neuroimaging methods because it does not conform to the constraints of a typical event-related design. Several recent fMRI studies have used seed-based functional connectivity to study the neural correlates of anxiety, showing increases in connectivity among regions like the amygdala and mPFC during threat of shock. However, hypothesis-driven seed-based approaches do not provide information about global patterns in the data. Therefore, the purpose of this study was to use a data-driven approach to determine the effect of anxiety on functional connectivity across the entire brain. We induced anxiety in healthy individuals using the threat of shock paradigm. Subjects were exposed to alternating blocks of threat and safety and instructed that shocks would be randomly delivered during the threat blocks. Throughout the experiment, subjects provided continuous ratings of their anxiety using a button box, but no other task was performed. We recorded multi-echo fMRI and used an independent components analysis (MEICA; Kundu et al., 2012) to remove non BOLD-like artifacts from the data. We also masked out white matter and CSF, and removed variability accounted for by nuisance variables. Next we performed a group-level independent components analysis (ICA; Calhoun et al., 2005), and generated spatial maps corresponding to the 25 components identified. To characterize the connectivity within these components, we used 3dTcorrMap in AFNI to correlate the timeseries for each voxel in a given component with the timeseries of every other voxel in the component independently for safe and threat for each subject. We then averaged these values to obtain a single metric that reflected the connectivity within a given component for each subject\/condition. Using a paired sample t-test we found that subjects reported significantly more anxiety during threat than safety. Using a mixed-effects GLM we found a significant increase in within-network connectivity across components during threat than safety. These results suggest that anxiety increases within network-connectivity, which may reflect an enhanced state of vigilance when potential threats are imminent. These results are consistent with recent work from our lab showing that threat improves performance in a sustained attention task, and current work showing that threat decreases alpha power (a possible sign of disinhibition) as recorded by magnetoencephalography.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                          \u3053\u306e\u767a\u8868\u3067\u306f\uff0c\u4e0d\u5b89\u6642\u3068\u5e73\u5e38\u6642\u306b\u304a\u3051\u308b\u5168\u8133\u306e\u6a5f\u80fd\u7684\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u3064\u3044\u3066\u8abf\u67fb\u3057\u305f\u3082\u306e\u3067\u3057\u305f\uff0e\u4e0d\u5b89\u6642\u306e\u65b9\u304c\u9818\u57df\u9593\uff0c\u9818\u57df\u5185\u306e\u30b3\u30cd\u30af\u30c6\u30a3\u30d3\u30c6\u30a3\u304c\u5f37\u304f\u306a\u308b\u3068\u3044\u3046\u7d50\u679c\u3067\u3057\u305f\uff0e
                          \n\u30b9\u30c8\u30ec\u30b9\u30bf\u30b9\u30af\u6642\u306e\u8133\u6d3b\u52d5\u306e\u72b6\u614b\u306e\u9055\u3044\u3092\u691c\u8a0e\u3057\u305f\u3044\u79c1\u306b\u3068\u3063\u3066\uff0c\u975e\u5e38\u306b\u8208\u5473\u6df1\u3044\u767a\u8868\u3067\u3057\u305f\uff0e\u3069\u306e\u3088\u3046\u306bROI\u3092\u53d6\u3063\u305f\u306e\u304b\uff0c\u76f8\u95a2\u3092\u8a08\u7b97\u3057\u305f\u306e\u306f\u4f55\u306b\u5bfe\u3057\u3066\u306a\u306e\u304b\u306a\u3069\uff0c\u3088\u308a\u8a73\u3057\u304f\u8abf\u3079\u3066\u307f\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\u00a0 \uff1a Metabolomics of Resilience to Social Stress\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a B. N. DULKA, A. K. BOURDON, C. T. CLINARD, M. B. MUVVALA, S. R. CAMPAGNA, M. A. COOPER;\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSex and Social Factors in Fear and AnxietyAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aSocial defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of resilience, until recently it has not been feasible to associate levels of multiple neurochemicals in several brain regions to stress-related phenotypes. Metabolomics is a quantitative analysis of small molecules present in biological systems and has been increasingly used for the discovery of biomarkers. The objective of the present study was to identify neurochemicals in select brain regions that distinguish susceptible and resilient individuals in two rodent models of acute social defeat: one with mice and another with Syrian hamsters. We expect that this comparative approach will add strength to the generalizability of these findings. In the first experiment, male mice were subjected to acute social defeat stress using a resident-intruder model and tested for social avoidance 24 hours later in an open field arena to phenotype individuals as resilient or susceptible. One week later, mice were subjected to a second acute social defeat episode, and tissue was immediately collected from the medial prefrontal cortex (mPFC), amygdala (AMY), nucleus accumbens (NAC), and hippocampus (HPC). Liquid chromatography coupled with both tandem and high resolution mass spectrometry (LC-MS) was then used for neurochemical and metabolite detection. In the second experiment, we paired male Syrian hamsters in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 hours after the last pairing animals were exposed to acute social defeat stress. Immediately after social defeat tissue was collected from the mPFC, AMY, NAC, and HPC, and each sample was analyzed using LS-MS. Preliminary analyses indicate several small molecules that significantly differ between defeated and non-defeated animals. For example, defeated hamsters exhibited higher levels of DOPAC in the HPC and AMY and lower levels of NAD+\/NADH in the AMY, HPC, and mPFC compared to home cage controls, suggesting increased metabolism of dopamine and impaired energy metabolism, respectively. Analyses to identify metabolites that distinguish susceptible and resilient animals are ongoing. We believe that taking a metabolomics approach is an essential first step toward developing novel biomarkers for stress-related mental illness.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                          \u3053\u306e\u767a\u8868\u3067\u306f\uff0cSocial defeat \u306b\u66dd\u3055\u308c\u305f\u30de\u30a6\u30b9\u3084\u30cf\u30e0\u30b9\u30bf\u30fc\u306e\u5185\u5074\u524d\u982d\u8449\u524d\u90e8\u76ae\u8cea\uff08mPFC\uff09\u3084\u6241\u6843\u4f53\uff08AMY\uff09\uff0c\u6838\u5074\u5750\u6838\uff08NAC\uff09\u3068\u6d77\u99ac\uff08HPC\uff09\u3092\u53d6\u308a\u51fa\u3057\uff0c\u305d\u306e\u6297\u751f\u7269\u8cea\u3092LC-MS\u3067\u5206\u6790\u3057\u305f\u3082\u306e\u3067\u3059\uff0e
                          \n\u30b9\u30c8\u30ec\u30b9\u72b6\u614b\u306e\u9055\u3044\u3068\u8133\u306e\u72b6\u614b\u306e\u95a2\u4fc2\u6027\u306b\u3064\u3044\u3066\u30e1\u30bf\u30dc\u30ed\u30fc\u30e0\u5206\u6790\u3092\u7528\u3044\u3066\u8abf\u67fb\u3059\u308b\u90e8\u5206\u306f\u79c1\u3068\u540c\u3058\u3067\u3059\u304c\uff0c\u3053\u306e\u767a\u8868\u3067\u306f\u8133\u5b9f\u8cea\u306e\u69cb\u6210\u7269\u8cea\u3092\u30e1\u30bf\u30dc\u30ed\u30fc\u30e0\u5206\u6790\u3059\u308b\u3068\u3053\u308d\u304c\u79c1\u3068\u7570\u306a\u308a\u307e\u3059\uff0e\u30d2\u30c8\u3092\u5bfe\u8c61\u3068\u3059\u308b\u7814\u7a76\u3067\u306f\u3053\u306e\u3088\u3046\u306a\u76f4\u63a5\u7684\u306a\u65b9\u6cd5\u306f\u51fa\u6765\u306a\u3044\u306e\u3067\uff0c\u975e\u5e38\u306b\u523a\u6fc0\u7684\u306a\u767a\u8868\u3067\u3057\u305f\uff0e
                          \n <\/p>\n\n\n\n
                          \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aClassification of age\u2012related brain connectivity using resting state fMRI and the support vector machine\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aT. IIDAKA, E. BAGARINAO, S. KOYAMA, M. KUNIMI, T. NAKAI;\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMemory and Cognition: Influence by AgingAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aAge-related changes in brain function of healthy young and old subjects have been investigated with fMRI and cognitive tasks. Recently, functional connectivity analysis using fMRI in resting rather than task conditions has emerged as an important tool for understanding brain aging and dementia. A classification approach using machine learning such as the support vector machine (SVM) could therefore significantly contribute to this field of research. In the present study, we classified healthy young and old subjects’ resting[[unable to display character: &#8210;]]state (rs[[unable to display character: &#8210;]]) fMRI activity by the SVM. We achieved high classification accuracy with relatively few features. Study participants included 53 young (mean age, 22.6 years, male\/female, 25\/28) and 57 old (mean age, 68.6 years, male\/female, 24\/33) healthy subjects. None of the subjects had cognitive impairment (MMSE > 24) or clinical depression. Whole brain echo planar images were obtained during the resting state with eyes open (3T, Siemens, Trio, TR = 3000 ms, TE = 30 ms, 64 \u00d7 64 matrix, 39 slices, 135 volumes). The images were preprocessed with SPM8. The mean signal time courses in 90 cerebral regions were then extracted with the Data Processing Assistant for Resting-State fMRI (DPARSF) software. A 90 \u00d7 90 correlation matrix of functional connectivity was created for each subject. The connectivity matrices were subjected to an in-house SVM program (linear SVM, C parameter = 1) that implemented principal component analysis and permutation tests to classify the groups. The results showed that the accuracy was 100% when using all subjects and 96.4% when subjects were split into training and test sets (10-fold cross validation). Of 4005 possible connections, high classification accuracy was obtained from only 66 pair-wise connectivities. The connected regions were mainly located in the frontal (29%), subcortical (23%), and temporal (20%) areas. A connectivity value between the anterior cingulate gyrus and olfactory gyrus in the left hemisphere significantly correlated with the age of old subjects (r = [[unable to display character: &#8210;]]0.45, p < 0.05, Bonferroni correction). Thus, we achieved high classification accuracy between the young and old subjects by using rs[[unable to display character: &#8210;]]fMRI and SVM. The age-related difference in connectivity was distributed across the whole brain; however, majority of the connectivities were in the frontal, subcortical, and temporal regions. In the future, the present study could be extended to develop a biomarker of aging and dementia by including subjects with cognitive impairment.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                          \u3053\u306e\u767a\u8868\u306f\uff0c \u82e5\u5e74\u5c64\u3068\u9ad8\u9f62\u5c64\u306e\u88ab\u9a13\u8005\u306eRST\u3092\u8a08\u6e2c\u3057\uff0c\u305d\u308c\u305e\u308c\u306e\u9818\u57df\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u3092\u8a08\u7b97\u3057\uff0c\u305d\u308c\u309266\u6b21\u5143\u307e\u3067\u524a\u6e1b\u3057\u305f\u3082\u306e\u3092\u7279\u5fb4\u91cf\u3068\u3057\u3066\uff0cSVM\u3067\u82e5\u5e74\u5c64\u3068\u9ad8\u9f62\u5c64\u3092\u8b58\u5225\u3057\u305f\u3082\u306e\u3067\u3059\uff0e\u305d\u3057\u3066\u8b58\u5225\u7387\u304c\u3088\u304b\u3063\u305f\u3068\u304d\u306e\u9818\u57df\u306e\u30da\u30a2\u306b\u3064\u3044\u3066\u691c\u8a0e\u3057\u305f\u3082\u306e\u3067\u3057\u305f\uff0e\u8133\u6d3b\u52d5\u304b\u3089\u5f97\u3089\u308c\u305f\u7279\u5fb4\u91cf\u306e\u524a\u6e1b\u65b9\u6cd5\u304c\u8208\u5473\u6df1\u304b\u3063\u305f\u306e\u3067\u3059\u304c\uff0c\u3042\u307e\u308a\u8a73\u3057\u304f\u306f\u5206\u304b\u3089\u306a\u304b\u3063\u305f\u306e\u3067\u95a2\u9023\u3059\u308b\u3082\u306e\u3092\u8abf\u67fb\u3057\u305f\u3044\uff0e
                          \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\u6edd \u8b19\u4e00<\/td>\n<\/tr>\n
                          \u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u8133\u8840\u6d41\u91cf\u5909\u5316\u306b\u3088\u308b\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u5bb9\u91cf\u306e\u691c\u8a0e:\u30ea\u30fc\u30c7\u30a3\u30f3\u30b0\u30b9\u30d1\u30f3\u30c6\u30b9\u30c8\u3092\u7528\u3044\u305f\u691c\u8a0e<\/td>\n<\/tr>\n
                          \u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nExamination of working memory capacity by cerebral blood flow changes : study using reading span test<\/td>\n<\/tr>\n
                          \u8457\u8005<\/strong><\/td>\n\u6edd\u8b19\u4e00, \u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
                          \u4e3b\u50ac<\/strong><\/td>\n\u4e00\u822c\u8ca1\u56e3\u6cd5\u4eba<\/td>\n<\/tr>\n
                          \u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nNeuroscienece 2015<\/td>\n<\/tr>\n
                          \u4f1a\u5834<\/strong><\/td>\n<\/td>\n<\/tr>\n
                          \u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2015\/10\/18-21<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                           
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                            2015\/10\/18-23\u306bMcCormick Place\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fSociety for Neuroscience 2015\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\u795e\u7d4c\u79d1\u5b66\u306e\u7814\u7a76\u8005\u3084\u81e8\u5e8a\u533b\u306a\u3069\u304c\u53c2\u52a0\u3059\u308b\u4e16\u754c\u6700\u5927\u7d1a\u306e\u8133\u3084\u795e\u7d4c\u7cfb\u306b\u95a2\u9023\u3059\u308b\u79d1\u5b66\u7684\u306a\u767a\u898b\u3092\u76ee\u7684\u3068\u3057\u3066\u3044\u307e\u3059\uff0e\u5b9f\u969b\u306b15,000\u4ee5\u4e0a\u306e\u79d1\u5b66\u7684\u306a\u6280\u8853\u3084\u8133\u306e\u69cb\u9020\uff0c\u5065\u5eb7\uff0c\u75c5\u6c17\uff0c\u304a\u3088\u3073\u6cbb\u7642\u6cd5\u306b\u95a2\u3059\u308b\u65b0\u3057\u3044\u7814\u7a76\u306e\u30d7\u30ec\u30bc\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u304c\u306a\u3055\u308c\uff0c\u6570\u591a\u304f\u306e\u9769\u65b0\u7684\u306a\u7814\u7a76\u304c\u62ab\u9732\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u5ca1\u6751\u3055\u3093\uff0c\u4fe1\u697d\u3055\u3093\uff0c\u7530\u4e2d\u52c7\u4eba\u3055\u3093\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e
                            \n <\/p>\n

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                            1. \u7814\u7a76\u767a\u8868\n
                                \n
                              • \u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

                                \u79c1\u306f\u5b66\u4f1a\u958b\u59cb2\u65e5\u76ee\u306e8-12\u6642\u306e\u30dd\u30b9\u30bf\u30fc\u30bb\u30c3\u30b7\u30e7\u30f3\u3067\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e \uff14\u6642\u9593\u30dd\u30b9\u30bf\u30fc\u306e\u524d\u306b\u7acb\u3061\uff0c\u304d\u3066\u4e0b\u3055\u3063\u305f\u65b9\u306b\u81ea\u8eab\u306e\u7814\u7a76\u306e\u8aac\u660e\u3068\u8cea\u7591\u5fdc\u7b54\u3092\u884c\u3044\u307e\u3057\u305f\uff0e\u4eca\u56de\u306e\u767a\u8868\u306f\u300c\u8133\u8840\u6d41\u91cf\u5909\u5316\u306b\u3088\u308b\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u5bb9\u91cf\u306e\u691c\u8a0e:\u30ea\u30fc\u30c7\u30a3\u30f3\u30b0\u30b9\u30d1\u30f3\u30c6\u30b9\u30c8\u3092\u7528\u3044\u305f\u691c\u8a0e\u300d\u3067\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
                                [Title] Examination of working memory capacity by cerebral blood flow changes : study using reading span test[Purpose]The capacity of working memory (WM) is different depending on the person. Up to now, evaluation method of WM capacity of brain function measurement has not been established. Therefore, we examined the relationship between performance of reading span test (RST) and brain regions involved in WM.
                                \n[Method]Cerebral blood flows changes in subjects 20 people during RST were measured. Whole brain (116 measurement channels) was measured as the measurement range by near infrared spectroscopy. In order to analyze, subjects were classified to high performance group and the low performance group by a score of RST. Then hemodynamic model was created by convolution of hemodynamic response function (HRF) and rectangular function that based on the experimental design. In consideration of individual differences, parameters of HRF were determined by the optimization in order to match as much as possible the measurement data and hemodynamic model. Based on dynamic time warping (DTW) distance between the measurement data and the hemodynamic response model created, difference in brain activity between high performance group and the low performance group was examined.
                                \n[Results]In the performances of top six people and the performance of subordinate six people, there was a major difference by t-test (p <.01). Differences in brain activity between these groups were examined. We consider that the measurement channel is not active if DTW distance between the hemodynamic response model created and the measurement data is large. DTW distance between the two groups measurement channel was compared by t-test. When the p-value is low, the difference between the two groups of DTW distance is greater. Through the result of the examination, a significant difference was found in DTW distance between the prefrontal dorsolateral, Wernicke’s area in left hemisphere and motor cortex. Thus, it is found that regions involved in WM performance of the top person are more active than the low performance person. It is suggested that these relationships regions brings a difference in performance.
                                \n[Discussion]The comparison result high performance group DTW distance between the hemodynamic model and the measured data showed more active than regions of low performance group. Comparing peak arrival time of blood flow between these areas, peak of the prefrontal dorsolateral (central executive) is earlier than the peak of Wernicke’s area. This result indicates that activity of Wernicke\u2019s area is weak because of inadequate control of the central executive.
                                \n[Conclusion]The present study showed that the high performance group has a high ability to control by the central executive to RST.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                                  \n
                                • \u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\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>
                                  \nNICT\u306e\u6e90\u3055\u3093\u304b\u3089HRF\u30d1\u30e9\u30e1\u30fc\u30bf\u3068\u8133\u6d3b\u52d5\u306e\u95a2\u4fc2\u306b\u3064\u3044\u3066\u3069\u3046\u8003\u5bdf\u3057\u3066\u3044\u308b\u304b\u8cea\u554f\u3092\u9802\u304d\u307e\u3057\u305f\uff0e\u79c1\u306f\u3053\u308c\u306b\u5bfe\u3057\u3066\uff0c\u307e\u3060\u8003\u5bdf\u3067\u304d\u3066\u304a\u3089\u305a\u4eca\u5f8c\u306e\u8ab2\u984c\u306b\u3057\u305f\u3044\u3068\u8003\u3048\u3066\u3044\u308b\uff0c\u3068\u56de\u7b54\u3044\u305f\u3057\u307e\u3057\u305f\uff0e
                                  \n\u6e90\u3055\u3093\u306f\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u306b\u8a73\u3057\u3044\u304a\u65b9\u3067\u8907\u6570\u306e\u30a2\u30c9\u30d0\u30a4\u30b9\u3082\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e
                                  \n\u3053\u306eRST\u3067\u306eDLPFC\u306e\u6d3b\u52d5\u306f\u3082\u3063\u3068\u8907\u96d1\u306a\u3082\u306e\u306b\u306a\u308b\u305f\u3081\u5358\u7d14\u306b\u4e00\u3064\u306e\u6307\u6a19\u3067\u793a\u3059\u3053\u3068\u306f\u51fa\u6765\u306a\u3044\u305f\u3081\uff0c\u8907\u6570\u306e\u6307\u6a19\u306e\u7d44\u307f\u5408\u308f\u305b\u3067\u8003\u3048\u308b\u5fc5\u8981\u304c\u3042\u308b\u3068\u30a2\u30c9\u30d0\u30a4\u30b9\u3092\u9802\u304d\u307e\u3057\u305f\uff0e
                                  \n 
                                  \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>2<\/strong>
                                  \nHRF\u3084GLM\u306e\u8cea\u554f\u3092\u5e7e\u3064\u304b\u9802\u304d\u307e\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\u79c1\u306f\u795e\u7d4c\u767a\u706b\u6642\u306e\u8840\u6d41\u52d5\u614b\u3092\u6a21\u3057\u305f\u95a2\u6570\u3067\u3042\u308b\u3053\u3068\u3068\uff0cHRF\u3068\u8133\u8840\u6d41\u5909\u5316\u30c7\u30fc\u30bf\u306e\u985e\u4f3c\u5ea6\u3092\u5206\u6790\u3059\u308b\u3053\u3068\u3067\u6d3b\u6027\u306e\u5224\u5b9a\u3092\u3059\u308b\u65b9\u6cd5\u3067\u3042\u308b\u3053\u3068\u3092\u8aac\u660e\u3057\u307e\u3057\u305f\uff0e\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u306b\u95a2\u5fc3\u306e\u3042\u308b\u65b9\u304c\u3053\u306e\u8cea\u554f\u3092\u3057\u3066\u3044\u307e\u3057\u305f\uff0e
                                  \n 
                                  \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>3<\/strong>
                                  \nDeoxy-Hb\u306f\u4eca\u56de\u691c\u8a0e\u3057\u3066\u3044\u306a\u3044\u306e\u304b\u3068\u3044\u3046\u8cea\u554f\u3092\u9802\u304d\u307e\u3057\u305f\uff0e\u3053\u308c\u306b\u5bfe\u3057\u3066\u79c1\u306f\u4eca\u5f8c\u691c\u8a0e\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u7b54\u3048\u307e\u3057\u305f\uff0eNIRS\u306b\u5c11\u3057\u8a73\u3057\u3044\u65b9\u3060\u3063\u305f\u3068\u601d\u3044\u307e\u3059\uff0e
                                  \n <\/p>\n

                                    \n
                                  • \u611f\u60f3<\/li>\n<\/ul>\n

                                    \u4eca\u56de\u306e\u5b66\u4f1a\u53c2\u52a0\u306e\u6e96\u5099\u306f\uff0c\u81ea\u5206\u306e\u8a08\u753b\u6027\u306e\u7121\u3055\u304c\u795f\u308a\u7d50\u679c\u3092\u304e\u308a\u304e\u308a\u307e\u3067\u51fa\u305b\u305a\uff0c\u305d\u306e\u305f\u3081\u591a\u304f\u306e\u65b9\u306e\u304a\u4e16\u8a71\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u305d\u306e\u304a\u852d\u3067\uff0c\u7121\u4e8b\u767a\u8868\u3092\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u305f\u3068\u8003\u3048\u3066\u3044\u307e\u3059\uff0e\u7279\u306b\u65e5\u548c\u5148\u751f\u306b\u306f\u30dd\u30b9\u30bf\u30fc\u306e\u82f1\u8a9e\u306e\u4fee\u6b63\u306b\u304a\u4ed8\u304d\u5408\u3044\u3044\u305f\u3060\u304d\uff0c\u5927\u5909\u611f\u8b1d\u3057\u3066\u304a\u308a\u307e\u3059\uff0e\u305d\u3057\u3066\u4eca\u56de\u306e\u767a\u8868\u5185\u5bb9\u306b\u305f\u3069\u308a\u7740\u3051\u305f\u306e\u306f\u5ee3\u5b89\u5148\u751f\u306e\u3054\u6307\u5c0e\u306e\u304a\u852d\u3067\u3059\uff0e\u975e\u5e38\u306b\u9762\u767d\u3044\u7d50\u679c\u304c\u51fa\u305f\u3068\u611f\u3058\u3066\u304a\u308a\u307e\u3059\uff0e
                                    \n\u5b66\u4f1a\u81ea\u4f53\u3067\u306fNIRS\u306e\u7814\u7a76\u3084HRF\u306b\u3064\u3044\u3066\u306e\u7814\u7a76\u3082\u3044\u304f\u3064\u304b\u767a\u8868\u3055\u308c\u3066\u304a\u308a\uff0c\u4eca\u5f8c\u306e\u8abf\u67fb\u3059\u3079\u304d\u5185\u5bb9\u3092\u78ba\u8a8d\u3067\u304d\u3066\u3068\u3066\u3082\u6709\u610f\u7fa9\u3067\u3057\u305f\uff0e\u79c1\u306e\u767a\u8868\u306b\u3082\u4f55\u4eba\u306e\u65b9\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u3044\u305f\u3060\u3051\u305f\u3088\u3046\u3067\u975e\u5e38\u306b\u52b1\u307f\u306b\u306a\u308a\u307e\u3057\u305f\uff0e
                                    \n\u3053\u306e\u5b66\u4f1a\u306b\u53c2\u52a0\u3057\uff0c\u4fee\u58eb\u8ad6\u6587\u4f5c\u6210\u306e\u305f\u3081\u306b\u5b66\u4f1a\u6e96\u5099\u4e2d\u306b\u5f97\u305f\u8ab2\u984c\uff0c\u5b66\u4f1a\u4e2d\u306b\u5f97\u305f\u8ab2\u984c\u306b\u4eca\u5f8c\u53d6\u308a\u7d44\u307f\uff0c\u826f\u3044\u3082\u306e\u3092\u4ed5\u4e0a\u3052\u305f\u3044\u3068\u3044\u3046\u6c17\u6301\u3061\u304c\u6e67\u3044\u3066\u304d\u307e\u3057\u305f\uff0e\u826f\u3044\u523a\u6fc0\u3092\u5f97\u3089\u308c\u305f\u3068\u601d\u3044\u307e\u3059\uff0e
                                    \n <\/p>\n

                                      \n
                                    1. \u8074\u8b1b<\/li>\n<\/ol>\n

                                      \u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e
                                      \n <\/p>\n\n\n\n
                                      \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a\u3000Neural specializations for interpersonal interaction in a competitive gambling task\u8457\u8005 \uff1a M. R. PIVA, X. ZHANG, A. NOAH, S. CHANG, J. HIRSCH\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a \u00a0Social Cognition: Neural Processes and Disorders.
                                      \nAbstruct \uff1a Dynamic interpersonal interaction is integral to typical human social behavior. Although recent dyadic studies have investigated the paired neural correlates of communicative and cooperative tasks, little is known about the paired neural correlates that underlie competitive tasks requiring social interaction. Conventional neuroimaging techniques such as fMRI have identified key social regions in single brains specifically activated by competing with a human rather than a computer opponent, particularly the temporal-parietal junction (TPJ) [1]. A goal of our study is to extend these findings to interpersonal neural correlates between two brains in an ecologically valid context. We utilized near-infrared spectroscopy (NIRS) to directly measure BOLD signals simultaneously in pairs of subjects playing a simplified poker game. In this game, one player was first randomly dealt either a low or high card. This player was asked to bet or fold. The opposing player was then required to bet or fold in response to the action of the first player. The next trial then began with the opposite player receiving either a low or high card. This simplified poker game was played in two different conditions. In condition one, two subjects played the poker game against each other. In condition two, the same subjects simultaneously played against matched computer opponents. We hypothesized that neural areas potentially involved in social interaction, such as the TPJ, would be differentially sensitive to measures of interbrain coherence during the human vs human and human vs computer conditions. Wavelet analysis [2] was used to quantify coherence between the players for all regions sampled, including the TPJ. Behavioral results suggest that subjects play similarly, roughly obeying Nash equilibrium for a given set of contingencies regardless of the opponent. However, preliminary coherence findings indicate higher synchrony between cross-brain signals originating in the TPJ for the human vs human condition than for the human vs computer condition. These findings extend single brain studies of interpersonal competition to a dual brain paradigm and provide new evidence for a role of TPJ cross-brain coherence in social cognition. 1. Carter et al. (2012) A distinct role for the temporal-parietal junction in predicting socially guided decisions. Science, 337(6090), 109-111. 2. Torrence and Compo (1998) A practical guide to wavelet analysis. Bull of the Am Meteorological Soc, 79(1), 61-78.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                      \u3053\u306e\u767a\u8868\u306e\u5185\u5bb9\u306f\u30dd\u30fc\u30ab\u30fc\u30b2\u30fc\u30e0\u6642\u306e\u8133\u6d3b\u52d5\u3092fNIRS\u3067\u8a08\u6e2c\u3057\u305f\u7d50\u679c\u306b\u3064\u3044\u3066\u3067\u3057\u305f\uff0e\u6a5f\u68b0\u3092\u611b\u8247\u306b\u3057\u305f\u5834\u5408\u3068\uff0c\u4eba\u5bfe\u4eba\u30672\u4eba\u540c\u6642\u306b\u8a08\u6e2c\u3057\u305f\u5834\u5408\u306e\u5b9f\u9a13\u3092\u3057\u3066\u3044\u308b\u3068\u3053\u308d\u304c\u9762\u767d\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e\u307e\u305ffNIRS\u3068\u3057\u3066\u306f\u73cd\u3057\u304f\uff0c\u30a2\u30b8\u30a2\u570f\u5916\u306e\u5927\u5b66\u306e\u7814\u7a76\u3060\u3063\u305f\u3068\u3053\u308d\u3082\u9a5a\u304d\u3067\u3057\u305f\uff0efNIRS\u306e\u666e\u53ca\u306f\u3046\u308c\u3057\u304f\u3082\u3042\u308a\u307e\u3059\u304c\uff0c\u8ffd\u3044\u629c\u304b\u308c\u306a\u3044\u3088\u3046\u306b\u9811\u5f35\u308a\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e
                                      \n\u89e3\u6790\u306bfMRI\u3067\u6709\u540d\u306aPPI\u3092\u4f7f\u3063\u3066\u3044\u307e\u3057\u305f\u3002\u53bb\u5e74\u306e\u5b66\u4f1a\u3067\u3082\u898b\u304b\u3051\u305f\u306e\u3067\uff0c\u4eca\u5ea6\u3057\u3063\u304b\u308a\u52c9\u5f37\u3057\u3066\u304d\u305f\u3044\u3067\u3059\uff0e
                                      \n <\/p>\n\n\n\n
                                      \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1aNovel BOLD model for hemodynamic response with brief stimulation in the human brain\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a J. KIM, D. RESS\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Blood Flow Functional Imaging.
                                      \nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMost attempts to explain the BOLD response have assumed non-linear
                                      \nvenous dilation, thus yielding \u201cballoon\u201d models. However, recent brief stimulation experiments showed prompt arterial dilation without venous volume changes. Accordingly, we assume that arterial dilation creates an underdamped flow (CBF) response to yield a new \u201carterial impulse\u201d model. The CBF and oxygen demand (CMRO2) responses are combined to predict longitudinal oxygen saturation (SO2) in capillary and venous compartments, which are then linked to the BOLD signal. Our model is validated against measurements of the BOLD hemodynamic response function (HRF) evoked by brief stimulation in human visual cortex.
                                      \nMethods: The BOLD signal depends on SO2 changes in capillaries and veins. We assume a uniform cylindrical geometry for the vessels and finely grid their lengths. Model includes flow, oxygen dissociation, and diffusion into extravascular tissue, to obtain continuous SO2 spatial profiles. CBF response is modeled by a linear network, which describes the impulse response produced by prompt arterial dilation. CMRO2 response is modeled by a gamma function. The HRF was measured using a 2-s stimulus of 4-Hz flickering dots followed by a 26-s blank period. High-resolution fMRI data (0.9-mm voxels) was obtained in 7 subjects (spiral acquisition, 1.5-s\/volume). Each session produced ~85 HRF responses that were averaged across visual areas V1-3. The model was fit to the HRFs by adjusting CBF and CMRO2 parameters. Results: The model predicts substantial SO2 variations along the length of capillaries and veins (Fig A). HRF measurements are in good agreement with model fits (Fig B), which are based on estimates of the corresponding CBF and CMRO2 responses (Fig C). The model predicts an offset linear correlation with near unity slope between CBF and CMRO2 peak amplitudes (Fig D). Conclusion: We establish a new arterial impulse model based on the hypothesis that prompt arterial dilation is a key physiological mechanism for the HRF, and demonstrate its efficacy in predicting the BOLD HRF.
                                      \n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                      \u3053\u306e\u767a\u8868\u306f\u5f93\u6765\u306e\u30e2\u30c7\u30eb\u3067\u4f5c\u6210\u3055\u308c\u305fHRF\u3068\u7570\u306a\u308b\u52d5\u8108\u30a4\u30f3\u30d1\u30eb\u30b9\u3092\u30e2\u30c7\u30eb\u306b\u3057\u305fHRF\u306e\u59a5\u5f53\u6027\u306b\u3064\u3044\u3066\u691c\u8a0e\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u3053\u308c\u306f\u52d5\u8108\u306e\u62e1\u5f35\u306e\u4ed5\u65b9\u3092\u5143\u306b\u9178\u7d20\u9700\u8981\u3068\u8840\u6d41\u52d5\u614b\u3092\u7d44\u307f\u5408\u308f\u305b\u3066HRF\u3092\u8003\u6848\u3057\u3066\u3044\u307e\u3057\u305f\uff0e
                                      \nHRF\u3092\u63a8\u5b9a\u3059\u308b\u305f\u3081\u306b\u306f\u3082\u3063\u3068\u751f\u7269\u5b66\u7684\u306a\u77e5\u8b58\u304c\u5fc5\u8981\u3060\u3068\u75db\u611f\u3057\u307e\u3057\u305f\uff0e
                                      \n <\/p>\n\n\n\n
                                      \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aComparison of fMRI analysis methods for accurate detection of heterogeneous hemodynamic responses\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a J. LIU, Z. FANG, D. BERNAL-CASAS, J. LEE\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Combining Optogenetics with Electrophysiology or Functional Magnetic Resonance Imaging.
                                      \nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aFunctional magnetic resonance imaging (fMRI) has been extensively used in brain network studies. One of the key elements in fMRI data analysis is to accurately detect the evoked hemodynamic response function (HRF).
                                      \nHowever, because fMRI analysis tools often rely on specific HRF models, the wide range of possible HRF shapes poses a significant challenge in accurate detection.
                                      \nFor example, it has been demonstrated that HRF varies among brain regions, subjects, and behavioral tasks.
                                      \nNon-canonical HRFs are also commonly seen in patients with brain disorders such as Alzheimer’s disease, epilepsy, and stroke. Furthermore, with optogenetic fMRI, specific control has led us to observe highly distinct HRFs that are closely related to underlying physiology. On the other hand, model-free analysis methods run the risk of elevated false positive rates. Thus, it is important to investigate and understand the advantages and limitations of each fMRI analysis method when heterogeneous HRFs are present. Here, we address this previously undervalued matter in detail and provide a systematic analysis on commonly used fMRI analysis methods across a wide range of HRF shapes. We evaluated both model-based methods, including canonical, Fourier, and gamma sets based on general linear model (GLM) analysis, as well as model-free methods, such as temporal independent component analysis (ICA) and coherence analysis. Both simulated datasets and in vivo acquired optogenetic fMRI datasets were analyzed. Our results suggest that temporal ICA, coherence analysis, and GLM with 4 to 5 Fourier or gamma basis functions yield high sensitivity over a broad range of HRF shapes, although only the GLM with Fourier or gamma basis provides accurate estimates of the original HRFs. In contrast, GLM with canonical basis functions performs inadequately in terms of both sensitivity and model fitting. By directly comparing each analysis method on their ability to detect and model different HRFs, our results offer valuable guidance for brain network studies and enable fMRI data analysis of increasing complexity.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                      \u3053\u306e\u767a\u8868\u306fWhite noise\u306e\u7537\u5973\u5dee\u306e\u691c\u8a0e\u3092MEG\u7528\u3044\u3066\u691c\u8a0e\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u30bf\u30b9\u30af\u306f\u7a7a\u9593\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u30bf\u30b9\u30af\u3067\u4e00\u81f4\u304b\u4e0d\u4e00\u81f4\u306e\u3068\u304d\u306e\u8133\u6d3b\u52d5\u3092\u6e2c\u5b9a\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u3053\u306e\u4eba\u3082\u5973\u6027\u306e\u65b9\u3067\u3001\u5973\u6027\u306e\u65b9\u304c\u6226\u7565\u3068\u304b\u4f7f\u3048\u3066\u3044\u308b\u306e\u3067\u306f\u3068\u8003\u5bdf\u3057\u3066\u3044\u307e\u3057\u305f\uff0eMEG\u3067\u306e\u8133\u8840\u6d41\u5909\u5316\u3067\u306f\u5973\u6027\u306f\u5de6\u4e0b\u524d\u982d\u56de\u3001\u7537\u6027\u306f\u8a00\u8a9e\u91ce\u304c\u6d3b\u6027\u3057\u3066\u3044\u305f\u3089\u3057\u3044\u3002\u3067\u3082\u306a\u305c\u4e00\u81f4\u3068\u4e0d\u4e00\u81f4\u3067\u6bd4\u8f03\u3059\u308b\u5fc5\u8981\u3042\u3063\u305f\u306e\u304b\u306b\u3064\u3044\u3066\u306f\u7406\u89e3\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\u3002
                                      \n <\/p>\n\n\n\n
                                      \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aImagine the future! How does episodic simulation enhance prospective memory?\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a I. MOMENNEJAD, J. D. COHEN, K. A. NORMAN\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Combining Optogenetics with Electrophysiology or Functional Magnetic Resonance Imaging.
                                      \nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Imagining task-related future episodes enhances prospective memory (PM) (Brewer et al. 2011). One hypothesis is that episodic simulation recruits mechanisms that spontaneously bring prospective intentions to mind at the right time (Einstein and McDaniel, 2000). However, the neural mechanisms underlying the role of episodic future simulation in prospective memory have not yet been established. We suggest that (a) spontaneous retrieval processes in PM rely on episodic memory (Cohen and O\u2019Reilly, 1996), and (b) imagining task-related future episodes (episodic \u201cpreplay\u201d) increases the odds that the memory trace laid down during intention-formation will match the participant\u2019s mental state when the PM target appears. This increase in study-test match should (in turn) increase the likelihood that the PM target will trigger spontaneous retrieval of the PM intention. This view predicts that neural evidence for accurate episodic future simulation (i.e., preplay of features that match the PM target) would correlate with prospective memory success. To test this prediction, we used multi-voxel pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data from a non-focal prospective memory paradigm. Participants were instructed to perform a numerical parity or magnitude task at fixation (ongoing task). While faces and scenes appeared peripherally on the left or right side of the screen. Participants were instructed to respond to a specific peripheral face or scene image (non-focal PM target) when it appeared on a specific side of the screen (left or right). In each trial, participants were informed about their future target (the identity of the image, and the side of the screen on which it would appear) and the ongoing task they would be performing when it appeared. After instruction, participants were asked to mentally simulate the future target and rate the quality of their imagery (20 s) before the start of the task. Behaviorally, we found a positive correlation between the ratings of imagery quality and PM hit rate. In order to test whether neural evidence for future simulation correlated with PM success, we trained a classifier on a functional localizer with images of faces and scenes (appearing on the left or right, during an ongoing parity or magnitude task), and we used these parameters to decode what the subjects \u201cimagined\u201d during the simulation period, along the following four dimensions: left\/right, image category, specific image identity, and ongoing task (parity\/magnitude). We will present the results of analyses exploring whether MVPA evidence of preplay during the simulation period predicts PM success.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                      \u3053\u306e\u7814\u7a76\u306foptgenetic\u3068\u547c\u3070\u308c\u308b\u624b\u6cd5\u3067\u691c\u51fa\u3055\u308c\u305fHRF\u306e\u9650\u754c\u3092\u691c\u8a0e\u3057\u3066\u3044\u307e\u3057\u305f\uff0eHRF\u306e\u63a8\u5b9a\u306b\u304a\u3044\u3066\u8208\u5473\u6df1\u3044\u5358\u8a9e\u304c\u591a\u304f\u5927\u5909\u53c2\u8003\u306b\u306a\u308a\u307e\u3057\u305f\uff0eOptgenetic\u306e\u5185\u5bb9\u306f\u308f\u304b\u308a\u307e\u305b\u3093\u3067\u3057\u305f\u304c\uff0c\u8133\u306e\u7d50\u5408\u6027\u306e\u691c\u8a0e\u306b\u3082\u6709\u52b9\u3067\u3042\u308b\u3068\u3044\u3046\u7d50\u8ad6\u3060\u3063\u305f\u305f\u3081\uff0c\u3057\u3063\u304b\u308a\u3068\u8abf\u67fb\u3057\u3066\u3044\u304d\u305f\u3044\u3067\u3059\u3002
                                      \n <\/p>\n\n\n\n
                                      \u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aNear-Infrared Spectroscopy (NIRS) measurement for evaluating mild delirium in hepatic disease\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a A. YOSHIMURA, M. M. TOWE, L. K. MAX, A. LAFLAM, J. JOHNS, D. H. EDWIN, M. LINDQUIST, C. W. HOGUE, A. GURAKAR, K. J. NEUFELD, A. KAMIYA\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Functional Mechanisms of Attention and Disorders of Attention
                                      \nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Delirium, also known by some as \u201cencephalopathy\u201d, is a common and serious clinical syndrome that is associated with significant mortality and increases in healthcare resource utilization. Although early detection of delirium is crucial for improving patient outcomes, it is made difficult due to the lack of quick, easy screening tools. As a result, such syndromes often go undetected in hospital and clinical settings. In this study, we aim to reveal brain function in mildly delirious patients with liver disease by using near-infrared spectroscopy (NIRS), an optical topography system designed to measure the changes in concentration of oxy- and deoxy-hemoglobin in the cerebral cortex. Specifically, we examined these changes in the frontal and temporal areas of the brain during cortical stimulation using tasks for attention and executive function. We found a significant correlation between Hb integral values on NIRS during these tasks and participants\u2019 values on the delirium rating score revised 1998 (DRS-R-98), a commonly used rating scale for measuring delirium. These findings suggest that the NIRS optical topography system might be a useful tool for evaluating and detecting mild delirium.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                      \u3053\u306e\u767a\u8868\u306ffNIRS\u3092\u7528\u3044\u305f\u305b\u3093\u5984\u306e\u8a3a\u65ad\u304a\u3088\u3073\u8a55\u4fa1\u3092\u691c\u8a0e\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u65e2\u306b\u5b58\u5728\u3059\u308b\u305b\u3093\u5984\u306e\u8a55\u4fa1\u65b9\u6cd5\u306b\u3088\u308b\u30b9\u30b3\u30a2\u3068\u8133\u8840\u6d41\u306e\u76f8\u95a2\u3092\u898b\u308b\u3053\u3068\u3067\uff0cfNIRS\u306e\u6709\u7528\u6027\u3092\u7d50\u8ad6\u4ed8\u3051\u3066\u3044\u307e\u3057\u305f\uff0e
                                      \n\u666e\u6bb5\u81ea\u5206\u304c\u8a08\u6e2c\u3059\u308b\u30c7\u30fc\u30bf\u306f\u3068\u3066\u3082\u4e0d\u5b89\u5b9a\u306a\u306e\u3067\u75c5\u6c17\u306e\u8a3a\u65ad\u304c\u3067\u304d\u308b\u3068\u3044\u3046\u7d50\u679c\u306f\u3068\u3066\u3082\u9a5a\u304d\u3067\u3057\u305f\uff0e\u3053\u306e\u65b9\u3068\u306fNIRS\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u6271\u3044\u306b\u3064\u3044\u3066\u304a\u8a71\u51fa\u6765\u3066\u3068\u3066\u3082\u6709\u610f\u7fa9\u3067\u3057\u305f\uff0e
                                      \n 
                                      \n\u53c2\u8003URL<\/p>\n

                                        \n
                                      • Society for Neuroscience 2015, http:\/\/www.sfn.org\/<\/li>\n<\/ul>\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\u7530\u4e2d\u52c7\u4eba<\/td>\n<\/tr>\n
                                        \u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n\u7167\u660e\u74b0\u5883\u304c\u8996\u899a\u63a2\u7d22\u6642\u306e\u8133\u6d3b\u52d5\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u306e\u691c\u8a0e -fNIRS\u3092\u7528\u3044\u305f\u691c\u8a0e-<\/td>\n<\/tr>\n
                                        \u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\nExamination of the effect of light environment on brain activity during visual search task by fNIRS<\/td>\n<\/tr>\n
                                        \u8457\u8005<\/strong><\/td>\n\u7530\u4e2d\u52c7\u4eba\u3001\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n
                                        \u4e3b\u50ac<\/strong><\/td>\nSOCIETY for NEUROSCIENCE<\/td>\n<\/tr>\n
                                        \u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\nNeuroscience2015<\/td>\n<\/tr>\n
                                        \u4f1a\u5834<\/strong><\/td>\nMcCormick Place in Chicago<\/td>\n<\/tr>\n
                                        \u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n2015\/10\/17-2015\/10\/21<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                         
                                        \n <\/p>\n

                                          \n
                                        1. \u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n

                                          2015\/10\/17\u304b\u30892015\/10\/21\u306b\u304b\u3051\u3066\u3001McCormick Place in Chicago\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305fNeuroscience2015\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306b\u306f\u300130,000\u4eba\u4ee5\u4e0a\u300180\u30f6\u56fd\u4ee5\u4e0a\u306e\u795e\u7d4c\u5de5\u5b66\u306b\u95a2\u308f\u308b\u5148\u751f\u65b9\u3084\u5b66\u751f\u304c\u53c2\u52a0\u3057\u3001\u5404\u3005\u306e\u7814\u7a76\u5185\u5bb9\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u5171\u6709\u3067\u304d\u308b\u5834\u3067\u3059\uff0e
                                          \n\u79c1\u306f\u5168\u65e5\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\u3001\u6edd\u3055\u3093\u3001\u5ca1\u6751\u3055\u3093\u3001\u4fe1\u697d\u3055\u3093\u304c\u53c2\u52a0\u3055\u308c\u307e\u3057\u305f\uff0e
                                          \n <\/p>\n

                                            \n
                                          1. \u7814\u7a76\u767a\u8868\n
                                              \n
                                            • \u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n

                                              \u79c1\u306f18\u65e5\u306e8:00-12:00\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e \u5348\u524d\u4e2d\u3001\u30dd\u30b9\u30bf\u30fc\u306e\u524d\u306b\u7acb\u3061\u3001\u767a\u8868\u3092\u805e\u304d\u306b\u6765\u3066\u304f\u3060\u3055\u308b\u65b9\u3005\u306b\u81ea\u5206\u306e\u7814\u7a76\u5185\u5bb9\u30923\u5206\u307b\u3069\u3067\u767a\u8868\u3057\u3001\u8cea\u7591\u5fdc\u7b54\u3059\u308b\u3068\u3044\u3063\u305f\u3082\u306e\u3067\u3057\u305f\uff0e
                                              \n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n\n\n\n
                                              \u3010Purpose\u3011In this study, examination of light environment to improve intelligent productivity and comfort is conducted. It is reported that light environment effects on working efficiency and psychological states of office workers. However, working efficiency and psychological states are processed in the brain and we investigated the effect of light environment on brain activity. Brain activities were measured by functional near-infrared spectroscopy (ETG-7100; Hitachi Medical Corporation). We have constructed the special experimental environment whose light color can be changed. Because of this environment, more channels of fNIRS can be used compared to the former study.
                                              \n 
                                              \n\u3010Methods\u3011
                                              \nUnder each type of light, cerebral blood flow (CBF) changes were measured. Task performance was measured by percentage of correct answers. Subjects were divided into two groups (Blue efficiency group and No efficiency group) by percentage of correct answers. And we examined the difference of brain activity by calculating the average of oxy-Hb.
                                              \n 
                                              \n\u3010Results\u3011
                                              \nIn task performance, t-test was conducted in Blue efficiency group and there was significant difference between White and Blue. In brain activity, the channels whose average value was positive were regarded as active region. In blue efficiency group, the common active region was identified as fusiform area in Blue by POTATo (Optical Topography Analysis Tool). In no efficiency group, left-temporal lobe was widely active in White.
                                              \n 
                                              \n\u3010Discussions and Conclusions\u3011
                                              \nIn task performance of blue efficiency group, percentage of correct answers in Blue was much better in White. By examination of CBF changes in blue efficiency group, fusiform area which has visual perception function was commonly active in Blue. These results indicated that the activation of fusiform area led the improvement of task performance. In no efficiency group, there was no significant difference in task performance, but the activation was widely seen in White. These results suggested that the spread of activation might not affect task performance.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                               <\/p>\n

                                                \n
                                              • \u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n

                                                \u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e
                                                \n 
                                                \n\u30fb\u8cea\u554f\u5185\u5bb9<\/strong>
                                                \n\u4eca\u56de\u306e\u5b66\u4f1a\u3067\u306e\u8cea\u7591\u5fdc\u7b54\u3067\u306f\u3001NIRS\u306e\u30c7\u30fc\u30bf\u51e6\u7406\u3084\u7d50\u679c\u306b\u95a2\u3059\u308b\u8a73\u7d30\u89e3\u8aac\u3092\u3059\u308b\u5834\u9762\u304c\u591a\u304b\u3063\u305f\u3067\u3059\uff0e\u6ecb\u8cc0\u533b\u79d1\u5927\u5b66\u3000\u7cbe\u795e\u533b\u5b66\u52a9\u6559\u306e\u5409\u6751\u7be4\u5148\u751f\u304c\u300c\u30bf\u30b9\u30af\u533a\u9593\u306e\u7a4d\u5206\u5024\u3092\u8a08\u7b97\u3057\u3066\u691c\u8a0e\u3059\u308b\u5834\u5408\u304c\u591a\u3044\u3068\u601d\u3063\u3066\u3044\u305f\u3051\u3069\u3001\u30bf\u30b9\u30af\u533a\u9593\u306e\u6700\u5927\u5024\u307e\u305f\u306f\u6700\u5c0f\u5024\u3092\u30bc\u30ed\u70b9\u88dc\u6b63\u3057\u3066\u8840\u6d41\u306e\u4e0a\u6607\u5177\u5408\u3092\u691c\u8a0e\u3059\u308b\u306e\u306f\u9762\u767d\u3044\u300d\u3068\u30b3\u30e1\u30f3\u30c8\u3057\u3066\u304f\u3060\u3055\u3044\u307e\u3057\u305f\uff0e
                                                \n\u307e\u305f\u3001\u30a2\u30eb\u30d7\u30b9\u96fb\u6c17\u682a\u5f0f\u4f1a\u793e\u3000\u7b2c2\u5546\u54c1\u958b\u767a\u90e8\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u30ea\u30fc\u30c0\u30fc\u306e\u6dfb\u7530\u85ab\u3055\u3093\u304b\u3089\u306f\u3001\u3069\u306e\u3088\u3046\u306aNIRS\u3092\u4f7f\u7528\u3057\u3066\u5b9f\u9a13\u3092\u304a\u3053\u306a\u3063\u3066\u3044\u305f\u306e\u304b\u3068\u3044\u3046\u3053\u3068\u3092\u8a73\u7d30\u306b\u8cea\u554f\u3057\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\u3002
                                                \n 
                                                \n <\/p>\n

                                                  \n
                                                • \u611f\u60f3<\/li>\n<\/ul>\n

                                                  \u521d\u3081\u3066\u306e\u56fd\u969b\u5b66\u4f1a\u3067\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3042\u308a\u3001\u3068\u3066\u3082\u7dca\u5f35\u3057\u307e\u3057\u305f\uff0e\u3057\u304b\u3057\u3001\u8cea\u554f\u3082\u6570\u554f\u3044\u305f\u3060\u3051\u3066\u3001\u975e\u5e38\u306b\u826f\u3044\u7d4c\u9a13\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u82f1\u8a9e\u3067\u8cea\u7591\u5fdc\u7b54\u3059\u308b\u3068\u3044\u3046\u6a5f\u4f1a\u304c\u30db\u30f3\u30c8\u306b\u521d\u3081\u3066\u306e\u3053\u3068\u3067\u3001\u6b63\u76f4\u4f55\u3092\u8a00\u3063\u3066\u3044\u308b\u306e\u304b\u308f\u304b\u3089\u306a\u3044\u3053\u3068\u3082\u3042\u308a\u307e\u3057\u305f\u304c\u3001\u306a\u308b\u3079\u304f\u81ea\u5206\u306e\u7814\u7a76\u5185\u5bb9\u3092\u4f1d\u3048\u3088\u3046\u3068\u52aa\u529b\u3057\u305f\u3053\u3068\u306f\u975e\u5e38\u306b\u826f\u3044\u7d4c\u9a13\u306b\u306a\u3063\u305f\u3068\u601d\u3044\u307e\u3059\uff0e\u3053\u306e\u7d4c\u9a13\u3092\u4eca\u5f8c\u306e\u7814\u7a76\u751f\u6d3b\u3084\u5c31\u8077\u6d3b\u52d5\u306b\u6d3b\u304b\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e
                                                  \n <\/p>\n

                                                    \n
                                                  1. \u8074\u8b1b<\/li>\n<\/ol>\n

                                                    \u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e\uff15\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<\/p>\n\n\n\n
                                                    \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a Near-Infrared Spectroscopy (fNIRS) measurement for evaluating mild delirium in hepatic disease\u8457\u8005 \uff1a A. YOSHIMURA, M. M. TOWE, L. K. MAX, A. LAFLAM, J. JOHNS, D. H. EDWIN, M. LINDQUIST, C. W. HOGUE, A. GURAKAR, K. J. NEUFELD, A. KAMIYA
                                                    \n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a Functional Mechanisms of Attention and Disorders of Attention
                                                    \n 
                                                    \nAbstract
                                                    \nDelirium, also known by some as \u201cencephalopathy\u201d, is a common and serious clinical syndrome that is associated with significant mortality and increases in healthcare resource utilization. Although early detection of delirium is crucial for improving patient outcomes, it is made difficult due to the lack of quick, easy screening tools. As a result, such syndromes often go undetected in hospital and clinical settings. In this study, we aim to reveal brain function in mildly delirious patients with liver disease by using near-infrared spectroscopy (NIRS), an optical topography system designed to measure the changes in concentration of oxy- and deoxy-hemoglobin in the cerebral cortex. Specifically, we examined these changes in the frontal and temporal areas of the brain during cortical stimulation using tasks for attention and executive function. We found a significant correlation between Hb integral values on NIRS during these tasks and participants\u2019 values on the delirium rating score revised 1998 (DRS-R-98), a commonly used rating scale for measuring delirium. These findings suggest that the NIRS optical topography system might be a useful tool for evaluating and detecting mild delirium.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                                    \u3053\u306e\u7814\u7a76\u306e\u767a\u8868\u8005\u306f\u3001\u79c1\u306e\u7814\u7a76\u5185\u5bb9\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u8cea\u554f\u3057\u3066\u304f\u3060\u3055\u3063\u305f\u3001\u6ecb\u8cc0\u533b\u79d1\u5927\u5b66\u306e\u5409\u6751\u5148\u751f\u3067\u3057\u305f\u3002\u79c1\u3068\u540c\u3058\u304fNIRS\u3092\u4f7f\u7528\u3057\u305f\u7814\u7a76\u3067\u3042\u308a\u3001\u89e3\u6790\u65b9\u6cd5\u3084\u7d50\u679c\u306b\u95a2\u3057\u3066\u30c7\u30a3\u30b9\u30ab\u30c3\u30b7\u30e7\u30f3\u3067\u304d\u308b\u5185\u5bb9\u3067\u3057\u305f\u3002\u524d\u982d\u524d\u91ce\u80cc\u5916\u5074\u90e8\u306e\u5de6\u5074\u3060\u3051\u306b\u306a\u305c\u76f8\u95a2\u304c\u898b\u3089\u308c\u3001\u53f3\u5074\u3067\u306f\u898b\u3089\u308c\u306a\u304b\u3063\u305f\u306e\u304b\u3001\u5b9f\u969b\u306e\u81e8\u5e8a\u7814\u7a76\u306b\u643a\u308f\u308b\u5148\u751f\u65b9\u3082\u4eca\u5f8c\u691c\u8a0e\u3055\u308c\u3066\u3044\u304f\u3068\u3044\u3046\u304a\u8a71\u306f\u3001\u8208\u5473\u6df1\u304b\u3063\u305f\u3067\u3059\u3002
                                                    \n <\/p>\n\n\n\n
                                                    \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a The control of attention is altered in the absence of subjective awareness\u8457\u8005 \uff1a T. WEBB, M. S. A. GRAZIANO
                                                    \n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a Functional Mechanisms of Attention and Disorders of Attention
                                                    \n 
                                                    \nAbstract
                                                    \nWe proposed that awareness is a crucial part of the control mechanism for attention. Many studies have shown that people can pay attention to a stimulus without being aware of it, suggesting that awareness is not needed for attention. However, awareness may still have effects on attention. We hypothesized that the presence or absence of awareness will change the control of attention. To test the hypothesis, we directly compared attention with and without awareness in human subjects performing a Posner task. Metacontrast masking of a visual stimulus was applied such that subjects reported being aware of the stimulus in one condition and unaware of the stimulus in another condition. The stimulus was used as the cue in the Posner task, allowing us to measure the amount of attention drawn by the stimulus. Attention was measured at five time points during the first 500 ms after stimulus presentation. We found that attention was drawn to the stimulus regardless of whether or not people were subjectively aware of it. However, attention was significantly different in the aware and the unaware conditions. It was not simply the case that awareness was associated with more attention. At one time point, subjects showed significantly more attention to the stimulus when they were unaware of it, whereas at another time point subjects showed significantly less attention to the stimulus when they were unaware of it. The time course of attention was changed by the presence or absence of awareness. These differences show that awareness is not an epiphenomenon and that it plays some role in the control of attention.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                                    \u3053\u306e\u767a\u8868\u3067\u306f\u3001\u8996\u899a\u523a\u6fc0\u3092\u7528\u3044\u3066\u610f\u8b58\u3068\u6ce8\u610f\u306e\u95a2\u4fc2\u6027\u3092\u691c\u8a0e\u3057\u3066\u3044\u3066\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\u3002\u3057\u304b\u3057\u3001\u4f7f\u7528\u3057\u3066\u3044\u308bPosner Task\u306e\u5185\u5bb9\u3092\u82f1\u8a9e\u3067\u8aac\u660e\u3055\u308c\u3066\u3082\u7406\u89e3\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\u3002\u5fc3\u7406\u72b6\u614b\u3068\u6ce8\u529b\u306e\u95a2\u4fc2\u6027\u306b\u304a\u3044\u3066\u306f\u79c1\u306e\u7814\u7a76\u5185\u5bb9\u306b\u8fd1\u304b\u3063\u305f\u3068\u3044\u3046\u3053\u3068\u3082\u3042\u308a\u3001\u3053\u306e\u4f7f\u7528\u8ab2\u984c\u306b\u95a2\u3057\u3066\u6587\u732e\u8abf\u67fb\u3092\u3057\u3066\u3044\u304f\u4e88\u5b9a\u3067\u3059\u3002
                                                    \n <\/p>\n\n\n\n
                                                    \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a Can wearable NIRS capture brain activities comparably to EEG?\u8457\u8005 \uff1a M. YAMAZAKI, H. EDA
                                                    \n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a Optical Methods\u2161
                                                    \n 
                                                    \nAbstract
                                                    \nIntroduction
                                                    \nNear infrared spectroscopy (NIRS) calculates hemoglobin parameters, such as change in oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb), using the near infrared lights around the 800 nm wavelength. The NIRS has been used in brain science, clinical field to evaluate the brain activities. We developed wearable NIRS sensor module and suggested that it can capture physiological information from everywhere in the body (Eda et.al., SfN2014). Purpose of this study is to validate the wearable NIRS as a new method of measuring the brain activities.
                                                    \nMethods
                                                    \nWe conducted EEG and NIRS recording simultaneously. 1)EEG : We attached 19 scalp EEG electrodes on the head according to 10-20 system and recorded EEG data using Neurofax EEG-1200 (NihonKohden) for 3 sessions. The session consisted of both eyes open and close state for 20 seconds each. 2) NIRS : We put two wearable NIRS sensor modules on the frontal head region (between Fpz and Fz) and the occipital head region (between O1 and O2) and measured the hemoglobin parameters (oxyHb and deoxyHb). We compared the signals recorded by EEG and NIRS in both eyes opening state and closing state.
                                                    \nResults
                                                    \nEye closing states : \u03b1 activities were captured predominant in the occipital head region (O1 and O2) immediately after eyes closed. NIRS showed that oxyHb dynamically elevated and decreased deoxyHb 3-5 seconds after the appearance of\u03b1 activities in the occipital head region compared to the frontal head region. Eye opening states : EEG showed mixture of low amplitude\u03b1 and \u03b2activities without predominant rhythmic activities. NIRS also showed no significant dynamic changes in both oxyHb and deoxyHb. Conclusion This study showed that the wearable NIRS module captured the dynamic oxyHb changes associate with the appearance of \u03b1 activities. This result is concordant with fMRI studies which hemodynamic response (increased oxyHb and decreased deoxyHb) was shown when the brain activities increased. The wearable NIRS module suggests utility in the assessment of the brain activities as a new measuring tool.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                                    \u3053\u306e\u767a\u8868\u3067\u306f\u3001\u30a6\u30a7\u30a2\u30e9\u30d6\u30eb\u306aNIRS\u30bb\u30f3\u30b5\u30e2\u30b8\u30e5\u30fc\u30eb\u306e\u6709\u7528\u6027\u3092\u691c\u8a3c\u3057\u3066\u3044\u308b\u3053\u3068\u306b\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\u3002\u76ee\u304c\u9589\u3058\u3066\u3044\u308b\u3068\u304d\u306b\u8996\u899a\u91ce\u3092\u3082\u3064\u5f8c\u982d\u90e8\u3067\u03b1\u6ce2\u304c\u691c\u51fa\u3055\u308c\u308b\u3053\u3068\u306b\u7591\u554f\u3092\u611f\u3058\u307e\u3057\u305f\u304c\u3001\u3053\u308c\u304b\u3089\u8133\u6d3b\u52d5\u3092\u8a08\u6e2c\u3067\u304d\u308bNIRS\u30bb\u30f3\u30b5\u30e2\u30b8\u30e5\u30fc\u30eb\u304c\u5b9f\u7528\u5316\u3055\u308c\u308c\u3070\u3001\u77e5\u7684\u751f\u7523\u6027\u5411\u4e0a\u3092\u4fc3\u9032\u3055\u305b\u308b\u4f5c\u696d\u74b0\u5883\u306e\u81ea\u52d5\u5236\u5fa1\u30b7\u30b9\u30c6\u30e0\u3082\u69cb\u7bc9\u53ef\u80fd\u306b\u306a\u308b\u306e\u304b\u306a\u3001\u3068\u30c6\u30f3\u30b7\u30e7\u30f3\u304c\u4e0a\u304c\u308a\u307e\u3057\u305f\u3002
                                                    \n <\/p>\n\n\n\n
                                                    \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a Features of sleep architecture relate to the neural representation and behavioral stability of memories\u8457\u8005 \uff1a E. COWAN, A. LIU, S. KOTHARE, O. DEVINSKY, L. DAVACHI
                                                    \n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a Human Memory Processes : Encoding, Retrieval, and Consolidation
                                                    \n 
                                                    \nAbstract
                                                    \nTheories of systems memory consolidation posit that memories are stabilized as they become more distributed throughout the cortex. Sleep has been linked with successful memory consolidation, and evidence suggests particular features in the architecture of sleep may relate to sleep-dependent memory enhancements. Recent evidence suggests a 24-hour delay promotes more distributed memory traces, as measured by hippocampal-cortical functional connectivity, in manner predictive of subsequent behavioral resistance to forgetting, indicating a specific role in memory stabilization. However, it remains unknown what aspects of sleep architecture are related to the distribution of memory traces, and the effect this has on behavioral measures of memory. To investigate this relationship, we designed a three-day experiment utilizing overnight measurements of polysomnography, fMRI, and behavior. Subjects were asked to repeatedly encode sets of word-image pairs with an intervening period of overnight sleep (Sleep List), or a brief wakeful period (Awake List), thus differing in the opportunity for potential consolidation. During the second presentation, subjects restudied the previously seen word-image pairs while in the scanner. Cued source recall was probed immediately following the scan and after a 24-hour delay, providing a measure of memory stability over time. Overnight sleep was classified into its component stages, revealing a selective relationship between duration of Stage 2 sleep and memory performance for the delayed test. Analysis of the fMRI data demonstrated a positive correlation between duration of Stage 2 sleep and univariate activity in ventromedial prefrontal cortex, left middle occipital gyrus, and left lateral occipital cortex, but a negative correlation with activity in the hippocampus, perirhinal and parahippocampal cortices, specifically for the successfully recalled Sleep List pairs. These findings suggest that the duration of Stage 2 sleep relates to a shift in activation patterns from medial temporal lobe regions to distributed cortical regions. Furthermore, activity in the vmPFC and left middle occipital gyrus regions was found to significantly correlate with memory performance only on the delayed test, indicating that activity in these regions may relate to the stability of the memory. Additional analyses will focus on the relationship of other oscillatory features of sleep architecture, including spindle density, with the neural representation and behavioral expression of memory traces.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                                    \u3053\u306e\u767a\u8868\u3067\u306f\u30013\u65e5\u9593\u306eMRI\u5b9f\u9a13\u3092\u7d4c\u3066\u8a18\u61b6\u306e\u5b9a\u7740\u3068\u7761\u7720\u306e\u95a2\u4fc2\u6027\u3092\u691c\u8a0e\u3057\u3066\u3044\u308b\u3068\u3053\u308d\u306b\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\u3002MRI\u306e\u7d30\u304b\u3044\u5b9f\u9a13\u8a2d\u8a08\u3084\u691c\u8a0e\u65b9\u6cd5\u306a\u3069\u3001\u79c1\u306e\u82f1\u8a9e\u80fd\u529b\u3067\u306f\u7406\u89e3\u3067\u304d\u306a\u3044\u90e8\u5206\u3082\u3042\u308a\u307e\u3057\u305f\u3002\u4e3b\u89b3\u7684\u306a\u30a2\u30f3\u30b1\u30fc\u30c8\u3060\u3051\u3067\u306f\u306a\u304f\u3001\u8133\u79d1\u5b66\u306e\u89b3\u70b9\u304b\u3089\u3001\u8a18\u61b6\u306e\u5b9a\u7740\u5ea6\u5408\u3092\u691c\u8a0e\u3057\u3066\u3044\u308b\u3068\u3053\u308d\u306b\u3001\u79c1\u306e\u7814\u7a76\u306b\u3082\u751f\u304b\u305b\u308b\u90e8\u5206\u304c\u3042\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u611f\u3058\u307e\u3057\u305f\u3002
                                                    \n <\/p>\n\n\n\n
                                                    \u767a\u8868\u30bf\u30a4\u30c8\u30eb \uff1a Neural activation and saccadic eye movements involved during letter and object naming speed tasks\u8457\u8005 \uff1a N. Z. AL DAHHAN, D. C. BRIEN, J. R. KIRBY, D. P. MUNOZ
                                                    \n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d \uff1a Eye Movements : Neurophysiology of Saccades
                                                    \n 
                                                    \nAbstract
                                                    \nNaming speed (NS) tasks, which measure how quickly and accurately subjects can name sets of highly familiar stimuli (e.g., letters) randomly presented in a visual array, have been shown to be a precursor and concurrent correlate of accurate and efficient reading. However, it is still not known what cognitive processes underlie this relationship. Functional magnetic resonance imaging (fMRI) was used to investigate the neural substrates and cognitive processes underlying performance during letter and object NS tasks. We used three methods to examine task performance: (a) changing stimulus composition to emphasize phonological and\/or visual aspects; (b) decomposing NS times into pause and articulation components; and (c) analyzing eye movements and brain activation involved in a NS task. We recruited 19 healthy young adults (ages 21 – 26 years), and employed a block design consisting of a letter NS task and three variants that were either phonologically and\/or visually confusing (Compton, 2003); and an object NS task with a variant in which the object names rhymed with one another, while subjects\u2019 eye movements and articulations were recorded. We examined how these manipulations influenced performance and whether they resulted in differences in neural activation. Behavioral analyses revealed that for the letter NS task, NS manipulations were associated with specific patterns of performance which were influenced by visual rather than phonological similarity. When the task was both visually and phonologically similar, participants had significantly longer naming times and fixation durations, and made more frequent saccades and regressions. However, for the object NS tasks participants’ performance was not affected when the names of the objects rhymed with one another. This was indicated by a trend in which participants made shorter fixations and fewer saccades, and had significantly shorter naming times and made fewer regressions on the phonologically similar object task than the control task. fMRI results indicated significant activation during both letter and object NS tasks in brain areas involved in the reading network and in tasks that require eye movement control and attention in typical adult readers, such as the temporal-parietal area, inferior frontal cortex, superior temporal gyrus, and the ventral visual stream. Further analyses revealed that the different task manipulations target key structures within this reading network, such as the anterior cingulate cortex, middle temporal gyrus, and thalamus. These findings reveal that NS tasks recruit the same network of neural structures that are involved in reading.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                                                    \u3053\u306e\u767a\u8868\u3067\u306f\u3001\u8996\u4f5c\u696d\u306b\u304a\u3051\u308b\u4f5c\u696d\u52b9\u7387\u3092\u6e2c\u308b\u8ab2\u984c\u3068\u3057\u3066Naming Speed Task\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3057\u305f\u3002\u8ab2\u984c\u5185\u5bb9\u304c\u79c1\u306e\u7814\u7a76\u3067\u4f7f\u7528\u3057\u3066\u3044\u308b\u8996\u899a\u63a2\u7d22\u8ab2\u984c\u3068\u985e\u4f3c\u3057\u3066\u3044\u308b\u3053\u3068\u304b\u3089\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\u3002fMRI\u3092\u7528\u3044\u3066\u306e\u5b9f\u9a13\u3067\u306f\u3042\u308a\u307e\u3057\u305f\u304c\u3001\u4e0b\u524d\u982d\u56de\u3084\u4e0a\u5074\u982d\u56de\u306a\u3069\u304c\u6d3b\u6027\u3057\u3066\u3044\u308b\u5185\u5bb9\u3067\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u691c\u8a0e\u3082\u3055\u308c\u3066\u3044\u307e\u3057\u305f\u304c\u3001\u89e3\u6790\u624b\u6cd5\u306b\u95a2\u3057\u3066\u306f\u7406\u89e3\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\u3002\u3053\u306e\u8ab2\u984c\u306b\u95a2\u3057\u3066\u3082\u6587\u732e\u8abf\u67fb\u3092\u884c\u3063\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002
                                                    \n 
                                                    \n 
                                                    \n\u53c2\u8003<\/strong>URL<\/strong>
                                                    \n1) https:\/\/www.sfn.org\/annual-meeting\/neuroscience-2015<\/p>\n","protected":false},"excerpt":{"rendered":"

                                                    Neuroscience 2015 \u304c\u3001October 17-21\u306e\u65e5\u7a0b\u3067\u3001Chicago \u3000\u30de\u30b3\u30fc\u30df\u30c3\u30af\u30d7\u30ec\u30a4\u30b9\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\u3002 \u4e0b\u8a18\u306e\uff14\u4ef6\u306e\u767a\u8868\u3092\u884c\u3044\u307e\u3057\u305f\u3002 Examination of the effect … <\/p>\n

                                                    “\u3010\u901f\u5831\u3011Neuroscience 2015” \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":[6],"tags":[],"class_list":["post-3074","post","type-post","status-publish","format-standard","hentry","category-6"],"_links":{"self":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/3074","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=3074"}],"version-history":[{"count":0,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/3074\/revisions"}],"wp:attachment":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3074"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3074"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3074"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}