{"id":5545,"date":"2018-10-08T18:08:10","date_gmt":"2018-10-08T09:08:10","guid":{"rendered":"http:\/\/www.is.doshisha.ac.jp\/news\/?p=5545"},"modified":"2018-10-08T18:08:10","modified_gmt":"2018-10-08T09:08:10","slug":"%e3%80%90%e9%80%9f%e5%a0%b1%e3%80%91-3","status":"publish","type":"post","link":"https:\/\/is.doshisha.ac.jp\/news\/?p=5545","title":{"rendered":"\u3010\u901f\u5831\u3011"},"content":{"rendered":"<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u6771\u4eac\u5927\u5b66\u306b\u3066\u958b\u50ac\u3055\u308c\u305f\u3000fNIRS2018\u306b\u7814\u7a76\u5ba4\u304b\u30894\u4ef6\u306e\u767a\u8868\u3092\u884c\u3044\u307e\u3057\u305f\u3002<\/p>\n<ul>\n<li>A fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task Megumi Mizuno, Sho Taniguchi, Satoru Hiwa,Tomo Hiroyasu<\/li>\n<li>Detecting attentional and inattentional brain metastates based on dynamic functional connectivity analysis, Miyu Nishizawa , Satoru Hiwa,Tomo Hiroyasu<\/li>\n<\/ul>\n<p><!--more--><br \/>\n<strong>\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"183\"><strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n<td width=\"467\">\u6c34\u91ce\u3081\u3050\u307f<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"467\">\u5354\u8abf\u8ab2\u984c\u6642\u306e\u8133\u9593\u795e\u7d4c\u540c\u671f\u306efNIRS\u3092\u7528\u3044\u305fhyperscanning\u306e\u7814\u7a76<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"467\">A fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u8457\u8005<\/strong><\/td>\n<td width=\"467\">Megumi Mizuno, Sho Taniguchi, Satoru Hiwa,Tomo Hiroyasu<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u4e3b\u50ac<\/strong><\/td>\n<td width=\"467\">The Society for fNIRS<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\n<td width=\"467\">fNIRS2018<\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u4f1a\u5834<\/strong><\/td>\n<td width=\"467\"><strong>\u6771\u4eac\u5927\u5b66\u3000\u672c\u90f7\u30ad\u30e3\u30f3\u30d1\u30b9<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"183\"><strong>\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n<td width=\"467\">2018\/10\/05-2018\/10\/08<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n<ol>\n<li>\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u304b\u3051\u3066\uff0c\u6771\u4eac\u5927\u5b66 \u672c\u90f7\u30ad\u30e3\u30f3\u30d1\u30b9\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305ffNIRS2018\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\uff0c\u5149\u5b66\u7684\u65b9\u6cd5\u3092\u7528\u3044\u3066\u751f\u7269\u7d44\u7e54\u3001\u7279\u306b\u8133\u6a5f\u80fd\u3092\u7406\u89e3\u3057\u3088\u3046\u3068\u3059\u308b\u57fa\u790e\u79d1\u5b66\u8005\u304a\u3088\u3073\u81e8\u5e8a\u79d1\u5b66\u8005\u306e\u5c02\u9580\u5bb6\u304c\u610f\u898b\u4ea4\u63db\u3092\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e\u79c1\u306f\uff0c2018\/10\/05\u304b\u30892018\/10\/08\u306e\u5168\u65e5\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u65e5\u548c\u5148\u751f\uff0c\u897f\u6fa4\u7f8e\u7d50\uff0c\u6c60\u7530\u5e78\u6a39\uff0c\u5c71\u672c\u6e09\u5b50\uff0c\u8c37\u53e3\u5c1a\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e<\/p>\n<ol start=\"2\">\n<li>\u7814\u7a76\u767a\u8868\n<ul>\n<li>\u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\u79c1\u306f2018\/10\/07\u306ePoster Session \u300cPoster\u2161\u300d\u306b\u3066\u8c37\u53e3\u5c1a\u3068\u5171\u306b\u767a\u8868\u81f4\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c\u5348\u524d,\u5348\u5f8c1\u6642\u9593\u305a\u3064\u306e\u8a082\u6642\u9593\uff0c\u81ea\u7531\u306b\u767a\u8868\u304a\u3088\u3073\u8cea\u7591\u5fdc\u7b54\u3092\u884c\u3046\u6642\u9593\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e<br \/>\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u300cA fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task\u300d\u3067\u3059\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"661\">Introduction: Social interaction is a dynamic behavior between individuals who modify their actions and reactions depending on the actions of their partner. In this study, we investigate the relationship between social interaction and brain functions. Cui et al. analyzed the neural synchronization between two subjects who played a cooperation game involving synchronizing each other\u2019s response timing and revealed that the interpersonal brain coherence of the subjects increased during the cooperative task [1]. In this study, to easily facilitate the cooperative behavior of the participants, we improved the experimental design and examined the inter-brain neural synchronization during the cooperative task.<br \/>\nMethods: Twenty-two healthy adult males (11 pairs, age: 22.7 \u00b1 1.0 years old, right-handed) participated in this experiment. The experimental environment is shown in Fig 1. The brains of the two participants during their social interaction were simultaneously measured by hyperscanning using a single functional near-infrared spectroscopy (fNIRS) device (ETG-7100, Hitachi, Ltd.). A 3 \u00d7 10 probe consisting of 47 measurement channels was attached to the forehead of each subject. Participants were instructed: (1) to synchronize the response timing of their partner after the cue (synchronization task), (2) to respond faster than their partner (competition task), and (3) to respond quickly to the cue (single A\/B task) [1]. In the synchronization task, the time difference between the responses of the two participants were fed back to each of them. Each participant predicted his partner&#8217;s behavior based on the time difference, and was asked to synchronize his responses at the next cue. Wavelet transform coherence was calculated from two sets of time-series data of cerebral blood flow changes. Then we performed a one-sample t-test (p &lt; 0.05) of the coherence increase of each task and investigated the brain regions where the coherence increased.<br \/>\nResults &amp; Discussion: The difference in response time between the two participants in the synchronization task was significantly larger than that of the single A and B task (p &lt; 0.05). This result indicates that the participants not only responded quickly to the cue, but also reacted by anticipating the behavior of their opponents. A t-score map of coherence increase is shown in Fig 2. The coherence within the left superior frontal gyrus (SFG) and left middle frontal gyrus (MFG) increased significantly in the synchronization task. The left SFG is involved in building a trust relationship [2]. Hence, it is assumed that this region affects cooperative behavior. Furthermore, the coherence in these two regions did not increase significantly in either the competitive or single task. Therefore, we suggest that the inter-brain synchronization in these brain regions can be utilized as a metric of cooperativeness.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<ul>\n<li>\u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n<p>\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<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb91<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\n\u5354\u8abf\u3068\u7af6\u4e89\u3092\u6bd4\u8f03\u3057\u3066wavelet coherence\u3067\u8a55\u4fa1\u3057\u3066\u3044\u308b\u5148\u884c\u7814\u7a76\u304c\u65e2\u306b\u5831\u544a\u3055\u308c\u3066\u3044\u308b\u304c\u3001\u65b0\u898f\u6027\u306f\u4f55\u304b\u3002\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u3001\u5148\u884c\u7814\u7a76\u306e\u5b9f\u9a13\u3092\u6a21\u5023\u3057\u3066\u3044\u308b\u304c\u3001\u3088\u308a\u591a\u304f\u306e\u9818\u57df\u3092\u8a08\u6e2c\u3057\u3066\u3044\u307e\u3059\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb92<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\ncoherence\u306f\u884c\u52d5\u306e\u30a2\u30af\u30c6\u30a3\u30d9\u30fc\u30b7\u30e7\u30f3\u3092\u691c\u51fa\u3057\u3066\u3057\u307e\u308f\u306a\u3044\u304b\uff0e\u7af6\u4e89\u306f\u3088\u308a\u884c\u52d5\u304c\u540c\u671f\u3057\u3066\u3044\u308b\u305f\u3081\u6bd4\u8f03\u3067\u304d\u306a\u3044\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3054\u610f\u898b\u3092\u9802\u304d\u307e\u3057\u305f\uff0eCoherence\u306b\u3088\u308b\u8a55\u4fa1\u306e\u6709\u7528\u6027\u3092\u691c\u8a0e\u3057\u3066\u3044\u308b\u4eba\u3082\u3044\u308b\u305f\u3081\uff0c\u8a55\u4fa1\u65b9\u6cd5\u306e\u691c\u8a0e\u3082\u884c\u3063\u3066\u3044\u304f\u5fc5\u8981\u304c\u3042\u308b\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb93<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\nSingle\u8ab2\u984c\u306f\u3069\u3046\u306a\u3063\u305f\u306e\u304b\u3002\u306a\u305csingle\u8ab2\u984c\u3092\u884c\u3063\u305f\u306e\u304b\u3002\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u306f\u3001\u305f\u3060\u5358\u306b\u5408\u56f3\u306b\u5bfe\u3057\u3066\u5fdc\u7b54\u3059\u308b\u3068\u3044\u3046\u8981\u7d20\u3092\u6bd4\u8f03\u3059\u308b\u305f\u3081\u306b\u884c\u3063\u305f\uff0eSingel\u8ab2\u984c\u306e\u7d50\u679c\u306f\u3001singleA\u3068B\u306e\u30b3\u30f3\u30c7\u30a3\u30b7\u30e7\u30f3\u306f\u540c\u3058\u306a\u306e\u306b\uff0ct-map\u304c\u304b\u306a\u308a\u7570\u306a\u3063\u305f\u305f\u3081\uff0c\u72b6\u614b\u3092\u63a8\u5b9a\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u306a\u304b\u3063\u305f\uff0e\u3053\u308c\u306f\u88ab\u9a13\u8005\u306e\u500b\u4eba\u306eEQS\u30b9\u30b3\u30a2\u306e\u9055\u3044\u306b\u73fe\u308c\u3066\u3044\u3066\uff0c\u3053\u306e\u9055\u3044\u304c\u8133\u72b6\u614b\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u305f\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb94<\/strong><br \/>\n\u30e4\u30af\u30eb\u30c8\u306e\u7814\u7a76\u6240\u306e\u65b9\u304b\u3089\u3054\u610f\u898b\u3092\u9802\u304d\u307e\u3057\u305f\uff0e<br \/>\n\u7af6\u4e89\u72b6\u614b\u304c\u597d\u304d\u306a\u4eba\u3068\u5354\u8abf\u72b6\u614b\u304c\u597d\u304d\u306a\u4eba\u306e\u4e3b\u89b3\u7684\u306a\u72b6\u614b\u306a\u3069\u304c\u7d50\u679c\u306b\u5f71\u97ff\u3057\u305f\u308a\u3057\u306a\u3044\u306e\u304b\uff0e\u5b9f\u9a13\u5b9f\u65bd\u5f8c\u306b\u30a2\u30f3\u30b1\u30fc\u30c8\u3092\u5fc3\u7406\u8a55\u4fa1\u306e\u30a2\u30f3\u30b1\u30fc\u30c8\u3092\u884c\u3063\u3066\u307f\u3066\u306f\u3069\u3046\u304b\uff0e\u78ba\u304b\u306b\u5354\u8abf\u72b6\u614b\u3060\u3051\u304c2\u8005\u306e\u95a2\u4fc2\u6027\u306e\u4e2d\u3067\u826f\u3044\u72b6\u614b\u3067\u3042\u308b\u304b\u306f\u5206\u304b\u3089\u306a\u3044\u305f\u3081\uff0c\u30a2\u30f3\u30b1\u30fc\u30c8\u306b\u95a2\u3057\u3066\u4eca\u5f8c\u306e\u53c2\u8003\u306b\u3057\u307e\u3059\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb96<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\n\u306a\u305c\u5354\u8abf\u6642\u306b\u306e\u307fMFG.L\u306e\u6709\u610f\u306a\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u5897\u52a0\u304c\u898b\u3089\u308c\u305f\u3068\u8003\u3048\u3066\u3044\u308b\u304b\u3068\u3054\u8cea\u554f\u9802\u304d\u307e\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u306f\uff0cMFG.R\u306f\u5354\u8abf\u6642\u3068\u7af6\u4e89\u6642\u306e\u4e21\u65b9\u306b\u898b\u3089\u308c\u3066\u3044\u308b\u305f\u3081\uff0c\u4ed6\u8005\u306e\u3053\u3068\u3092\u8003\u3048\u308b\u3053\u3068\u306b\u95a2\u4e0e\u3057\u3066\u304a\u308a\uff0cMFG.L\u306f\u305d\u306e\u4e2d\u3067\u3082\u5354\u529b\u3059\u308b\u3053\u3068\u306b\u95a2\u308f\u308b\u9818\u57df\u3067\u3042\u3063\u305f\u53ef\u80fd\u6027\u304c\u3042\u308b\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u4e00\u65b9\u3067\uff0c\u5fc3\u306e\u7406\u8ad6\u306b\u95a2\u308f\u308bMFG\u306e\u5de6\u53f3\u5dee\u306b\u3064\u3044\u3066\u8abf\u67fb\u3057\u3066\u3044\u304f\u5fc5\u8981\u304c\u3042\u308b\u3068\u8003\u3048\u3066\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<ul>\n<li>\u611f\u60f3<\/li>\n<\/ul>\n<p>2\u56de\u76ee\u306e\u56fd\u969b\u5b66\u4f1a\uff0c3\u56de\u76ee\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3068\u3044\u3046\u3053\u3068\u3082\u3042\u308a\uff0c\u3053\u308c\u307e\u3067\u306e\u7d4c\u9a13\u3092\u751f\u304b\u3057\u3066\u843d\u3061\u7740\u3044\u3066\u767a\u8868\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u3082\u4f55\u304b\u3057\u3089\u306e\u56de\u7b54\u3092\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u305f\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u601d\u3044\u307e\u3059\uff0e\u591a\u304f\u306e\u4eba\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u9802\u304d\u3001hyperscanning\u306e\u7814\u7a76\u3092\u884c\u3063\u3066\u3044\u308b\u65b9\u3005\u3068\u4ea4\u6d41\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u3001\u5927\u5909\u6709\u610f\u7fa9\u306a\u767a\u8868\u3068\u306a\u308a\u307e\u3057\u305f\uff0e\u3053\u306e\u767a\u8868\u3092\u901a\u3058\u3066\u3001\u81ea\u5206\u306e\u7814\u7a76\u304chyperscanning\u7814\u7a76\u306e\u6a19\u6e96\u306e\u30ec\u30d9\u30eb\u306b\u307e\u3067\u6301\u3063\u3066\u3044\u304f\u3053\u3068\u304c\u51fa\u6765\u305f\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3001\u3053\u306e1\u5e74\u9593\u306e\u53d6\u308a\u7d44\u307f\u306e\u6210\u679c\u3092\u5b9f\u611f\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e<\/p>\n<ol start=\"3\">\n<li>\u8074\u8b1b<\/li>\n<\/ol>\n<p>\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"661\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Verifying Wavelet coherence analysis on fNIRS data using pseudorandom visual stimulation sequence<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a X. Zhang, J. A. Noah, S. Dravida, Y. Ono and J. Hirsch<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aPoster\u2160<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Neural mechanisms that underlie dynamic interpersonal interactions are thought to include temporally synchronous signals that reflect coupled processes between two brains [1]. Wavelet coherence analysis of hemodynamic signals acquired simultaneously during hyper-scanning experiments has been proposed for analysis of these neural processes [2,3]. However, this computational approach has not been validated against known markers. Here we generate a set of known neural coherences using pseudo random sequences of reversing checkerboard patterns. It is expected that input sequences that were more highly correlated generated higher cross-brain output correlations of wavelets in the visual cortex across pairs of subjects. Each visual stimulus event was a 2-second full-field reversing checkerboard pattern. Three random sequences, called sequence A, B and C (inset in figure), of such visual stimuli were presented for 2 minutes and repeated twice. The sequences were generated to have varying levels of correlation (e g: A-B more correlated than A-C). The expected coherence (left panel) was obtained by coherence analysis on the modeled fNIRS waveform, which was generated by convolving the stimulus sequence and the hemodynamic response function (HRF).The overall expected coherence is summarized as the average coherence within 0-30 second wavelength range (horizontal lines and numbers in left panel). Ten subjects participated. Subject\u2019s data were randomly paired with every other subject\u2019s data, resulting in ninety possible pairs.<br \/>\nThe combinations included A-A, B-B, or C-C, where both subjects viewed identical sequences of the stimuli (green). The other pairings were AB(red), A-C (blue) and B-C (cyan). The wavelet coherence results from measured fNIRS deOxyHB data (right panel) confirmed the expected coherence. Our results validate wavelet coherence as a technique for quanitfying the coherence of brain signals across participants during hyperscanning to study social interaction in ecologically valid paradigms.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Wavelet coherence\u304c\u507d\u967d\u6027\u3092\u691c\u51fa\u3057\u3066\u3044\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u30ec\u30d3\u30e5\u30fc\u3067\u306e\u6307\u6458\u3082\u3042\u3063\u305f\u305f\u3081\u3001\u3068\u3066\u3082\u8208\u5473\u6df1\u3044\u7814\u7a76\u3067\u3057\u305f\uff0e\u6307\u30bf\u30c3\u30d7\u306e\u540c\u671f\u3068\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u306e\u540c\u671f\u304c\u985e\u4f3c\u3057\u3066\u3044\u305f\u3068\u3044\u3046\uff0c\u3044\u3044\u7d50\u679c\u304c\u793a\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"661\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Interpersonal brain synchronization during social cooperation in<br \/>\nchildren with Autism: a hyperscanning study using fNIRS<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Vanessa Reindl, Jana A. Kruppa, Julia Prinz, Eileen Wei\u00df, Christian<br \/>\nGerloff, Wolfgang Scharke, Beate Herpertz-Dahlmann, Kerstin Konrad and Martin Schulte-R\u00fcther<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster\u2161<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Background: Interpersonal brain synchronization has repeatedly been demonstrated during joint social tasks for healthy adults and recently also for parent-child dyads [1]. Pioneering studies have demonstrated diminished brain-to-brain synchrony in adults with autism spectrum disorder (ASD) during such tasks [2]. To date, no study has investigated this in children with ASD and has examined whether the familiarity of the interaction partner modulates interpersonal brain synchronization.<br \/>\nMethods: Using functional near-infrared spectroscopy (fNIRS) hyperscanning, we assessed brain-to-brain synchrony in prefrontal brain regions during a cooperative and a competitive computer task in 43 typically developing (TD) children and 15 children with ASD (8-18 years) while playing with one of their parents. Adult strangers performed the identical tasks with each child. Participants were instructed to either respond jointly via button press in response to a target (cooperation) or to respond faster than the other player (competition). Within each dyad, wavelet coherence was calculated for oxy-hemoglobin brain signals of corresponding channels as a measure of brain-to-brain synchrony.<br \/>\nResults: On the behavioral level, preliminary results showed that the dyad\u2019s cooperative performance was neither influenced by interaction partner nor by group. However, during competition, the child won more often against the parent than against the stranger, and children with ASD won more often against parent\/stranger than TD children. On the neural level, preliminary results revealed a significant interaction of partner and group for coherence in two channels located in Brodmann areas 8 and 9: coherence in the ASD group was significantly smaller when playing with the parent compared to a stranger. No significant effect of partner was observed in the TD group.<br \/>\nConclusion: Data collection in both samples is ongoing. Preliminary results suggest<br \/>\ndifferential coherence in ASD with respect to the interaction partner\u2019s familiarity. In a larger sample it remains to be seen, whether fNIRS hyperscanning represents a valuable tool for investigating brain-to-brain synchrony during social tasks as a proxy for typical and atypical social interaction.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5b66\u4f1a\u3092\u901a\u3057\u3066fNIRS\u306e\u5229\u70b9\u3092\u751f\u304b\u3057\u3066\u5b50\u4f9b\u3092\u5bfe\u8c61\u306b\u3057\u3066\u3044\u308b\u7814\u7a76\u304c\u591a\u3044\u3068\u611f\u3058\u307e\u3057\u305f\uff0e\u4e2d\u3067\u3082\u3053\u306e\u767a\u8868\u306f\uff0c\u5354\u8abf\u6642\u3068\u7af6\u4e89\u6642\u306e\u89aa\u5b50\u3068\u77e5\u3089\u306a\u3044\u5927\u4eba\u3068\u5b50\u4f9b\u306e\u795e\u7d4c\u540c\u671f\u3092Cui\u306e\u5b9f\u9a13\u3092\u5b50\u4f9b\u3067\u3082\u5206\u304b\u308b\u30b2\u30fc\u30e0\u306b\u3057\u3066\u5b9f\u9a13\u3092\u884c\u3044\u6bd4\u8f03\u3057\u3066\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"661\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000THE NEW NEUROSCIENCE OF TWO:<br \/>\nHYPERSCANNING WITH fNIRS TO UNDERSTAND COMMUNICATING BRAINS<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Joy Hirsch, Ph.D.<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Cognitive &amp; social neuroscience [invited talk]<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Humans are a profoundly social species. However, little is known about the most fundamental brain functions that mediate live social interactions. This knowledge gap between single and social brain processes, is, in part, a consequence of conventional neural imaging methods that are generally restricted to single individuals, static tasks, and nonverbal responses. However, recent developments of fNIRS hyperscanning (imaging two individuals simultaneously) enables rigorous investigation of this unexplored neural domain of human social behavior. Two existing theoretical frameworks converge as a foundation for this new \u201cneuroscience of two\u201d. The first is the Interactive Brain Hypothesis (De Jaegher, et al, 2016) which proposes that social interactions are mediated by dedicated brain processes. This hypothesis provides a general framework for the investigation of neural mechanisms underlying social interaction. The second is a quantifiable model of dynamic neural coupling, i.e. the correlation between temporal patterns of neural signals across two interacting partners (Hasson and Frith, 2016). This model proposes that dynamic coupling is the mechanism by which information is shared between the sender and the receiver across brains. Hyperscanning with fNIRS, together with these emerging theoretical frameworks, establishes fNIRS as the neuroimaging method of choice for investigations of live human-to-human interactions. Paradigms for investigation of two individuals engaged in live and spontaneous communications include developments for imaging in natural environments as well as the computational methods necessary to quantify live cross-brain interactions. We have applied these tools to test specific cases of the interactive brain hypothesis using fNIRS hyperscanning and primary social cues such as real eye-to-eye contact compared to eye gaze at a picture-face (Hirsch, et al., 2017), a video-face (Noah, et al.,2018), and talking and listening (Hirsch, et al., 2018) with and without social interaction. Consistent with the Interactive Brain Hypothesis cross-brain coherence measured by Wavelet Coherence Analysis (MATLAB Wavelet Toolbox) between local brain areas is greater for interactive than non-interactive conditions. Specifically, dynamic neural coupling increases during interactions such as eye-to-eye contact and interactive speaking and listening. Further, the dynamic neural coupling is associated with neural activity in temporal-parietal regions of the brain consistent with specialized cross-brain neural mechanisms for live social interaction regardless of the modality or task. These, and other similar findings recently reported using fNIRS hyperscanning, contribute to an expanding experimental and theoretical foundation for a new neuroscience where the aim is to understand the dynamic signal exchanges and neural mechanisms within a dyad that underlie live episodes of social interaction in natural conditions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>fNIRS hyperscanning\u306e\u52d5\u5411\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u3066\u8208\u5473\u6df1\u3044\u8b1b\u6f14\u3067\u3057\u305f\uff0eCooperation\u3068Competition\u306e\u6bd4\u8f03\u306e\u7814\u7a76\u306f\u6700\u3082\u591a\u3044\u30c6\u30fc\u30de\u3067\u3042\u308b\u3053\u3068\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u4e00\u65b9\u3067\u30a2\u30a4\u30b3\u30f3\u30bf\u30af\u30c8\u306e\u7814\u7a76\u306f\u307b\u307c\u306a\u304f\uff0c\u6628\u5e74MISL\u3067\u53d6\u308a\u7d44\u307e\u308c\u3066\u3044\u305f\u30a2\u30a4\u30b3\u30f3\u30bf\u30af\u30c8\u306e\u7814\u7a76\u306f\u3044\u3044\u30c6\u30fc\u30de\u3060\u3063\u305f\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u601d\u3044\u307e\u3057\u305f\uff0e\u4f7f\u7528\u88c5\u7f6e\u3092\u7814\u7a76\u5ba4\u306b\u3042\u308b\u88c5\u7f6e\u3070\u304b\u308a\u3067\u5b9f\u969b\u306b\u540c\u3058\u3088\u3046\u306a\u5b9f\u9a13\u3092\u884c\u3046\u3053\u3068\u3082\u74b0\u5883\u7684\u306b\u306f\u53ef\u80fd\u3067\u3042\u308b\u3053\u3068\u3082\u5206\u304b\u308a\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"661\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Extraction of Synchronizing Cortical Activities\u3000between Mother and Infant<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Satoshi Morimoto, Eiichi Hoshino, Masahiro Hata,\u3000Michiko Asano<br \/>\nand Yasuyo Minagawa<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster\u3000\u2162<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aBackground: Hyperscanning studies using functional near-infrared spectrography (fNIRS) have revealed synchronized brain activities between participants who interact each other. However, synchronizing activities between mother and infant could not be evaluated precisely by analysis methods used previously (e.g., wavelet coherence), because those methods assume that two brains have similar hemodynamics, while this is not the case for adult and infant brains. The present study investigated how mother and 3- to 4-month-old infant spontaneously interact each other at brain hemodynamic levels by employing a new analysis method (Fig.1) that we developed.<br \/>\nMethods: 55 mother-infant dyads were participated in fNIRS recording under three<br \/>\nconditions; breast feeding (the feeding condition), resting state during mother holding her sleeping infant (the holding condition), and resting state during separation (the separation condition) [1]. For the following analysis, we utilized data of dyads who completed each condition. After removing artifacts, we obtained power spectrograms of OxyHb signals and combined them into a large matrix. The matrix was decomposed by non-negative matrix factorization, which lead two smaller matrices; a basis matrix and a coefficient matrix. We calculated the mean of the coefficients for each condition and compared these values between the conditions.<br \/>\nResults and discussion: We found several synchronized components which significantly<br \/>\nincreased in the feeding condition compared to those in other conditions. These components were shared by mother and infant channels, which related to the social brain network. These results suggested that we successfully extracted synchronized brain activities between mother and infant, and such synchronizations may be a fundamental of social attachment between them.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u7570\u306a\u308b\u5468\u6ce2\u6570\u6210\u5206\u306e\u985e\u4f3c\u5ea6\u3092\u7b97\u51fa\u3059\u308b\u305f\u3081\u306b\uff0cNon-negative matrix function\u3092\u7528\u3044\u3066\u3044\u307e\u3057\u305f\uff0eHyperscanning\u306e\u7814\u7a76\u3067\u306f\uff0c\u89e3\u6790\u65b9\u6cd5\u306b\u5de5\u592b\u304c\u898b\u3089\u308c\u308b\u7814\u7a76\u304c\u3042\u307e\u308a\u306a\u304b\u3063\u305f\u305f\u3081\uff0c\u4e00\u756a\u9762\u767d\u3044\u5185\u5bb9\u3060\u3068\u611f\u3058\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n\u53c2\u8003\u6587\u732e<\/p>\n<ul>\n<li>fNIRS2018 abstract<\/li>\n<\/ul>\n<p>http:\/\/fnirs2018.org\/wp-content\/uploads\/2018\/09\/fNIRS2018_abstract.pdf<br \/>\n<strong>\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"147\"><strong>\u00a0<\/strong><br \/>\n<strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n<td width=\"373\">&nbsp;<br \/>\n\u897f\u6fa4\u7f8e\u7d50<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">\u52d5\u7684\u6a5f\u80fd\u7684\u63a5\u7d9a\u5206\u6790\u306b\u57fa\u3065\u304f\u6ce8\u610f\u3068\u4e0d\u6ce8\u610f\u30e1\u30bf\u72b6\u614b\u306e\u691c\u51fa<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">Detecting attentional and inattentional brain metastates based on dynamic functional connectivity analysis<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8457\u8005<\/strong><\/td>\n<td width=\"373\">\u897f\u6fa4\u7f8e\u7d50, \u65e5\u548c\u609f, \u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4e3b\u50ac<\/strong><\/td>\n<td width=\"373\">Society for functional Near Infrared Spectroscopy<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\n<td width=\"373\">fNIRS2018<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4f1a\u5834<\/strong><\/td>\n<td width=\"373\">the University of Tokyo<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n<td width=\"373\">2018\/10\/5-2018\/10\/8<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n<ol>\n<li>\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n<p>2018\/10\/5\u304b\u30892018\/10\/8\u306b\u304b\u3051\u3066\uff0c\u6771\u4eac\u5927\u5b66\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305ffNIRS2018(http:\/\/fnirs2018.org\/)\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\uff0cSociety for functional Near Infrared Spectroscopy\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u305f\u7814\u7a76\u4f1a\u3067\uff0c\u6a5f\u80fd\u7684\u8fd1\u8d64\u5916\u5206\u5149\u6cd5\uff08fNIRS\uff09\u306e\u5206\u91ce\u306b\u304a\u3051\u308b\u3042\u3089\u3086\u308b\u30c8\u30d4\u30c3\u30af\u306b\u95a2\u3059\u308b\u7814\u7a76\u306b\u95a2\u5fc3\u306e\u3042\u308b\u7814\u7a76\u8005\u30fb\u533b\u5e2b\u30fb\u5b66\u751f\u304c\u53c2\u52a0\u3057\uff0cfNIRS\u306e\u53ef\u80fd\u6027\u3084\u65b9\u5411\u6027\u306b\u3064\u3044\u3066\u306e\u60c5\u5831\u4ea4\u63db\u3084\u8b70\u8ad6\u306e\u5834\u306b\u306a\u308b\u3053\u3068\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e<br \/>\n\u79c1\u306f5-8\u65e5\u306e\u5168\u65e5\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u65e5\u548c\u5148\u751f\uff0c\u6c60\u7530\uff0c\u6c34\u91ce\uff0c\u8c37\u53e3\uff0c\u5c71\u672c\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"2\">\n<li>\u7814\u7a76\u767a\u8868\n<ul>\n<li>\u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\u79c1\u306f7\u65e5\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u300cPoster\u2161\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\u5348\u524d\u3068\u5348\u5f8c1\u6642\u9593\u306e\u8a082\u6642\u9593\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e<br \/>\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u300cDetecting attentional and inattentional brain metastates based on dynamic functional connectivity analysis\u300d\u3068\u3044\u3046\u984c\u76ee\u3067\uff0c\u767a\u8868\u3092\u884c\u3044\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">Introduction: Recent studies have revealed changes in intrinsic brain organization using dynamic functional connectivity (dFC) analysis [1]. However, temporal changes in functional network topology owing to extrinsic factors have not been carefully examined. In addition, a lack of extrinsic attention sometimes leads to reduced work productivity or car accidents. It is important to quantify one\u2019s level of attention and distraction toward external stimuli in such situations. In this study, we propose a method for detecting changes in extrinsic attention using a dFC analysis and an evolutionary optimization algorithm.<br \/>\nMethods: Healthy adults (18 males, aged 22.4 \u00b1 1.0 years) participated in the study. The participants were asked to perform a psychomotor vigilance task (PVT) to induce sustained attention to external stimuli. Their brain activity was measured using a 116-channel functional near-infrared spectroscopy covering the entire brain. The measured cerebral blood flow changes were bandpass filtered, and time-varying FC matrices were calculated using a sliding-window approach and then binarized. Here, we assumed that there is a metastate that represents the characteristic network organization for each attentional and inattentional state. The metastate was modelled as a symmetric binary matrix, and its optimum structure was determined using a genetic algorithm. Metastate optimization was performed to maximize the similarity between the optimized metastate and the measured FC matrices obtained from the periods where the fastest or slowest 10% of the response times (RTs) were achieved. We assumed that the attentional and inattentional states could be observed in the fastest 10% of RTs and slowest 10% of RTs, respectively.<br \/>\nResults: The derived attentional and inattentional metastates are shown in Fig. 1 (a). In the attentional metastate, the connections around the left and right midfrontal gyrus (L\/R-MFG) were extracted as characteristic connections because MFG is involved in an interaction between the dorsal and ventral attention networks; it also plays a central role in the attention function. In the inattentional metastate, the right superior occipital gyrus (R-SOG) and the medial part of the left superior frontal gyrus (L-SFGmed) connection was extracted. The R-SOG is associated with the visual network, and the L-SFGmed is a component of the default mode network (DMN). Furthermore, a connection between the right supplementary motor area (R-SMA) and R-MFG was found in the attentional metastate\uff0cwhereas a connection between the R-SMA and L-SFGmed was found in the inattentional metastate. SMA is associated with motion control based on memory\uff0eThis suggests that the connection with SMA was altered depending on the level of attention. SMA was connected to the attention network in the attentional state and to the DMN in the inattentional state. The temporal changes in RT and the similarity between the metastate and time-varying FC matrices are shown in Figure 1(b). The similarity of the attentional state increased with the fastest 10% of RTs, and the similarity of the inattentional state was high in the case of the slowest 10% of RTs. We suggest that our proposed method can detect the attentional and inattentional state and evaluate the attention level. Even in the absence of behavioral data, such as RT, it was verified that the state of the human brain can be visualized by the occurrence rate of the metastate.<br \/>\n[1] Honey, C. J., et al. &#8220;Predicting human resting-state functional connectivity from structural connectivity.&#8221; Proceedings of the National Academy of Sciences 106.6 (2009): 2035-2040.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<ul>\n<li>\u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n<p>\u4eca\u56de\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>1<\/strong><br \/>\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\u3053\u306e\u7814\u7a76\u306e\u5c55\u671b\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u79c1\u306f\u3053\u306e\u30e1\u30bf\u72b6\u614b\u304c\u5b9a\u7fa9\u3067\u304d\u305f\u3053\u3068\u3067\uff0c\u5916\u56e0\u6027\u6ce8\u610f\u306b\u304a\u3051\u308b\u52d5\u7684\u306a\u8133\u72b6\u614b\u306e\u30ec\u30d9\u30eb\u3092\u8a55\u4fa1\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u305f\u3081\uff0c\u4ea4\u901a\u4e8b\u6545\u306e\u9632\u6b62\u3084\u4f5c\u696d\u52b9\u7387\u306e\u5411\u4e0a\u306b\u3082\u3064\u306a\u3052\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3042\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9\uff12<\/strong><br \/>\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\u4f55CH\u8a08\u6e2c\u3057\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u79c1\u306f116CH\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>3<\/strong><br \/>\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\uff0cfunctional connectivity\u3068\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u306e\u6642\u9593\u7684\u76f8\u95a2\u3068\u7b54\u3048\u307e\u3057\u305f\u304c\uff0c\u30b7\u30f3\u30af\u30ed\u30ca\u30a4\u30bc\u30fc\u30b7\u30e7\u30f3\u306e\u56f3\u3068\u306e\u95a2\u308f\u308a\u304c\u7406\u89e3\u3055\u308c\u307e\u305b\u3093\u3067\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>4<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u6ce8\u610f\u3068\u4e0d\u6ce8\u610f\u306e\u533a\u9593\u306e\u5f53\u3066\u306f\u307e\u308b\u884c\u5217\u306f\u4f55\u679a\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u30662\u679a\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>5<\/strong><br \/>\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\u524d\u51e6\u7406\u306f\u4f55\u3092\u884c\u3063\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u30d0\u30f3\u30c9\u30d1\u30b9\u30d5\u30a3\u30eb\u30bf\u3092\u7528\u3044\u3066\u30ce\u30a4\u30ba\u9664\u53bb\u3092\u884c\u3063\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>6<\/strong><br \/>\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\uff0cRT\u3068windowsize\u306b\u5dee\u304c\u3042\u308b\u304c\u554f\u984c\u306a\u3044\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u523a\u6fc0\u5448\u793a\u6642\u9593\u306e\u72b6\u614b\u3092\u6700\u3082\u53cd\u6620\u3059\u308b\u884c\u5217\u3092\u63a1\u7528\u3057\uff0c\u307e\u305f\uff0cSWC\u3092\u8a08\u7b97\u3059\u308b\u306e\u306b\u5fc5\u8981\u306a\u30b5\u30f3\u30d7\u30eb\u6570\u3092\u8003\u616e\u3057\u305fwindowsize\u306b\u306a\u3063\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u6bce\u5b66\u4f1a\u3067windowsize\u306b\u3064\u3044\u3066\u306f\u8cea\u554f\u3055\u308c\uff0c\u305d\u306e\u305f\u3073\u89e3\u6c7a\u3067\u304d\u3066\u3044\u306a\u3044\u3053\u3068\u306b\u3082\u3069\u304b\u3057\u3055\u3092\u611f\u3058\u308b\u306e\u3067\u4fee\u58eb\u8ad6\u6587\u3067\u306fwindowsize\u306e\u30b5\u30a4\u30ba\u306e\u691c\u8a0e\u307e\u3067\u884c\u3044\u305f\u3044\u3068\u601d\u3063\u3066\u3044\u307e\u3059\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>7<\/strong><br \/>\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\uff0cRTfast10%\u3068RTslow10%\u306e\u5024\u306f\u5177\u4f53\u7684\u306b\u3069\u308c\u304f\u3089\u3044\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u88ab\u9a13\u8005\u306b\u3088\u3063\u3066\u3070\u3089\u3064\u304f\u304c\uff0c\u30dd\u30b9\u30bf\u30fc\u3067\u767a\u8868\u3057\u3066\u3044\u308bfast10%\u306f0.6-0.8[s],slow10%\u306f0.1-0.3[s]\u3068\u7b54\u3048\u307e\u3057\u305f.\u88ab\u9a13\u8005\u3067\u5024\u304c\u7570\u306a\u308b\u3053\u3068\u306b\u5bfe\u3057\u3066\u6307\u6458\u3092\u53d7\u3051\u305f\u305f\u3081\uff0c\u3053\u306e\u7814\u7a76\u3067\u306f\uff0c\u5404\u88ab\u9a13\u8005\u306b\u6ce8\u610f\u4e0d\u6ce8\u610f\u306e2\u72b6\u614b\u304c\u3042\u308b\u3068\u4eee\u5b9a\u3057\u3066\u3044\u308b\u305f\u3081\u554f\u984c\u306a\u3044\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>8<\/strong><br \/>\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\uff0cattention metastate\u3068inattention metastate\u3067\u691c\u5b9a\u3092\u884c\u3063\u3066\u3044\u308b\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u884c\u3063\u3066\u3044\u306a\u3044\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>9<\/strong><br \/>\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\uff0cPVT\u306f\u3069\u306e\u3088\u3046\u306a\u72b6\u614b\u3092\u8a08\u6e2c\u3057\u305f\u3044\u3068\u304d\u306b\u7528\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u6ce8\u610f\u306e\u6301\u7d9a\u3092\u4fc3\u3057\u305f\u3044\u3068\u304d\u306b\u884c\u3046\u8ab2\u984c\u3067\u3042\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>10<\/strong><br \/>\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\uff0cattention metastate\u3068inattention metastate\u3092\u3069\u306e\u3088\u3046\u306b\u4f5c\u6210\u3057\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u5404\u88ab\u9a13\u8005\u306e\u6ce8\u610f\uff0c\u4e0d\u6ce8\u610f\u533a\u9593\u3067\u306e\u884c\u5217\u3068\u6700\u9069\u5316\u3055\u308c\u305f\u884c\u5217\u306e\u985e\u4f3c\u5ea6\u304c\u6700\u5927\u306b\u306a\u308b\u3088\u3046\u306b\u6700\u9069\u306a\u30e1\u30bf\u72b6\u614b\u3092\u691c\u51fa\u3057\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>11<\/strong><br \/>\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\u523a\u6fc0\u306f1\u3064\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c1\u3064\u3067\u3042\u308b\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>12<\/strong><br \/>\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\u300cr\u300d\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0cRT\u3068occurrence\u306e\u76f8\u95a2\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>13<\/strong><br \/>\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\uff0cPVT\u306f\u4f55\u5206\u9593\u884c\u3063\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u306610\u5206\u9593\u3068\u7b54\u3048\u307e\u3057\u305f\uff0e<\/p>\n<ul>\n<li>\u611f\u60f3<\/li>\n<\/ul>\n<p>educational course\u306b\u53c2\u52a0\u3057\uff0cNIRS\u306e\u57fa\u790e\u7684\u306a\u90e8\u5206\u3092\u5b66\u3076\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u57fa\u790e\u7684\u306a\u5185\u5bb9\u3092\u3082\u3046\u4e00\u5ea6\u805e\u304f\u3053\u3068\u306b\u3088\u3063\u3066\uff0c\u4f55\u304c\u3042\u3044\u307e\u3044\u306b\u306a\u3063\u3066\u3044\u308b\u306e\u304b\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u78ba\u7387\u7684\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u6cd5\u306e\u539f\u7406\u3084\u8a08\u6e2c\u65b9\u6cd5\u306b\u95a2\u3057\u3066\u306f\u898b\u76f4\u3059\u5fc5\u8981\u304c\u3042\u308b\u3068\u611f\u3058\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u306f\uff0c\u69d8\u3005\u306a\u30d0\u30c3\u30af\u30b0\u30e9\u30a6\u30f3\u30c9\u3092\u6301\u3063\u305f\u65b9\u3005\u306b\u7814\u7a76\u3092\u8aac\u660e\u3059\u308b\u6a5f\u4f1a\u304c\u3042\u308a\u5927\u5909\u6709\u610f\u7fa9\u306a\u6642\u9593\u306b\u306a\u308a\u307e\u3057\u305f\uff0eGA\u306e\u8aac\u660e\u90e8\u5206\u3092\u5897\u3084\u3057\uff0c\u539f\u7406\u3092\u7406\u89e3\u3067\u304d\u305f\u3053\u3068\u304c\u524d\u56de\u304b\u3089\u306e\u6210\u9577\u3060\u3068\u601d\u3063\u3066\u3044\u307e\u3059\uff0e\u305f\u3060\uff0c\u82f1\u8a9e\u3067\u8cea\u554f\u3055\u308c\u305f\u6642\u306b\u82f1\u8a9e\u3067\u7b54\u3048\u308b\u3053\u3068\u304c\u51fa\u6765\u306a\u304b\u3063\u305f\u306e\u3067\u4fee\u58eb\u8ad6\u6587\u307e\u3067\u306b\u8aac\u660e\u3067\u304d\u308b\u3088\u3046\u306b\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e\u307e\u305f\uff0c\u4fee\u58eb\u8ad6\u6587\u306b\u5411\u3051\u3066\uff0c\u518d\u5ea6\u8ab2\u984c\u3092\u6d17\u3044\u51fa\u3057\uff0c\u76ee\u6a19\u3092\u6301\u3063\u3066\u7814\u7a76\u3092\u9032\u3081\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"3\">\n<li>\u8074\u8b1b<\/li>\n<\/ol>\n<p>\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Dynamics of Functional Networks in the Developing Brain<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Fumitaka Homae<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Neonatal, pediatric &amp; developmental neuroscience I<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Introduction: Structural and functional organization of the brain occurs rapidly in early infancy. Previous studies report that in neonates and young infants, this neural organization is sensitive to speech sounds, and related functions in distinct brain regions have been partially elucidated (Homae et al., 2014). It is known that short speech sounds induce eventrelated activation in the temporal brain regions in young infants; increases in oxygenated hemoglobin (oxy-Hb) signals are followed by signal decreases to the onset level within a 10- to 20-second time scale. We can also visualize the static aspects of functional relationships, such as correlations between spontaneous activations in homologous regions (Homae et al.,2010). However, we have limited information on the dynamics of cortico-cortical interactions during the presentation of speech sounds to infants. In the present study, we calculated the dynamic functional connectivity (dFC) of cortical activation in neonates and 3- and 6-monthold infants in response to short sentences in Japanese. We hypothesized that functional relationships will not be constant, but will instead be modulated, during typical cortical hemodynamic responses to speech sounds. We further predicted that functional connectivity between distant cortical regions would change from a local to a global state depending on the stage of development.<br \/>\nMethods: We analyzed data obtained from quietly sleeping neonates (N = 28) and 3- and 6- month-old infants (N = 26 and 27, respectively). We presented auditory sentences while measuring brain activation using 94-channel fNIRS (ETG-7000, Hitachi). The continuous oxy-Hb signals were band-pass filtered from 0.01 to 0.2 Hz. The signal changes in response to speech sounds were examined by averaging the signals over segmented data blocks. We applied the Hilbert transform to the continuous data to estimate the phase of the signals in all channels. We defined dFC using the following equation (Cabral et al., 2017):<br \/>\nResults and Discussion: We found that the frontal and temporal regions in all participant groups demonstrated increases in oxy-Hb signals when the sentences were presented. In addition, 3- and 6-month-old infants exhibited similar changes in the occipital regions, as in our previous studies (Homae et al., 2011; Taga et al., 2018). The dFC between homologous regions increased with age, consistent with our previous findings (Homae et al., 2010). Although frontal regions exhibit dense clusters in all groups, clusters over the temporal, parietal, and occipital regions were observed only in 3- and 6-month-old infants. Overall, we found that the dFC between the frontal and temporal regions changed with the presentation of speech sounds, and the organization of functional networks depended on age. These results support our hypotheses and suggest that the dynamics of functional networks will help in revealing how infants hear speech sounds and acquire their native language.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u65b0\u751f\u5150\u3068\u4e73\u5e7c\u5150\u306b\u304a\u3051\u308b\u52d5\u7684\u6a5f\u80fd\u7684\u7d50\u5408\u89e3\u6790\u306e\u7814\u7a76\u3067\u3057\u305f\uff0edFC\u306e\u7814\u7a76\u3067\uff0cSWC\u3067\u306f\u306a\u3044\u624b\u6cd5\u3092\u7528\u3044\u3066\u304a\u308a\uff0cdFC\u306e\u7814\u7a76\u3068\u3057\u3066\u62bc\u3055\u3048\u3066\u304a\u304b\u306a\u3051\u308c\u3070\u3044\u3051\u306a\u3044\u3068\u611f\u3058\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aFunctional Connectivity Patterns in Monolingual and Bilingual Infants<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a B. Blanco, M. Molnar, E. Amico, M. Carreiras and C. Caballero-Gaudes<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Neonatal, pediatric &amp; developmental neuroscience I<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aIntroduction. In this work we evaluated whether brain adaptations are induced by the effect of an\u3000early and continued exposure to a bilingual vs. a monolingual environment by testing between\u3000group differences in resting state functional connectivity (RSFC). We also assessed the reliability\u3000of our previous results by testing sleeping, as opposed to awake infants, in order to maximize\u3000signal quality. Methods. Spontaneous hemodynamic activity was recorded (9 min.) using nearinfrared\u3000spectroscopy (NIRS) in 4-month-old infants (n=27 bilinguals, n=25 Spanish and n=26\u3000Basque monolinguals). Within each group we measured the antiphase relationship between\u3000deoxy- (HbR) and oxyhemoglobin (HbO2), and perform a hierarchical spatio-temporal clustering.\u3000Network based statistics (NBS) (Zalesky et al., 2010)\u3000and connICA (Amico et al., 2017) procedures were also\u3000employed to explore differences in functional connectivity\u3000patterns between groups. Results and Discussion. In our\u3000three experimental groups we observed an antiphase\u3000relationship between HbR and HbO2 (Fig. 1A) which\u3000resembles the results of Watanabe et al., (2017). The\u3000spatial configuration of clusters (Fig. 1B) across groups\u3000also demonstrates a high degree of consistency with\u3000previously reported results (Homae et al., 2010). These\u3000results were not replicated in our previous study in\u3000awake infants. We assume that our previously reported\u3000effects were probably caused by motion artifacts in the\u3000signal, and recognize the importance of correct data\u3000quality assessment in NIRS studies with infants to avoid\u3000this type of spurious results. Pairwise comparisons with\u3000NBS revealed a network (Fig. 1C) involving spatially\u3000homologous channels of both hemispheres showing\u3000stronger synchronization in Spanish monolingual infants\u3000than in Basque monolingual infants (p=0.04). The same\u3000difference between groups is also observed in HbO2\u3000(p=0.04) in a network showing a similar spatial disposition. ConnICA revealed a FC pattern (Fig.1C) showing a significantly larger presence in Spanish than in Basque monolingual infants, in\u3000HbR (p=0.04) and HbO2 (p=0.04), which resembles the results obtained with NBS. Despite their\u3000small effect, the observed between group differences are consistent across HbR and HbO2, and\u3000show a similar spatial pattern regardless of the procedure being employed.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u4f11\u6b62\u72b6\u614b\u6a5f\u80fd\u7684\u63a5\u7d9a\u6027\u306b\u304a\u3051\u308b\u7fa4\u9593\u306e\u5dee\u7570\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3057\u305f\uff0eNIRS\u30c7\u30fc\u30bf\u3092\u7528\u3044\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u89e3\u6790\u3067\uff0c\u30aa\u30ad\u30b7\u30fb\u30c7\u30aa\u30ad\u30b7\u3092\u7528\u3044\u3066\u89e3\u6790\u3092\u884c\u3063\u3066\u304a\u308a\uff0cNBS\uff0cCOnnICA\u306a\u3069\u65b0\u3057\u3044\u3053\u3068\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3053\u306e\u7814\u7a76\u3067\u306f\uff0c\u884c\u5217\u304c\u9818\u57df\u3067\u793a\u3055\u308c\u3066\u3044\u305f\u70b9\uff0cGrobal signal regression\uff0crobust independent FC pattern\u306a\u3069\u30dd\u30a4\u30f3\u30c8\u3068\u306a\u308b\u70b9\u306f\u4fee\u58eb\u8ad6\u6587\u307e\u3067\u306b\u304a\u3055\u3048\u305f\u3044\u3067\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aAdvanced topics in fNIRS data analysis : Motion Artifact Detection and Correction<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aMeryem A. Y\u00fccel<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Morning tutorial I<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Functional near-infrared spectroscopy (fNIRS) is a relatively new brain imaging technology. fNIRS allows measurements in relatively unrestrained environments. While this allows its adaptation to populations\/studies where other modalities are difficult or impossible to implement such as infants, children, speech studies, gait studies, movement disorders or neuro-intensive care, the resultant fNIRS signal often contain motion artifacts. In this lecture we will go over motion artifact detection and correction in detail. Particularly, we will go over several commonly-used motion artifact correction algorithms and will discuss advantages and disadvantages of each comparatively.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u30e2\u30fc\u30b7\u30e7\u30f3\u30a2\u30fc\u30c1\u30d5\u30a1\u30af\u30c8\u306b\u95a2\u3059\u308b\u7814\u7a76\u3067\u3057\u305f\uff0ePCA,Wavelet\u306a\u3069\u65e2\u5b58\u306e\u77e5\u8b58\u306e\u4ed6\u306b\uff0cSokine\uff0cCBSI\u306a\u3069\u306e\u65b0\u305f\u306a\u77e5\u898b\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aNeuroDOT: an extensible Matlab toolbox for streamlined optical brain mapping<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aA.T. Eggebrechta, D. Muccigrosso, J.P. Culver<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Data analysis &amp; algorithms<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Multiple challenges exist in standardization of data format and processing pipelines for optical neuroimaging. The goal of this project is to provide a fully self-contained and enduser-friendly workflow that seamlessly integrates with a wide variety of other data processing toolboxes and contains dedicated functions and pipelines for preprocessing, anatomical light modeling, reconstruction, post-processing analyses, and visualization. To meet these goals, we present a tool that provides the flexibility to be used by multiple array-based imaging modalities, format compatibility, spatial registration, ease of use, and analytical breadth and sophistication for post-processing. NeuroDOT is written in MATLAB in the style of a conventional MATLAB toolbox. Its functionality is distributed among several pipelines (Fig. 1), with extensive functions for data quality analysis and visualization. To aid in end-user support at multiple levels of familiarity and expertise, beyond the basic functionality, NeuroDOT contains data samples, support files, help sections, appendices, and tutorials. Specifically, a set of anonymized and published data samples have been chosen to reflect common experimental paradigms in neuroimaging (e.g., retinotopy and language based tasks), and are provided in both raw and pre-processed versions to aid in troubleshooting and training for the new user. The extensive support files \u2013 all stored as .matfiles &#8211; contain geometric information for some of our diffuse optical tomography caps, sensitivity matrices, spectroscopy matrices, and standard atlases. Together with the documentation, these files provide a blueprint for users to create counterparts for their own systems. The NeuroDOT toolbox currently supports a wide variety of standard data file formats (e.g., NIFTI, GIFTI, and others). Help sections exist for each function and are searchable from the MATLAB command line, with a Help Viewer version as well. Both are written and formatted in the style of their native MATLAB counterparts for familiarity and ease of use. Several appendices detail data structures, pipelines and their construction, and select visualizations of our pipelines\u2019 results for multiple data samples. Several tutorials are also included, each of which runs a data sample through a given pipeline to help the user harness the power and flexibility of NeuroDOT.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>NIRS\u30c7\u30fc\u30bf\u3092\u51e6\u7406\u3059\u308b\u30c4\u30fc\u30eb\u30dc\u30c3\u30af\u30b9\u306e\u7d39\u4ecb\u304c\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0eHOMER2,AFNI,freesurfer,NueroDOT\u306a\u3069\uff0c\u4f7f\u7528\u3057\u305f\u3053\u3068\u306e\u306a\u3044\u30c4\u30fc\u30eb\u30dc\u30c3\u30af\u30b9\u304c\u305f\u304f\u3055\u3093\u3042\u308b\u3053\u3068\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0eNIRS\u30c7\u30fc\u30bf\u306e\u524d\u51e6\u7406\u3084\u57fa\u672c\u7684\u306a\u8003\u3048\u65b9\u3092\u3053\u3046\u3044\u3063\u305f\u30c4\u30fc\u30eb\u30dc\u30c3\u30af\u30b9\u3067\u3082\u5b66\u3079\u308b\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u611f\u3058\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n\u53c2\u8003\u6587\u732e<\/p>\n<ul>\n<li>fNIRS2018, <a href=\"http:\/\/fnirs2018.org\/\">http:\/\/fnirs2018.org\/<\/a><\/li>\n<\/ul>\n<p><strong>\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"147\"><strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n<td width=\"373\">\u6c60\u7530\u5e78\u6a39<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">fNIRS\u3092\u7528\u3044\u305f\u8133\u6a5f\u80fd\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u304a\u3051\u308b\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\u8ca0\u8377\u91cf\u4f9d\u5b58\u5909\u5316\u306e\u89e3\u6790<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">Analysis of working memory-load dependent changes in functional network properties using fNIRS<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8457\u8005<\/strong><\/td>\n<td width=\"373\">\u6c60\u7530\u5e78\u6a39\uff0c\u65e5\u548c\u609f\uff0c\u5ee3\u5b89\u77e5\u4e4b<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4e3b\u50ac<\/strong><\/td>\n<td width=\"373\">\u533b\u7642\u60c5\u5831\u30b7\u30b9\u30c6\u30e0\u7814\u7a76\u5ba4<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\n<td width=\"373\"><strong>Neurophotonics<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4f1a\u5834<\/strong><\/td>\n<td width=\"373\">Hongo Campus of The University of Tokyo, Tokyo, Japan<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n<td width=\"373\">2018\/10\/05-2018\/10\/08<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n<ol>\n<li>\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u304b\u3051\u3066\uff0c\u6771\u4eac\u5927\u5b66\u672c\u90f7\u30ad\u30e3\u30f3\u30d1\u30b9\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305ffNIRS2018\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0eThe Society for functional near-infrared spectroscopy \uff08SfNIRS\uff09\u306f\uff0c\u5149\u5b66\u7684\u65b9\u6cd5\u3092\u7528\u3044\u3066\u751f\u7269\u7d44\u7e54\uff0c\u7279\u306b\u8133\u306e\u6a5f\u80fd\u7684\u7279\u6027\u306e\u7406\u89e3\u3092\u6df1\u3081\u308b\u57fa\u790e\u79d1\u5b66\u8005\u304a\u3088\u3073\u81e8\u5e8a\u79d1\u5b66\u8005\u306e\u7d44\u7e54\u3067\uff0c \u672c\u5b66\u4f1a\u306f\u30a2\u30a4\u30c7\u30a2\u306e\u4ea4\u63db\uff0c\u5b66\u969b\u7684\u5354\u529b\uff0c\u6559\u80b2\u306e\u4fc3\u9032\u3092\u76ee\u7684\u3068\u3057\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\uff0e\u79c1\u306f\u5168\u65e5\u7a0b\u53c2\u52a0\u3057\uff0c\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u65e5\u548c\u5148\u751f\uff0c\u6c34\u91ce\u3055\u3093\uff0c\u897f\u6fa4\u3055\u3093\uff0c\u8c37\u53e3\u3055\u3093\uff0c\u5c71\u672c\u3055\u3093\u304c\u53c2\u52a0\u3055\u308c\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"2\">\n<li>\u7814\u7a76\u767a\u8868\n<ul>\n<li>\u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\u79c1\u306f10\u670808\u65e5\u306e\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\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c\u8cbc\u308a\u51fa\u3057\u671f\u9593\u306f1\u65e5\u9593\uff0c\u30bb\u30c3\u30b7\u30e7\u30f3\u6642\u9593\u306f\u5348\u524d1\u6642\u9593\uff0c\u5348\u5f8c1\u6642\u9593\u306e\u8a082\u6642\u9593\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e<br \/>\n\u4eca\u56de\u306e\u767a\u8868\u306b\u3064\u3044\u3066\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"593\">\u306f\u3058\u3081\u306b\uff1a\u30ef\u30fc\u30ad\u30f3\u30b0\u30e1\u30e2\u30ea\uff08WM\uff09\u306f\uff0c\u60c5\u5831\u306e\u540c\u6642\u51e6\u7406\u3068\u4fdd\u5b58\u306e\u305f\u3081\u306e\u8a8d\u77e5\u30b7\u30b9\u30c6\u30e0\u3067\u3042\u308b[1]\uff0e\u672c\u8ad6\u6587\u3067\u306f\uff0cfNIRS\u306b\u3088\u308a\u6e2c\u5b9a\u3055\u308c\u305fN-back\u30bf\u30b9\u30af\u4e2d\u306e\u8133\u6d3b\u52d5\u306b\u3064\u3044\u3066\uff0c\u30b0\u30e9\u30d5\u7406\u8ad6\u89e3\u6790\u306b\u3088\u308a\u6a5f\u80fd\u7684\u30b3\u30cd\u30af\u30ec\u30a3\u30d3\u30c6\u30a3\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u304a\u3051\u308bWM\u8ca0\u8377\u91cf\u4f9d\u5b58\u5909\u5316\u3092\u8abf\u3079\u305f\uff0e\u65b9\u6cd5\uff1aN-back\u30bf\u30b9\u30af\uff08N = 1,2,3\uff09\u4e2d\u306e6\u4eba\u306e\u5065\u5eb7\u306a\u88ab\u9a13\u8005\uff08\u7537\u60276\u4eba\uff0c23\u00b11.2\u4eba\uff09\u306e\u8133\u8840\u6d41\u5909\u5316\u3092\uff0c116\u30c1\u30e3\u30cd\u30ebfNIRS\uff08ETG-7100\uff0cHitachi\uff0cLtd. \uff09\u3092\u7528\u3044\u3066\u8a08\u6e2c\u3057\u305f\uff0e fNIRS\u306e\u5168\u6e2c\u5b9a\u30c1\u30e3\u30cd\u30eb\u306f\uff0cAutomated Anatomical Labeling\uff08AAL\uff09\u306b\u57fa\u3065\u304f\u8133\u9818\u57df\u3068\u95a2\u9023\u3057\u3066\u3044\u305f\uff0e N-back\u30bf\u30b9\u30af\u4e2d\u306e\u5168\u8133\u9818\u57df\u9593\u306e\u6a5f\u80fd\u7684\u63a5\u7d9a\u6027\u3092\u793a\u3059\u76f8\u95a2\u4fc2\u6570\u884c\u5217\u3092\u8a08\u7b97\u3057\uff0c\u6b21\u306b\u30a8\u30c3\u30b8\u5bc6\u5ea6\u309230\uff05\u306b\u4fdd\u3064\u3088\u3046\u306b\u4e8c\u5024\u5316\u3057\u305f\uff0e\u30b0\u30e9\u30d5\u7406\u8ad6\u7279\u5fb4\u91cf\u3067\u3042\u308b\uff0cdegree\uff0cclustering coefficient\uff0cbetweenness centrality\uff0ceigenvector centrality\uff0cmodularity\uff0cparticipation coefficient\uff0cwithin-module degree z-score\u306f\uff0cBrain Connectivity Toolbox\u3092\u4f7f\u7528\u3057\u3066\u8a08\u7b97\u3055\u308c\u305f\uff0e\u5404\u30b0\u30e9\u30d5\u7406\u8ad6\u7279\u5fb4\u91cf\u3068WM\u8ca0\u8377\u3068\u306e\u30d4\u30a2\u30bd\u30f3\u76f8\u95a2\u3092\u5206\u6790\u3057\u305f\uff0e\u7d50\u679c\uff1a\u5de6\u4e0a\u5f8c\u982d\u90e8\u56de\uff08SOG\uff09\u306eclustering coefficient\u306f\uff0cWM\u8ca0\u8377\u3068\u6b63\u306e\u76f8\u95a2\u304c\u3042\u3063\u305f\uff08r = 0.53\uff0cp &lt;0.05\uff09\uff0e\u5de6\u4e0a\u524d\u982d\u56de\u5185\u5074\u90e8\uff08SFGmed\uff09\u306eparticipation coefficient\u3082\u307e\u305f\u6b63\u306e\u76f8\u95a2\u304c\u3042\u3063\u305f\uff08r = 0.50\uff0cp &lt;0.05\uff09\uff0e\u307e\u305f\uff0c\u5de6\u4e2d\u5fc3\u524d\u56de\uff08PreCG\uff09\u306edegree\uff0ceigenvector centrality\u304a\u3088\u3073within-module degree z-score\u306f\uff0cWM\u8ca0\u8377\u3068\u8ca0\u306e\u76f8\u95a2\u304c\u3042\u3063\u305f\uff08r = -0.59\uff0c-0.57\uff0c-0.49\uff0cp &lt;0.05\uff09\uff0e\u5de6\u4e2d\u5fc3\u524d\u56de\u5468\u8fba\u306e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u69cb\u9020\u3092\u56f31\u306b\u793a\u3059\uff0e \u4e0a\u524d\u982d\u56de\u5185\u5074\u90e8\u3068\u4e2d\u5fc3\u524d\u56de\u306fWM\u30d7\u30ed\u30bb\u30b9[2,3]\u306b\u95a2\u4e0e\u3057\u3066\u3044\u308b\u305f\u3081\uff0c\u3053\u308c\u3089\u306e\u9818\u57df\u306fWM\u8ca0\u8377\u91cf\u5909\u5316\u306e\u7279\u5fb4\u91cf\u3068\u3057\u3066\u5229\u7528\u53ef\u80fd\u3067\u3042\u308b\uff0e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<ul>\n<li>\u8cea\u7591\u5fdc\u7b54\u30fb\u610f\u898b<\/li>\n<\/ul>\n<p>\u4eca\u56de\u306e\u8b1b\u6f14\u767a\u8868\u3067\u306f\uff0c\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8cea\u7591\u30fb\u610f\u898b\u3092\u53d7\u3051\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u7591\u5fdc\u7b541<\/strong><br \/>\n<strong>\u3000<\/strong>Q. \u300cedge density\u300d\u3068\u306f\u3069\u3046\u3044\u3046\u610f\u5473\u304b\uff1f<br \/>\nA. \u30a8\u30c3\u30b8\u306e\u672c\u6570\u3092\u7d50\u5408\u53ef\u80fd\u306a\u30a8\u30c3\u30b8\u306e\u7dcf\u6570\u3067\u5272\u3063\u305f\u3082\u306e\uff0c<br \/>\n\u3059\u3079\u3066\u306e\u88ab\u9a13\u8005\u3067\u30a8\u30c3\u30b8\u306e\u672c\u6570\u304c\u540c\u3058\u306b\u306a\u308b\u3088\u3046\u306b\u3059\u308b\u3053\u3068<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u7591\u5fdc\u7b542<\/strong><br \/>\n<strong>\u3000<\/strong>Q. \u300cfeature values\u300d\u306f\u3069\u3046\u3084\u3063\u3066\u7b97\u51fa\u3057\u3066\u3044\u308b\u306e\u304b\uff1f<br \/>\n<strong>\u00a0<\/strong><strong>\u3000<\/strong>A. MATLAB\u306eBrain Connectivity Toolbox\uff08BCT\uff09\u3092\u7528\u3044\u3066\u7b97\u51fa\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u7591\u5fdc\u7b543<\/strong><br \/>\n<strong>\u3000<\/strong>Q. \u6210\u7e3e\u3068\u7279\u5fb4\u91cf\u306e\u76f8\u95a2\u306f\u3042\u3063\u305f\u306e\u304b\uff1f<br \/>\n<strong>\u00a0<\/strong><strong>\u3000<\/strong>A. \u306a\u304b\u3063\u305f<br \/>\nWM-load\u306f\u88ab\u9a13\u8005\u306b\u3088\u3063\u3066\u7570\u306a\u308b\u305f\u3081\u5b9f\u969b\u306e\u6210\u7e3e\u3067\u306f\u8a55\u4fa1\u3067\u304d\u306a\u3044\u305f\u3081<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u7591\u5fdc\u7b544<\/strong><br \/>\n<strong>\u3000<\/strong>Q. \u306a\u305c\u4ed6\u306e\u7279\u5fb4\u91cf\u306f\u307f\u3066\u3044\u306a\u3044\u306e\u304b\uff1f<br \/>\n<strong>\u00a0<\/strong><strong>\u3000<\/strong>A. \u3059\u3079\u3066\u898b\u3066\uff0c2-back\u3067\u9055\u3046\u50be\u5411\u304c\u3042\u308a\uff0c<br \/>\n\u305d\u306e\u4e2d\u3067\u3082\u9855\u8457\u306b\u305d\u306e\u50be\u5411\u304c\u8868\u308c\u3066\u3044\u305f\u7279\u5fb4\u91cf2\u3064\u3092\u30d4\u30c3\u30af\u30a2\u30c3\u30d7\u3057\u3066\u7d50\u679c\u306b\u8f09\u305b\u3066\u3044\u308b<br \/>\n<strong>\u30fb\u610f\u898b1<\/strong><br \/>\n\u300cquadrant\u300d\u306e\u610f\u5473\u304c\u4f1d\u308f\u3089\u305a4\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u610f\u5473\u304c\u5206\u304b\u308a\u306b\u304f\u304b\u3063\u305f<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u610f\u898b2<\/strong><br \/>\nN\u6570\u3092\u3082\u3063\u3068\u5897\u3084\u3057\u305f\u3089\u6210\u7e3e\u3068\u306e\u76f8\u95a2\u3082\u898b\u3089\u308c\u308b\u306e\u3067\u306f<br \/>\n&nbsp;<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u610f\u898b3<\/strong><br \/>\n2\u7fa4\u306b\u5225\u308c\u308b\u306e\u306f\u81ea\u7136\u306a\u3053\u3068\u306a\u306e\u3067\uff0c\u6210\u7e3e\u3084RT\u306a\u3069\u3068\u76f8\u95a2\u304c\u3042\u308c\u3070\u9762\u767d\u3044<br \/>\n&nbsp;<\/p>\n<ul>\n<li>\u611f\u60f3<\/li>\n<\/ul>\n<p>\u672c\u5b66\u4f1a\u3067\u306e\u79c1\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\uff0c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u89e3\u6790\u81ea\u4f53\u3082\u5c11\u306a\u304f\u30b0\u30e9\u30d5\u7406\u8ad6\u306b\u5f53\u3066\u306f\u3081\u3066\u89e3\u6790\u3057\u3066\u3044\u308b\u4eba\u304c\u307b\u3068\u3093\u3069\u3044\u306a\u304b\u3063\u305f\u306e\u3067\uff0c\u305d\u306e\u3042\u305f\u308a\u306e\u8cea\u554f\u304c\u3068\u3066\u3082\u591a\u304b\u3063\u305f\u3067\u3059\uff0e\u767a\u8868\u524d\u304b\u3089\u4e0d\u5b89\u3067\u3057\u305f\u304c\uff0c4\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u5206\u3051\u308b\u8a71\u304c\u306a\u304b\u306a\u304b\u7406\u89e3\u3057\u3066\u3082\u3089\u3048\u305a\u96e3\u3057\u304b\u3063\u305f\u3067\u3059\uff0e\u3057\u304b\u3057\uff0c\u5348\u524d\u30fb\u5348\u5f8c\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u3068\u3082\u591a\u304f\u306e\u4eba\u304c\u767a\u8868\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u304f\u308c\u3066\u5e38\u306b\u8ab0\u304b\u3068\u8a71\u3057\u3066\u3044\u308b\u72b6\u6cc1\u3067\uff0c\u6709\u610f\u7fa9\u306a\u6642\u9593\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u524d\u56de\u306e\u56fd\u969b\u5b66\u4f1a\u306b\u53c2\u52a0\u3057\u305f\u969b\u306b\u8ab2\u984c\u3060\u3068\u611f\u3058\u3066\u3044\u305f\u7814\u7a76\u3078\u306e\u7406\u89e3\u5ea6\u306f\u78ba\u5b9f\u306b\u4e0a\u304c\u3063\u3066\u3044\u305f\u305f\u3081\uff0c\u81ea\u4fe1\u3092\u6301\u3063\u3066\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u82f1\u8a9e\u80fd\u529b\u306b\u95a2\u3057\u3066\u306f\uff0c\u8cea\u554f\u306e\u610f\u5473\u306a\u3069\u306f\u7406\u89e3\u3067\u304d\u308b\u3082\u306e\u306e\u30dc\u30ad\u30e3\u30d6\u30e9\u30ea\u30fc\u306e\u5c11\u306a\u3055\u3082\u3042\u308a\u601d\u3063\u305f\u3088\u3046\u306b\u4f1d\u308f\u3089\u306a\u3044\u5834\u9762\u304c\u591a\u3005\u3042\u308a\u307e\u3057\u305f\u304c\uff0c\u4e00\u751f\u61f8\u547d\u805e\u3044\u3066\u304f\u3060\u3055\u308b\u4eba\u304c\u591a\u304f\u9811\u5f35\u3063\u3066\u8a71\u305b\u305f\u3068\u611f\u3058\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"3\">\n<li>\u8074\u8b1b<\/li>\n<\/ol>\n<p>\u4eca\u56de\u306e\u5b66\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e4\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"593\"><strong>\u767a\u8868\u30bf\u30a4\u30c8\u30eb<\/strong>\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Comparison of source localization techniques in Diffuse Optical Tomography for fNIRS application using a realistic head model<br \/>\n<strong>\u8457\u8005<\/strong>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a J. Tremblaya , E. Martinez-Montesb , P. Vannasinga , D.K. Nguyend , M. Sawane , F. Leporec , M. Lassondec , A. Gallaghera,c<br \/>\n<strong>\u30bb\u30c3\u30b7\u30e7\u30f3\u540d<\/strong>\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster Session<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a<br \/>\n\u80cc\u666f\uff1a\u6162\u6027\u9589\u585e\u6027\u80ba\u75be\u60a3\uff08COPD\uff09\u306f\u6b7b\u4ea1\u539f\u56e0\u306e\u7b2c4\u4f4d\u3067\u3042\u308a\uff0c2010\u5e74\u306b\u306f500\u5104\u7c73\u30c9\u30eb\u306e\u533b\u7642\u95a2\u9023\u8ca0\u62c5\u304c\u3042\u3063\u305f\uff0e\u6ce8\u610f\u5236\u5fa1\uff0c\u8a08\u753b\uff0c\u610f\u601d\u6c7a\u5b9a\u306b\u95a2\u308f\u308b\u524d\u982d\u524d\u91ce\uff08PFC\uff09\u306e\u5909\u5316\u306f\uff0cCOPD\u60a3\u8005\u306b\u304a\u3051\u308b\u8a8d\u77e5\u969c\u5bb3\u304a\u3088\u3073\u904b\u52d5\u969c\u5bb3\u304c\u542b\u307e\u308c\u308b\uff0efNIRS\u306f\uff0c\u9178\u7d20\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\uff08O2Hb\uff09\u3092\u4ecb\u3057\u3066\u76ae\u8cea\u795e\u7d4c\u6d3b\u52d5\u3092\u5b9a\u91cf\u5316\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3042\u308a\uff0c\u4e2d\u592e\u51e6\u7406\u3068\u904b\u52d5\u6027\u80fd\u3068\u306e\u9593\u306e\u3064\u306a\u304c\u308a\u3092\u628a\u63e1\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u306a\u65b0\u898f\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u6280\u8853\u3067\u3042\u308b\uff0e<br \/>\n\u76ee\u7684\uff1a COPD\u60a3\u8005\uff0c\u5065\u5e38\u306a\u82e5\u5e74\u8005\u304a\u3088\u3073\u9ad8\u9f62\u8005\u306ePFC O2Hb\u306e\u76f8\u5bfe\u7684\u5909\u5316\uff0c\u5f8c\u65b9\u30b9\u30da\u30ea\u30f3\u30b0\u306e\u6b63\u78ba\u3055\uff0c\u304a\u3088\u3073\u5358\u4e00\u304a\u3088\u3073\u4e8c\u91cd\u306e\u4f5c\u696d\u4e2d\u306e\u6b69\u884c\u306e\u6e1b\u5c11\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\uff0e<br \/>\n\u4eee\u8aac\uff1aH1\uff1aPFC O2Hb\u306f\uff0c\u30d9\u30fc\u30b9\u30e9\u30a4\u30f3\u8ab2\u984c\u3068\u6bd4\u8f03\u3057\u3066\u5f8c\u65b9\u30b9\u30da\u30ea\u30f3\u30b0\u306e\u9593\u306b\u5897\u52a0\u3057\uff0cCOPD\u60a3\u8005\u304a\u3088\u3073\u5065\u5eb7\u306a\u9ad8\u9f62\u8005\u304a\u3088\u3073\u82e5\u5e74\u6210\u4eba\u306e\u5358\u4e00\u306e\u30bf\u30b9\u30af\u3068\u6bd4\u3079\u3066\u4e8c\u91cd\u306e\u4ed5\u4e8b\u306e\u9593\u306b\u3055\u3089\u306b\u5897\u52a0\u3059\u308b\uff0e H2\uff1a\u5358\u4e00\u306e\u30bf\u30b9\u30af\u3068\u6bd4\u8f03\u3057\u3066\uff0c3\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u3059\u3079\u3066\u306e\u53c2\u52a0\u8005\u306f\u4e8c\u91cd\u306e\u30bf\u30b9\u30af\u306e\u9593\uff0c\u5f8c\u65b9\u30b9\u30da\u30ea\u30f3\u30b0\u306e\u7cbe\u5ea6\u304c\u4f4e\u4e0b\u3057\uff0c\u6b69\u884c\u306e\u6e1b\u5c11\u304c\u5927\u304d\u304f\u306a\u308b\uff0e<br \/>\n\u65b9\u6cd5\uff1a\u88ab\u9a13\u8005\u306f\u4ee5\u4e0b\u306e\u5358\u4e00\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3057\u305f\uff0e\uff081\uff09\u8a8d\u77e5\u8ab2\u984c\uff08CT\uff09\u3067\u3042\u308b\u5f8c\u65b9\u30b9\u30da\u30ea\u30f3\u30b0\uff082\uff0930m\u306e\u597d\u307e\u3057\u3044\u6b69\u884c\u6b69\u884c\uff08PPW\uff09\uff083\uff0930m\u9ad8\u901f\u6b69\u884c\u6b69\u884c\uff08FPW\uff09\uff0e\u305d\u306e\u5f8c\uff0cPPW\u3068FPW\u306e\u305d\u308c\u305e\u308c\u3068CT\u3092\u30da\u30a2\u306b\u3057\u305f\u4e8c\u91cd\u306e\u30bf\u30b9\u30af\u3092\u884c\u3063\u305f\uff0efNIRS\u30c7\u30fc\u30bf\u3092fnirSoft\u3067\u51e6\u7406\u3057\uff0c\u751f\u7406\u5b66\u7684\u30ce\u30a4\u30ba\u304a\u3088\u3073\u30e2\u30fc\u30b7\u30e7\u30f3\u30a2\u30fc\u30c1\u30d5\u30a1\u30af\u30c8\u3092\u6e1b\u8870\u3055\u305b\u305f\uff0e\u6b21\u3044\u3067\uff0c\u4fee\u6b63\u3055\u308c\u305fBeerLambert\u6cd5\u3092\u7528\u3044\u3066L. DLPFC\u306eO2Hb\u306e\u5909\u5316\u3092\u8a08\u7b97\u3057\u305f\uff0e\u6b69\u6570\u30d1\u30e9\u30e1\u30fc\u30bf\u306f5\u00d70.88m\u306e\u5727\u529b\u306b\u654f\u611f\u306a\u30bc\u30ce\u30de\u30c3\u30c8\u3092\u7528\u3044\u3066\u6e2c\u5b9a\u3057\u305f\uff0e<br \/>\n\u7d50\u679c\uff1a 20\u6b73\u306e\u82e5\u5e74\u6210\u4eba\uff08\u7537\u6027=10\uff0c\u5973\u6027=10\uff0c\u5e74\u9f62\uff1a28\u00b14\u6b73\uff09\uff0c20\u4eba\u306e\u9ad8\u9f62\u8005\uff08\u7537\u6027=10\uff0c\u5973\u6027=10\uff0c64\u00b111\u6b73\uff09\u304a\u3088\u30736\u4eba\u306eCOPD\u60a3\u8005\uff08\u7537\u6027=3\uff0c\u5973\u6027=3\uff0c\u5e74\u9f62\uff1a74\u00b18\u6b73\uff09\u304c\u53c2\u52a0\u3057\u305f\uff0eDLPFC\u306e\u0394O2Hb\u306f\uff0c\u82e5\u5e74\u6210\u4eba\u306e\u30d9\u30fc\u30b9\u30e9\u30a4\u30f3\u8ab2\u984c\uff08p = 0.042\uff09\u3068\u6bd4\u8f03\u3057\u3066CT\u671f\u9593\u4e2d\u306b\u5897\u52a0\u3057\uff0c\u9ad8\u9f62\u8005\u304a\u3088\u3073COPD\u60a3\u8005\u306b\u304a\u3044\u3066\u3088\u308a\u5927\u304d\u304f\u306a\u308b\u50be\u5411\u304c\u3042\u3063\u305f\uff0e\u540c\u69d8\u306b\uff0cFPW + CT\u3067\u306fFPW\u3068\u6bd4\u8f03\u3057\u3066\u9ad8\u9f62\u8005\u3067\u6709\u610f\u306b\u9ad8\u304b\u3063\u305f\uff080.27\u00b10.95\u03bcM\u5bfe-0.49\u00b11.01\u03bcM\uff0cp = 0.007\uff09\uff0c\u82e5\u5e74\u6210\u4eba\u304a\u3088\u3073COPD\u60a3\u8005\u3067\u306f\u3088\u308a\u9ad8\u3044\u50be\u5411\u304c\u3042\u3063\u305f\uff0e1\u5bfe2\u306e\u30bf\u30b9\u30af\u3092\u6bd4\u8f03\u3059\u308b\u3068\uff0c\u82e5\u3044\u5065\u5e38\u8005\uff08-16.9\u00b121.4\uff05\uff0cp = 0.002\uff09\u304a\u3088\u3073\u53e4\u3044\u5065\u5eb7\u30b0\u30eb\u30fc\u30d7\uff08-20.1\u00b122.2\uff05\uff0cp = 0.001\uff09\u306b\u304a\u3044\u3066\uff0c\u5f8c\u65b9\u30b9\u30da\u30ea\u30f3\u30b0\u306e\u7cbe\u5ea6\u304c\u4f4e\u4e0b\u3057COPD\u7fa4\u3067\u306f\uff08-32.2\u00b145.7\uff05\uff0cp = 0.191\uff09\uff0cFPW + CT\u3067\u306fCT\u3068\u6bd4\u8f03\u3057\u3066\u9ad8\u304b\u3063\u305f\uff0e\uff081\uff09FPW + CT\u4e2d\u306e\u901f\u5ea6\u304c3\u7fa4\u3059\u3079\u3066\u306b\u304a\u3044\u3066FPW\u3068\u6bd4\u8f03\u3057\u3066\u6e1b\u5c11\u3057\u305f\uff08p &lt;0.05\uff09\uff0e\uff082\uff09FPW + CT\u4e2d\u306e\u9ad8\u9f62\u8005\u304a\u3088\u3073COPD\u60a3\u8005\u306b\u304a\u3044\u3066FPW\u3068\u6bd4\u8f03\u3057\u3066\u30b9\u30a4\u30f3\u30b0\u6642\u9593\u306e\u5909\u52d5\u6027\u304c\u5897\u52a0\u3057\u305f\uff08p = 0.030\u304a\u3088\u3073p = 0.038\uff09\uff0e\uff083\uff09FPW\u60a3\u8005\u3068\u6bd4\u8f03\u3057\u3066COPD\u60a3\u8005\u306b\u304a\u3051\u308bFPW + CT\u306e\u9593\u306b\u7acb\u4f4d\u6642\u9593\u5909\u52d5\u304c\u5897\u52a0\u3057\u305f\uff08p = 0.026\uff09\uff0e<br \/>\n\u8a0e\u8ad6\uff1a\u672c\u7d50\u679c\u306f\uff0c\u5358\u4e00\u306e\u30bf\u30b9\u30af\u3068\u6bd4\u8f03\u3057\u3066\u4e8c\u91cd\u306e\u30bf\u30b9\u30af\u304cPFC\u306e\u0394O2Hb\u3092\u5897\u52a0\u3055\u305b\uff0c\u5f8c\u65b9\u306e\u30b9\u30da\u30eb\u306e\u6b63\u78ba\u3055\u3092\u4f4e\u4e0b\u3055\u305b\uff0c\u3088\u308a\u9045\u304f\u3088\u308a\u53ef\u5909\u306a\u6b69\u884c\u3092\u3082\u305f\u3089\u3059\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u308b\uff0e\u3088\u308a\u5927\u304d\u306aCOPD\u60a3\u8005\u306e\u30b5\u30f3\u30d7\u30eb\u306f\uff0c\u672c\u30c7\u30fc\u30bf\u306e\u5f37\u3055\u3092\u6539\u5584\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\uff0e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u7740\u76ee\u3057\u305f\u70b9\u306f\uff0c\u3000\u56f3\u306e\u898b\u305b\u65b9\u3067\u3059\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"588\">\n<h1>\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0 \uff1a The Brain at Work: Neural Correlates of Cognitive and Motor Performance<\/h1>\n<p>\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a W. D. Reida , S. A. Hassanb , L. V. Bonettic , K. K. Pattersona , D. S. Beald and A. C. Ruoccoe<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster Session<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a<br \/>\n\u8981\u7d04\uff1a\u30a6\u30a7\u30a2\u30e9\u30d6\u30eb\u306afNIRS\u306f\uff0c\u7814\u7a76\u5ba4\u4ee5\u5916\u306e\u4eba\u9593\u306e\u793e\u4f1a\u7684\u884c\u52d5\u3092\u7406\u89e3\u3059\u308b\u53ef\u80fd\u6027\u3092\u4e0e\u3048\u3066\u3044\u308b\u304c\uff0c\u73fe\u5b9f\u306efNIRS\u30c7\u30fc\u30bf\u306e\u5206\u6790\u3068\u89e3\u91c8\u306b\u306f\u5927\u304d\u306a\u8ab2\u984c\u304c\u3042\u308b\uff0e\u672c\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\uff0c\u53cd\u5fa9\u53ef\u80fd\u3067\u6709\u610f\u7fa9\u306a\u793e\u4f1a\u7684\u76f8\u4e92\u4f5c\u7528\u3092\u691c\u8a3c\u3059\u308b\u305f\u3081\u306e\u30c6\u30b9\u30c8\u30d9\u30c3\u30c9\u3068\u3057\u3066\uff0c\u5287\u5834\u306e\u4ff3\u512a\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\uff0e\u5168\u8eab\u30e2\u30fc\u30b7\u30e7\u30f3\u30ad\u30e3\u30d7\u30c1\u30e3\uff08mocap\uff09\u3068\u7d44\u307f\u5408\u308f\u305b\u3066fNIRS\u30c7\u30fc\u30bf\u3092\u53ce\u96c6\u3057\uff0c\u30e2\u30ab\u30c3\u30d7\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u52d5\u7684\u306a\u793e\u4f1a\u7684\u76f8\u4e92\u4f5c\u7528\u3092\u901a\u3058\u305f\u795e\u7d4c\u6d3b\u6027\u5316\u306e\u30d1\u30bf\u30fc\u30f3\u3092\u660e\u3089\u304b\u306b\u3059\u308b\u65b0\u3057\u3044\u518d\u767a\u5b9a\u91cf\u5316\u30e1\u30bd\u30c3\u30c9\u306e\u958b\u767a\u3092\u76ee\u7684\u3068\u3057\u3066\u3044\u308b\uff0e<br \/>\n\u65b9\u6cd5\uff1a\u5b9f\u9a13\u306b\u306f\u8a13\u7df4\u3092\u53d7\u3051\u305f2\u4eba\u306e\u4ff3\u512a\u30681\u4eba\u306e\u5287\u5834\u76e3\u7763\u304c\u53c2\u52a0\u3057\u305f\uff0e\u4e21\u65b9\u306e\u4ff3\u512a\u306f120Hz\u3067\u982d\u90e8\u3068\u56db\u80a2\u306e\u4f4d\u7f6e\u3092\u6355\u6349\u3059\u308bPerception Neuron\u304b\u3089\u5168\u8eab\uff0c\u6163\u6027\u30bb\u30f3\u30b5\u30d9\u30fc\u30b9\u306emocap\u30b9\u30fc\u30c4\u3092\u7740\u7528\u3057\u307e\u3057\u305f\uff0e1\u4eba\u306e\u4ff3\u512a\uff08B\uff09\u306f\uff0c5Hz\u3067\u524d\u982d\u524d\u91ce\u76ae\u8cea\u306b\u795e\u7d4c\u6d3b\u52d5\u3092\u8a18\u9332\u3059\u308b\uff0c16\u30c1\u30e3\u30f3\u30cd\u30eb\u306e\u7dda\u7dad\u6027\u306efNIRS\u30b7\u30b9\u30c6\u30e0\uff08WOT\uff0c\u65e5\u7acb\uff09\u3092\u88c5\u7740\u3057\u305f\uff0e\u8a18\u9332\u306f10x10m\u306e\u30d6\u30e9\u30c3\u30af\u30dc\u30c3\u30af\u30b9\u306e\u5287\u5834\u7a7a\u9593\u3067\u884c\u308f\u308c\u305f\uff0e20\u5206\u306e\u30ec\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u30bb\u30c3\u30b7\u30e7\u30f3\u3067\u306f\uff0c\u30b7\u30a7\u30a4\u30af\u30b9\u30d4\u30a2\u306e\u30c6\u30f3\u30da\u30b9\u30c8\u304b\u3089\u306e2\u3064\u306e\u30b7\u30e7\u30fc\u30c8\u30b7\u30fc\u30f3\uff08a\uff09\u30df\u30e9\u30f3\u30c0\u306f\u30ad\u30e3\u30ea\u30d0\u30f3\u306e\u9032\u6b69\u3092\u62d2\u5426\u3057\uff0cb\uff09\u30ad\u30e3\u30ea\u30d0\u30f3\u306f\u30d7\u30ed\u30b9\u30da\u30ed\u306e\u80cc\u5f8c\u3067\u9a5a\u3044\u3066\uff0c\u5f7c\u3092\u9a5a\u304b\u305b\u308b\uff0e\u4ff3\u512a\u306f\u5404\u30b7\u30fc\u30f3\u30923\u56de\u6f14\u594f\u3057\uff0c\u6b21\u306b\u30ed\u30fc\u30eb\u3092\u4ea4\u63db\u3057\uff0c3\uff5e6\u56de\u7e70\u308a\u8fd4\u3057\u518d\u751f\u3059\u308b\uff0e<br \/>\n\u30c7\u30fc\u30bf\u5206\u6790\uff1afNIRS\u30c7\u30fc\u30bf\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3057\uff0c\u30e2\u30fc\u30b7\u30e7\u30f3\u30a2\u30fc\u30c1\u30d5\u30a1\u30af\u30c8\u3092\u88dc\u6b63\u3057\uff0c\u30c0\u30a6\u30f3\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3057\uff0cCBSI\u5909\u63db\u3092\u7528\u3044\u3066\u795e\u7d4c\u6d3b\u6027\u5316\u4fe1\u53f7\u306b\u5909\u63db\u3057\u305f\uff0eMocap\u30c7\u30fc\u30bf\u306f\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3055\u308c\uff0c1000\u79d2\u306e\u5b9f\u9a13\u6642\u9593\u7d4c\u904e\u306b\u308f\u305f\u3063\u3066\u5404\u30a2\u30af\u30bf\u306e6\u3064\u306e\u7279\u5fb4\uff08\u982d\u90e8\uff0c\u81c0\u90e8\uff0c\u4e21\u624b\uff0c\u4e21\u8db3\uff09\u306e\u904b\u52d5\u30a8\u30cd\u30eb\u30ae\u30fc\u4fe1\u53f7\u306b\u5909\u63db\u3055\u308c\u305f\uff0e\u30e2\u30ab\u30c3\u30d7\u30c7\u30fc\u30bf\u306e\u53ef\u80fd\u306a\u54048\u79d2\u30b5\u30f3\u30d7\u30eb\u306f\uff0c\u6b8b\u308a\u306e\u30e2\u30ab\u30d7\u30c7\u30fc\u30bf\u5185\u306e\u53ef\u80fd\u306a\u54048\u79d2\u30a6\u30a3\u30f3\u30c9\u30a6\u3068\u76f8\u95a2\u3055\u308c\uff0c\u518d\u73fe\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u305f\uff0e\u3053\u306e\u30d7\u30ed\u30c3\u30c8\u306e\u5bfe\u89d2\u7dda\u306e\u9ec4\u8272\u306e\u30d1\u30bf\u30fc\u30f3\u306f\uff0c\u4ff3\u512a\u304c\u540c\u3058\u5834\u9762\u3092\u7e70\u308a\u8fd4\u3057\u5b9f\u884c\u3057\uff0c\u30d3\u30c7\u30aa\u6ce8\u91c8\uff08\u8d64\u7dda\uff09\u3068\u4e00\u81f4\u3059\u308b\u3068\u304d\u3092\u793a\u3059\uff0e\u5404\u7e70\u308a\u8fd4\u3057\u30d1\u30bf\u30fc\u30f3\u306e\u4e2d\u5fc3\uff08\u30d4\u30f3\u30af\/\u9ed2\u306e\u70b9\uff09\u3092\u5404\u91cd\u5927\u4e8b\u8c61\u306e\u4e2d\u5fc3\u3068\u3057\uff0cfNIRS\u30c7\u30fc\u30bf\u3092\u3053\u306e\u4e8b\u8c61\u306e\u524d\u5f8c8\u79d2\u9593\u306b\u308f\u305f\u3063\u3066\u5e73\u5747\u3057\u305f\uff0e\u3053\u308c\u306f\uff0c\u4ff3\u512a\u306b\u3088\u3063\u3066\u5b9f\u884c\u3055\u308c\u305f\u5404\u53cd\u5fa9\u30b7\u30fc\u30f3\u306b\u304a\u3044\u3066\uff0cfNIRS\u4fe1\u53f7\u306e\u30e2\u30ab\u30c3\u30d7\u5b9a\u7fa9\u3055\u308c\u305f\u753b\u50cf\u3092\u4e0e\u3048\u308b\uff0e<br \/>\n\u8a0e\u8ad6\uff1a\u3053\u308c\u3089\u306e\u30c7\u30fc\u30bf\u306f\uff0c\u610f\u5473\u306e\u3042\u308bfNIRS\u30c7\u30fc\u30bf\u304c\u5287\u5834\u306e\u6587\u8108\u91cd\u5927\u306a\u3053\u3068\u306b\uff0c\u5168\u8eab\u30e2\u30fc\u30b7\u30e7\u30f3\u30ad\u30e3\u30d7\u30c1\u30e3\u306b\u3088\u308a\uff0c\u79c1\u305f\u3061\u306ffNIRS\u30c7\u30fc\u30bf\u306e\u30c7\u30fc\u30bf\u99c6\u52d5\u5206\u6790\u3092\u5b9f\u65bd\u3057\uff0c\u4ff3\u512a\u306e\u8133\u5185\u3067\u8d77\u3053\u3063\u3066\u3044\u308b\u8a8d\u77e5\u4e8b\u8c61\u3092\u8996\u899a\u5316\u3059\u308b\u3053\u3068\u3092\u53ef\u80fd\u306b\u3057\u305f\uff0e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u9762\u767d\u304b\u3063\u305f\u3068\u3053\u308d\u306f\uff0c\u88ab\u9a13\u8005\u304c\u4ff3\u512a\u3060\u3063\u305f\u70b9\u3067\u3059\uff0eNIRS\u306e\u5229\u70b9\u3067\u3042\u308b\u52d5\u4f5c\u3057\u306a\u304c\u3089\u8133\u6d3b\u52d5\u3092\u8a08\u6e2c\u3057\u3066\u304a\u308a\u30e2\u30fc\u30b7\u30e7\u30f3\u306e\u30c7\u30fc\u30bf\u3068\u8133\u6d3b\u52d5\u306e\u30c7\u30fc\u30bf\u306b\u3064\u3044\u3066\u8003\u5bdf\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u8ab2\u984c\u306fN\u6570\u304c\u5c11\u306a\u3044\u3053\u3068\u3067\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"588\">\n<h1>\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0 \uff1a Seeing into the brain of an actor with fNIRS and mocap<\/h1>\n<p>\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a A. Hamilton1, P. Pinti1,2, D. Paoletti2, J.A. Ward2<br \/>\n&nbsp;<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster Session<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a<br \/>\nfNIRS\u306f\uff0c\u975e\u4fb5\u8972\u7684\u306a\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u6280\u8853\u3067\u3042\u308a\u7814\u7a76\u3084\u81e8\u5e8a\u5fdc\u7528\u3078\u306e\u95a2\u5fc3\u304c\u9ad8\u307e\u3063\u3066\u3044\u308b\uff0e\u904e\u53bb10\u5e74\u9593\uff0c\u8133\u7d44\u7e54\u306b\u304a\u3051\u308b\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u5909\u5316\u306e\u6709\u52b9\u306a\u6e90\u3092\u30a4\u30e1\u30fc\u30b8\u3059\u308b\u305f\u3081\u306e\u6570\u5b66\u7684\u67a0\u7d44\u307f\u3092\u958b\u767a\u3059\u308b\u53d6\u308a\u7d44\u307f\u304c\u306a\u3055\u308c\u3066\u304d\u305f\uff0e\u75c5\u6c17\u306e\u8133\u753b\u50cf\u3092\u518d\u69cb\u6210\u3059\u308b\u969b\uff0c\u8ffd\u52a0\u306e\u60c5\u5831\u307e\u305f\u306f\u5236\u7d04\u3092\u8ab2\u3059\u305f\u3081\u306b\u3055\u307e\u3056\u307e\u306a\u30a2\u30d7\u30ed\u30fc\u30c1\u304c\u3042\u308b\uff0e\u672c\u7814\u7a76\u306e\u76ee\u7684\u306f\uff0c\u88ab\u9a13\u8005\u3054\u3068\u306bMRI\u3092\u4f7f\u7528\u3057\u3066\u5149\u4f1d\u64ad\u3092\u30e2\u30c7\u30eb\u5316\u3059\u308bfNIRS\u65ad\u5c64\u64ae\u5f71\u306e\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u3067\uff0c\u3044\u304f\u3064\u304b\u306e\u7dda\u6e90\u4f4d\u7f6e\u7279\u5b9a\u6280\u8853\u306e\u6027\u80fd\u304a\u3088\u3073\u9650\u754c\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\u3067\u3042\u308b\uff0e\u9806\u554f\u984c\u306f\u7d44\u7e54\u5185\u306e\u5149\u4f1d\u642c\u306e\u30e2\u30f3\u30c6\u30ab\u30eb\u30ed\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u7528\u3044\u3066\u89e3\u6c7a\u3055\u308c\u308b\uff0e\u9006\u554f\u984c\u306fRytov\u8fd1\u4f3c\u3092\u7528\u3044\u3066\u7dda\u5f62\u5316\u3055\u308c\u308b\uff0e\u6b21\u306bTikhonov\u6b63\u5247\u5316\u306f\u6700\u5c0f\u4e8c\u4e57\u6cd5\u306b\u9069\u7528\u3055\u308c\uff0c\u7279\u7570\u5024\u5206\u89e3\uff0c\u30d0\u30c3\u30af\u30d7\u30ed\u30b8\u30a7\u30af\u30b7\u30e7\u30f3\uff0cL1-\u30ce\u30eb\u30e0\u6b63\u898f\u5316\uff0c\u6700\u5c0f\u898f\u7bc4\u63a8\u5b9a\uff0c\u4f4e\u5206\u89e3\u80fd\u96fb\u78c1\u30c8\u30e2\u30b0\u30e9\u30d5\u30a3\uff0c\u30d9\u30a4\u30b8\u30a2\u30f3\u30e2\u30c7\u30eb\u5e73\u5747\u5316\u6280\u6cd5\u306f\uff0c\u7279\u6027\u5206\u6790\uff0c\u307c\u304b\u3057\u304a\u3088\u3073\u5c40\u5728\u5316\u8aa4\u5dee\u6e2c\u5b9a\u3092\u52d5\u4f5c\u3055\u305b\u308b\u53d7\u4fe1\u6a5f\u3092\u4f7f\u7528\u3057\u3066\u6bd4\u8f03\u3055\u308c\u308b\uff0e\u73fe\u5b9f\u7684\u306a\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\uff08N = 450\uff09\u304a\u3088\u3073\u6210\u4eba\u306e\u88ab\u9a13\u8005\u304b\u3089\u5f97\u3089\u308c\u305f\u30c7\u30fc\u30bf\u3092\u7528\u3044\u3066\uff0c\u3053\u306e\u7814\u7a76\u306f\u3053\u308c\u3089\u306e\u97f3\u6e90\u5b9a\u4f4d\u6280\u6cd5\u304c\u4eba\u9593\u306e\u982d\u90e8fNIRS\u65ad\u5c64\u64ae\u5f71\u6cd5\u306b\u304a\u3044\u3066\u3069\u306e\u3088\u3046\u306b\u6319\u52d5\u3059\u308b\u304b\u3092\u63cf\u5199\u3059\u308b\uff0eBayesian Model Averaging\u306f\uff0c\u4ed6\u306e\u65b9\u6cd5\u3068\u6bd4\u8f03\u3057\u3066DOT\u306e\u6709\u671b\u306a\u65b9\u6cd5\u3068\u3057\u3066\u63d0\u6848\u3055\u308c\u3066\u304a\u308a\uff0c\u7279\u7570\u6027\u3084\u7cbe\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u308b\u53ef\u80fd\u6027\u304c\u9ad8\u304f\uff0c\u9a12\u97f3\u3084\u6df1\u3044\u60c5\u5831\u6e90\u304c\u3042\u308b\u5834\u5408\u3067\u3082\u307c\u3084\u3051\u3084\u5c40\u5728\u8aa4\u5dee\u3092\u4f4e\u6e1b\u3059\u308b\u53ef\u80fd\u6027\u304c\u9ad8\u3044\uff0e\u6b63\u898f\u5316\u3055\u308c\u305f\u6700\u5c0f\u4e8c\u4e57\u6cd5\u306a\u3069\u306e\u53e4\u5178\u7684\u306a\u518d\u69cb\u6210\u65b9\u6cd5\u306f\uff0c\u3088\u308a\u826f\u3044\u611f\u5ea6\u3092\u63d0\u4f9b\u3059\u308b\u304c\uff0c\u3088\u308a\u9ad8\u3044\u307c\u304b\u3057\u3092\u63d0\u4f9b\u3059\u308b\uff0e\u3088\u308a\u65ac\u65b0\u306aL1\u30d9\u30fc\u30b9\u306e\u65b9\u6cd5\u306f\uff0c\u308f\u305a\u304b\u306a\u307c\u304b\u3057\u304a\u3088\u3073\u9ad8\u3044\u7279\u7570\u6027\u3092\u6709\u3059\u308b\u304c\u611f\u5ea6\u306f\u4f4e\u3044\u758e\u6eb6\u6db2\u3092\u63d0\u4f9b\u3059\u308b\uff0e\u3053\u308c\u3089\u306e\u65b9\u6cd5\u306e\u9069\u7528\u306f\uff0c\u6210\u4eba\u306e\u88ab\u9a13\u8005\u3068\u306e\u8996\u899a\u7684fNIRS\u5b9f\u9a13\u3092\u7528\u3044\u3066\u5b9f\u9a13\u7684\u306b\u3082\u5b9f\u8a3c\u3055\u308c\u3066\u3044\u308b\uff0e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u9762\u767d\u304b\u3063\u305f\u3068\u3053\u308d\u306f\uff0c\u62e1\u6563\u5149\u30c8\u30e2\u30b0\u30e9\u30d5\u30a3\uff08Diffuse optical tomography\uff0cDOT\uff09\u306b\u7740\u76ee\u3057\u3066\u3044\u305f\u70b9\u3067\u3059\uff0e\u9806\u554f\u984c\u30fb\u9006\u554f\u984c\u3092\u65b9\u7a0b\u5f0f\u3092\u7528\u3044\u3066\u89e3\u3044\u3066\u3044\u3066\uff0c\u666e\u6bb5\u3042\u307e\u308a\u805e\u304d\u306a\u308c\u306a\u3044\u8a71\u3060\u3063\u305f\u306e\u3067\u96e3\u3057\u304b\u3063\u305f\u3067\u3059\u304c\uff0c\u672c\u30dd\u30b9\u30bf\u30fc\u4ee5\u5916\u306b\u3082DOT\u306e\u767a\u8868\u3092\u3057\u3066\u3044\u308b\u4eba\u304c\u591a\u304f\u898b\u53d7\u3051\u3089\u308c\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table width=\"590\">\n<tbody>\n<tr>\n<td width=\"590\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aComparison of Kernels in Online SVM Classification of fNIRS Data<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Ruisen Huanga , Ho-Ryong Yoob and Keum-Shik Honga<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster Session<br \/>\nAbstruct\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a<br \/>\n\u76ee\u7684\uff1aSVM\uff08Support Vector Machine\uff09\u306f\u8133\u4fe1\u53f7\u5206\u985e\u306b\u304a\u3044\u3066\u5e83\u304f\u7528\u3044\u3089\u308c\u3066\u3044\u308b\u304c\uff0cSVM\u306e\u305f\u3081\u306e\u6700\u9069\u5316\u3055\u308c\u305f\u30ab\u30fc\u30cd\u30eb\u306f\u672a\u77e5\u306e\u307e\u307e\u3067\u3042\u308b\uff0e<br \/>\n\u65b9\u6cd5\uff1a8\u540d\u306e\u5065\u5eb7\u306a\u88ab\u9a13\u8005\u304b\u3089\u53d6\u5f97\u3057\u305f\u8133\u4fe1\u53f7\u3092\u8abf\u3079\u305f\uff0efNIRS\u3092\u7528\u3044\u3066mental arithmetic (AR)\u8ab2\u984c\u3068mental counting (MC)\u8ab2\u984c\u4e2d\u306e\u524d\u982d\u524d\u91ce\u304b\u3089\u306e\u4fe1\u53f7\u3092\u53d6\u5f97\u3057\u305f\uff0e\u5404\u30c1\u30e3\u30cd\u30eb\u304b\u3089\u50be\u304d\uff08\u6700\u5c0f\u4e8c\u4e57\u56de\u5e30\u8fd1\u4f3c\uff09\uff0c\u5e73\u5747\uff0c\u5206\u6563\uff0c\u6700\u5927\u304a\u3088\u3073\u6700\u5c0f\u7279\u5fb4\u3092\u62bd\u51fa\u3057\uff0c\u6700\u7d42\u7684\u306b\u30d0\u30a4\u30ca\u30ea\u304a\u3088\u3073\u30de\u30eb\u30c1\u30af\u30e9\u30b9\u5206\u985e\u30bf\u30b9\u30af\u306bSVM\u3092\u4f7f\u7528\u3057\u305f\uff0e\u3053\u306e\u30d7\u30ed\u30bb\u30b9\u3067\u306f\u7dda\u5f62\uff0c\u30ac\u30a6\u30b9\uff0c\u591a\u9805\u5f0f\u306a\u3069\u306e\u3044\u304f\u3064\u304b\u306e\u7570\u306a\u308b\u30ab\u30fc\u30cd\u30eb\u304c\u30c6\u30b9\u30c8\u3055\u308c\u305f\uff0e<br \/>\n\u7d50\u679c\u3068\u8003\u5bdf\uff1a\u5206\u985e\u7387\u306f\uff0c\u30ab\u30fc\u30cd\u30eb\u3054\u3068\u306b\u975e\u5e38\u306b\u7570\u306a\u3063\u305f\uff0e \u30ac\u30a6\u30b7\u30a2\u30f3\u30ab\u30fc\u30cd\u30eb\u306e\u6a19\u6e96\u504f\u5dee\u3084\u591a\u9805\u5f0f\u30ab\u30fc\u30cd\u30eb\u306e0\u6b21\u9805\u306a\u3069\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\uff0c\u5206\u985e\u7cbe\u5ea6\u306b\u5927\u304d\u304f\u5f71\u97ff\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\uff0e\u305d\u306e\u7d50\u679c\uff0c\u3053\u308c\u3089\u306e\u8abf\u6574\u53ef\u80fd\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u6700\u9069\u5316\u3055\u308c\u305f\u5024\u306f\u88ab\u9a13\u8005\u56fa\u6709\u3067\u3042\u308b\u3053\u3068\u304c\u8a3c\u660e\u3055\u308c\u308b\uff0e\u3053\u308c\u306f\uff0c\u540c\u3058\u5024\u3067\u5206\u985e\u7387\u304c85\uff05\u3092\u8d85\u3048\u308b\u5834\u5408\u308432\uff05\u3088\u308a\u4f4e\u304f\u306a\u308b\u5834\u5408\u304c\u3042\u308b\u305f\u3081\u3067\u3042\u308b\uff0e \u5404\u30ab\u30fc\u30cd\u30eb\u306e\u9577\u6240\u3068\u77ed\u6240\u3092\u307e\u3068\u3081\u8b70\u8ad6\u3057\u305f\uff0e<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u7740\u76ee\u3057\u305f\u306e\u306f\uff0c NIRS\u30c7\u30fc\u30bf\u306b\u5bfe\u3057\u3066SVM\u3092\u7528\u3044\u3066\u3044\u308b\u70b9\u3067\u3059\uff0e2\u3064\u306e\u624b\u6cd5\u3092\u6bd4\u8f03\u3057\u3066\u304a\u308a\uff0c\u63d0\u6848\u624b\u6cd5\u306e\u7d50\u679c\u306b\u3064\u3044\u3066\u71b1\u304f\u8a9e\u3063\u3066\u304f\u308c\u305f\u306e\u304c\u5370\u8c61\u7684\u3067\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"147\"><strong>\u00a0<\/strong><br \/>\n<strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n<td width=\"373\">&nbsp;<br \/>\n\u5c71\u672c\u6e09\u5b50<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\"><\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">A fNIRS study of attentional state<br \/>\ninduced by breath-counting meditation<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8457\u8005<\/strong><\/td>\n<td width=\"373\">\u5c71\u672c\u6e09\u5b50, \u65e5\u548c\u609f\uff0c\u5ee3\u5b89\u77e5\u4e4b,<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4e3b\u50ac<\/strong><\/td>\n<td width=\"373\">Society for fNIRS<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\n<td width=\"373\">fNIRS2018<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4f1a\u5834<\/strong><\/td>\n<td width=\"373\">\u6771\u4eac\u5927\u5b66<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u958b\u50ac\u65e5\u7a0b\u3000<\/strong><\/td>\n<td width=\"373\">2018\/10\/05-2018\/10\/08<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n<ol>\n<li>\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u304b\u3051\u3066\uff0c\u6771\u4eac\u5927\u5b66\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305ffNIRS2018\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u3053\u306efNIRS2018\u306f\uff0cSociety for fNIRS\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\u305f\u7814\u7a76\u4f1a\u3067\uff0cSociety for fNIRS\u306f\uff0c\u5149\u5b66\u7684\u65b9\u6cd5\u3092\u7528\u3044\u3066\u751f\u7269\uff0c\u7279\u306b\u8133\u6a5f\u80fd\u7279\u6027\u3092\u7406\u89e3\u3057\u3088\u3046\u3068\u3059\u308b\u57fa\u790e\u79d1\u5b66\u8005\u53ca\u3073\u81e8\u5e8a\u79d1\u5b66\u8005\u306e\u5c02\u9580\u7d44\u7e54\u3067\u3059\uff0e\u3053\u306e\u5b66\u4f1a\u306e\u76ee\u7684\u306f\uff0c\u30a2\u30a4\u30c7\u30a2\u306e\u4ea4\u63db\u3084\uff0c\u5b66\u969b\u7684\u5354\u529b\uff0c\u6559\u80b2\u3092\u4fc3\u9032\u3059\u308b\u3053\u3068\u3067\u3059\uff0e<br \/>\n\u79c1\u306f\u5168\u3066\u306e\u65e5\u7a0b\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u65e5\u548c\u5148\u751f\uff0cM2\u6c60\u7530\u3055\u3093\uff0c\u897f\u6fa4\u3055\u3093\uff0c\u6c34\u91ce\u3055\u3093\uff0cM1\u8c37\u53e3\u304f\u3093\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"2\">\n<li>\u7814\u7a76\u767a\u8868\n<ul>\n<li>\u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\u79c1\u306f8\u65e5\u306e10\u6642\u534a\u304b\u308911\u6642\u534a\uff0c\u53ca\u307314\u6642\u304b\u308915\u6642\u306e\u30bb\u30c3\u30b7\u30e7\u30f3\u300cPoster\u2162\u300d\u306b\u53c2\u52a0\u81f4\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c\u767a\u8868\u6642\u9593\u306f\u5348\u524d\u3068\u5348\u5f8c\u54041\u6642\u9593\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e<br \/>\n\u4eca\u56de\u306f\uff0cA fNIRS study of attentional state induced by breath-counting meditation\u3068\u3044\u3046\u30bf\u30a4\u30c8\u30eb\u3067\u767a\u8868\u81f4\u3057\u307e\u3057\u305f\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\"><strong>Introduction:<\/strong> Mindfulness, nonjudgmentally paying attention to the present moment, is expected to promote our mental well-being. One of the important components of meditation is attention. In the meditation practice, practitioners try to sustain their attention on their physical sensation so as to improve their interoceptive attention. In this study, we aim to investigate whether meditation induces our interoceptive attention using fNIRS scanning of brain activity during breath-counting meditation. To emphasize the characteristics of the interoceptive state, we also measured the exteroceptive state of practitioners during responding to and counting the external auditory cues. The brain states between two states were compared and discussed using functional connectivity analysis.<br \/>\n<strong>Methods: <\/strong>Meditation novices (10 males, aged 21.4 \u00b1 1.0 years) who had never experienced meditation practices or retreats participated in the experiment. They were asked to perform two tasks: 1) breath-counting task (BCT) and 2) auditory counting task (ACT). BCT is first proposed by Levinson et al. and shown to be effective as a behavioral measure of mindfulness meditation [1]. In the BCT, participants counted their breaths from 1 to 9 repeatedly, not with voice but just mentally. With breaths 1\u20138 they pressed one button, and on ninth breath they pressed another. In the ACT, they were asked to quickly press the button responding to the auditory cues and counted them from 1 to 9 as same as the BCT. In both tasks, they restarted counting from one if they got distracted as well as pressing a third button. An fNIRS device (ETG-7100, Hitachi, Ltd.) whose probes were placed on frontal region (47 CH), occipital region (47 CH) and parietal region (22 CH) was used to measure the brain activity during two tasks. The measured data was band-pass filtered with the pass band of 0.008 &#8211; 0.09 Hz. Pearson\u2019s correlation coefficient matrix of the cerebral blood flow changes among all the brain regions were calculated for each participant. Each matrix was binarized so as to preserve the edge density of 15%. Graph theoretical metrics, degree centrality and betweenness centrality were calculated for each matrix. Differences in functional connectivity network between two tasks were compared based on these graph metrics.<br \/>\n<strong>Results<\/strong>: We found that degree centrality of the right dorsal superior frontal gyrus (SFGdor) was significantly higher in the BCT than the ACT, while couldn\u2019t find no significant differences in betweenness centrality. The SFGdor is included in dorsal attention network and involved with top-down attention [2]. We assume that the BCT induced active attention to the participants\u2019 interoceptive sense, while the ACT induced the passive states to the external stimuli. Also, our study has revealed that the difference between the two states was reflected on the nodal degree of the SFGdor. The future study should be performed to further test these assumptions together with the analysis of correlations between neural states and behavioral metrics such as a counting accuracy.<br \/>\n&nbsp;<br \/>\n[1] D.B. Levinson, E.L. Stoll, S.D. Kindy, H.L. Merry and R.J. Davidson, \u201cA mind you can count on: validating breath counting as a behavioral measure of mindfulness,&#8221; Frontiers in psychology, vol. 5, p.1202, 2014.<br \/>\n[2] R.N. Spreng, J. Sepulcre, G.R. Turner, W.D. Stevens and D.L. Schacter, \u201cIntrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain,&#8221; Journal of cognitive neuroscience, vol. 25, no. 1, pp. 74-86, 2013.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<ul>\n<li>\u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n<p>\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<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>1<\/strong><br \/>\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\uff0c2\u3064\u306e\u30bf\u30b9\u30af\u306e\u9055\u3044\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0cACT\u306f\u5916\u53d7\u5bb9\u7684\u51e6\u7406\u3092\u4fc3\u3059\u3088\u3046\u6ce8\u610f\u5bfe\u8c61\u3092\u5916\u90e8\u523a\u6fc0\u3068\u3057\uff0c\u4e00\u65b9\u3067BCT\u306f\u6570\u606f\u89b3\u3092\u884c\u3046\u3053\u3068\u306b\u3088\u308a\u5185\u767a\u7684\u6ce8\u610f\u3092\u4fc3\u3057\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n<strong>\u00a0<\/strong><br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>2<\/strong><br \/>\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\uff0cCounting accuracy\u3068\u306f\u306a\u306b\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u5b9f\u9a13\u4e2d\u3069\u306e\u3088\u3046\u306b\u30dc\u30bf\u30f3\u30d7\u30ec\u30b9\u3092\u884c\u3063\u3066\u3044\u308b\u304b\u3092\u8aac\u660e\u3057\uff0c\u6b63\u3057\u3044\u30dc\u30bf\u30f3\u30d7\u30ec\u30b9\u306e\u30bb\u30c3\u30c8\u6570\u3092\u7dcf\u30bb\u30c3\u30c8\u6570\u3067\u5272\u308b\u3053\u3068\u3067\u7b97\u51fa\u3057\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>3<\/strong><br \/>\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\u76f8\u95a2\u3092\u6c42\u3081\u305f\u30c7\u30fc\u30bf\u306f\u3069\u306e\u30c7\u30fc\u30bf\u304b\uff0c\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u306e\u307f\u89e3\u6790\u3057\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u306e\u5909\u5316\u91cf\u306e\u307f\u89e3\u6790\u3057\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>4<\/strong><br \/>\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\uff0cCH\u6570\u306f\u3044\u304f\u3064\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u5168\u8133\u6e2c\u5b9a\u3057\uff0c116CH\u3067\u3042\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>5<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306f\uff0c\u6e2c\u5b9a\u30c7\u30fc\u30bf\u306b\u9aea\u306e\u6bdb\u306e\u5f71\u97ff\u306f\u306a\u3044\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u88c5\u7f6e\u306b\u3088\u308a\u30a8\u30e9\u30fcCH\u3092\u5224\u5b9a\u3057\uff0c\u305d\u306eCH\u306f\u89e3\u6790\u5bfe\u8c61\u304b\u3089\u9664\u5916\u3057\u3066\u3044\u308b\u305f\u3081\u554f\u984c\u306a\u3044\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u3057\u304b\u3057\u4eca\u5f8c\u691c\u8a0e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3068\u8003\u3048\u3066\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>6<\/strong><br \/>\n\u30e4\u30af\u30eb\u30c8\u306e\u7814\u7a76\u6240\u306e\u65b9\u304b\u3089\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u3053\u306e\u30bf\u30b9\u30af\u306e\u9055\u3044\u304c\u5206\u304b\u3063\u305f\u3089\u4f55\u304c\u3044\u3044\u306e\u304b\uff0c\u4e0a\u4f4d\u76ee\u7684\u306f\u4f55\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u7791\u60f3\u4e2d\u306e\u8133\u72b6\u614b\u3092\u5b9a\u91cf\u5316\u3057\uff0c\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u3068\u3057\u3066\u3044\u308b\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>8<\/strong><br \/>\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\u7791\u60f3\u3068\u8a00\u3063\u305f\u3089\u76ee\u3092\u3064\u3076\u3063\u3066\u3044\u308b\u30a4\u30e1\u30fc\u30b8\u3060\u304c\u3053\u306e\u5b9f\u9a13\u306f\u3069\u3046\u3057\u3066\u3044\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u9589\u773c\u3067\u5b9f\u9a13\u3092\u884c\u3063\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>9<\/strong><br \/>\n\u65b0\u6f5f\u533b\u7642\u798f\u7949\u5927\u5b66\u306e\u5c0f\u5cf6\u3055\u3093\u304b\u3089\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u3053\u306e\u30bf\u30b9\u30af\u306f\u4eba\u306b\u3088\u3063\u3066\u6570\u306f\u9055\u3046\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u56de\u7b54\u3067\u3059\u304c\uff0c\u4e21\u65b9\u5171\u306e\u30bf\u30b9\u30af\u3067\u500b\u4eba\u306b\u3088\u3063\u3066\u56de\u6570\u304c\u7570\u306a\u308a\uff0cBCT\u306f\u4eba\u306b\u3088\u3063\u3066\u547c\u5438\u306e\u30b9\u30d4\u30fc\u30c9\u304c\u9055\u3044\uff0cACT\u306f\u30e9\u30f3\u30c0\u30e0\u306a\u611f\u899a\u3067\u97f3\u3092\u63d0\u793a\u3057\u3066\u3044\u308b\u305f\u3081\u7570\u306a\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>10<\/strong><br \/>\n\u540c\u3058\u304f\uff0c\u5c0f\u5cf6\u3055\u3093\u304b\u3089\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u7791\u60f3\u3068\u306f\u305d\u3093\u306a\u306b\u884c\u308f\u308c\u3066\u3044\u308b\u3082\u306e\u306a\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u56de\u7b54\u3067\u3059\u304c\uff0c\u6d77\u5916\u3067\u306f\u6709\u540d\u306a\u4f01\u696d\u3067\u4f5c\u696d\u52b9\u7387\u3092\u4e0a\u3052\u308b\u305f\u3081\u306b\u7791\u60f3\u3059\u308b\u6642\u9593\u3092\u8a2d\u3051\u308b\u306a\u3069\u3068\u53d6\u308a\u5165\u3089\u308c\u3066\u3044\u308b\u304c\uff0c\u305d\u308c\u306b\u5bfe\u3057\u3066\u65e5\u672c\u3067\u306f\u307e\u3060\u305d\u3053\u307e\u3067\u666e\u53ca\u3057\u3066\u3044\u306a\u3044\u304b\u3082\u3057\u308c\u306a\u3044\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>11<\/strong><br \/>\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\u30dc\u30bf\u30f3\u30d7\u30ec\u30b9\u306e\u969b\uff0c\u7dd1\u306e\u30dc\u30bf\u30f3\u306f\u3044\u3064\u62bc\u3059\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3059\u308b\u56de\u7b54\u3067\u3059\u304c\uff0c2\u3064\u306e\u30bf\u30b9\u30af\u3068\u3082\u6c17\u304c\u9038\u308c\u305f\u3089\u62bc\u3059\u3088\u3046\u6307\u793a\u3057\u3066\u3044\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u3057\u304b\u3057\uff0c\u7279\u306bACT\u3067\u306f1\u304b\u30899\u307e\u3067\u30dc\u30bf\u30f3\u3092\u62bc\u3057\u3066\u3044\u308b\u6700\u4e2d\u306b\u7dd1\u306e\u30dc\u30bf\u30f3\u3092\u62bc\u3059\u30bf\u30a4\u30df\u30f3\u30b0\u304c\u5206\u304b\u3089\u306a\u3044\u3068\u8cea\u554f\u3044\u305f\u3060\u304d\uff0c\u3046\u307e\u304f\u7b54\u3048\u3089\u308c\u305a\u5ee3\u5b89\u5148\u751f\u306b\u52a9\u3051\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e1\u304b\u30899\u307e\u3067\u6570\u3048\u3066\u3044\u308b\u9593\u306b\uff0c\u97f3\u3060\u3051\u306b\u96c6\u4e2d\u3059\u308b\u3088\u3046\u306b\u6307\u793a\u3057\u3066\u304a\u308a\uff0c\u4f8b\u3048\u3070\u304a\u663c\u3054\u98ef\u306e\u3053\u3068\u3092\u8003\u3048\u3066\u3057\u307e\u3063\u305f\u3089\u305d\u306e\u6642\u306b\u30dc\u30bf\u30f3\u3092\u304a\u3059\u3088\u3046\u306b\u6307\u793a\u3057\u3066\u3044\u308b\uff0c\u3068\u56de\u7b54\u3057\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>12<\/strong><br \/>\n\u4e09\u83f1\u30b1\u30df\u30ab\u30eb\u30db\u30fc\u30eb\u30c7\u30a3\u30f3\u30b0\u30b9\u30b0\u30eb\u30fc\u30d7\u306e\u91d1\u5b50\u3055\u3093\u304b\u3089\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u7791\u60f3\u3068\u306f\u7121\u306b\u306a\u308b\u3082\u306e\u3067\u306f\u306a\u3044\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u5f13\u9053\u3067\u7684\u3092\u72d9\u3046\u3068\u304d\u306b\u7121\u306b\u306a\u308b\u3088\u3046\u306a\u3068\u304d\u3068\u540c\u3058\u3088\u3046\u306a\u611f\u3058\u304b\u3068\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\u304c\uff0c\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u30de\u30a4\u30f3\u30c9\u30d5\u30eb\u30cd\u30b9\u3068\u306f\u300c\u4eca\u3053\u306e\u77ac\u9593\u300d\u306b\u610f\u56f3\u7684\u306a\u6ce8\u610f\u3092\u5411\u3051\u308b\u3053\u3068\u3067\u3042\u308a\uff0c\u7121\u306b\u306a\u308b\u3053\u3068\u3068\u306f\u7570\u306a\u308b\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>13<\/strong><br \/>\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\u7791\u60f3\u306e\u7814\u7a76\u3068\u306f\u3088\u304f\u884c\u308f\u308c\u3066\u3044\u308b\u3082\u306e\u306a\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c\u7791\u60f3\u306e\u7814\u7a76\u306f\u884c\u308f\u308c\u3066\u3044\u308b\u304c\uff0c\u719f\u7df4\u8005\u306b\u304a\u3051\u308b\u7814\u7a76\u306b\u6bd4\u3079\u3066\u521d\u5fc3\u8005\u3092\u5bfe\u8c61\u3068\u3057\u305f\u7814\u7a76\u306f\u5c11\u306a\u3044\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>14<\/strong><br \/>\n\u6d5c\u677e\u533b\u79d1\u5927\u5b66\u306e\u5927\u661f\u5148\u751f\u304b\u3089\u8cea\u554f\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u3053\u3061\u3089\u306e\u8cea\u554f\u306f\uff0c\u6570\u3092\u6570\u3048\u308b\u3068\u4f55\u304b\u7d50\u679c\u304c\u7570\u306a\u308b\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0c2\u3064\u306e\u30bf\u30b9\u30af\u3069\u3061\u3089\u3068\u3082\u6570\u306f\u6570\u3048\u3066\u3044\u308b\u3053\u3068\u3092\u8aac\u660e\u3057\uff0c\u30bf\u30b9\u30af\u306e\u9055\u3044\u3092\u304a\u4f1d\u3048\u3057\u307e\u3057\u305f\uff0e\u305d\u3057\u3066\u7d50\u679c\u3068\u3057\u3066\uff0c\u8ce6\u6d3b\u3067\u306f\u9055\u3044\u304c\u898b\u3089\u308c\u306a\u304b\u3063\u305f\u304c\uff0c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3067\u306f\u6709\u610f\u306a\u5dee\u304c\u3042\u3063\u305f\u3053\u3068\u8aac\u660e\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>15<\/strong><br \/>\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\u3069\u306e\u3088\u3046\u306b\u30b3\u30f3\u30c8\u30e9\u30b9\u30c8\u3092\u7acb\u3066\u305f\u306e\u304b\uff0c2\u30bf\u30b9\u30af\u306e\u6bd4\u8f03\u306e\u307f\u3092\u884c\u3063\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\uff0cACT\u306e\u307f\uff0cBCT\u306e\u307f\uff0cAC\u3068BCT\u306e\u6bd4\u8f03\u3068\u3059\u3079\u3066\u306e\u30d1\u30bf\u30fc\u30f3\u3092\u691c\u8a0e\u3057\u305f\u304c\uff0c\u96c6\u56e3\u89e3\u6790\u3067\u306f\u8ce6\u6d3b\u9818\u57df\u306f\u898b\u3089\u308c\u306a\u304b\u3063\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<ul>\n<li>\u611f\u60f3<\/li>\n<\/ul>\n<p>\u79c1\u305f\u3061\u306e\u7814\u7a76\u5ba4\u3068\u3057\u3066\u3082\u521d\u3081\u3066\u53c2\u52a0\u3059\u308b\u5b66\u4f1a\u3067\uff0c\u3069\u3093\u306a\u5b66\u4f1a\u306a\u306e\u304b\u697d\u3057\u307f\u306b\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u79c1\u3068\u3057\u3066\u306f2\u5ea6\u76ee\u306e\u56fd\u969b\u5b66\u4f1a\u306e\u53c2\u52a0\uff0c\u305d\u3057\u3066\u6771\u4eac\u3067\u884c\u308f\u308c\u305f\u3053\u3068\u3082\u3042\u308a\uff0c\u524d\u56de\u306e\u56fd\u969b\u5b66\u4f1a\u307b\u3069\u7dca\u5f35\u306f\u305b\u305a\u81e8\u3080\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u521d\u65e5\u306b\u306feducational course\u306b\u3082\u53c2\u52a0\u3055\u305b\u3066\u3044\u305f\u3060\u304d\uff0cNIRS\u306e\u8a08\u6e2c\u3084\u51e6\u7406\u65b9\u6cd5\u306a\u3069\u3092\u518d\u5ea6\u78ba\u8a8d\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e2\u65e5\u76ee\u304b\u3089\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3082\u306f\u3058\u307e\u308a\uff0c\u8074\u8b1b\u3082\u305f\u304f\u3055\u3093\u3055\u305b\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0eNIRS\u306b\u3064\u3044\u3066\u306e\u5b66\u4f1a\u306e\u305f\u3081\uff0c\u4eca\u307e\u3067\u77e5\u3089\u306a\u304b\u3063\u305f\u89e3\u6790\u30bd\u30d5\u30c8\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u305f\u308a\uff0c\u4eca\u5f8c\u81ea\u5206\u305f\u3061\u306e\u7814\u7a76\u306b\u6d3b\u304b\u305b\u305d\u3046\u306a\u3053\u3068\u3082\u305f\u304f\u3055\u3093\u805e\u304f\u3053\u3068\u304c\u3067\u304d\uff0c\u3068\u3066\u3082\u8cb4\u91cd\u306a\u7d4c\u9a13\u3092\u3055\u305b\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u79c1\u306e\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u306f\u5b66\u4f1a\u6700\u7d42\u65e5\u3067\u3057\u305f\u304c\uff0c\u305f\u304f\u3055\u3093\u306e\u65b9\u304c\u805e\u304d\u306b\u6765\u3066\u304f\u3060\u3055\u308a\uff0c\u8cea\u554f\u3082\u305f\u304f\u3055\u3093\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u524d\u56de\u306b\u6bd4\u3079\u308b\u3068\u7dca\u5f35\u3082\u3057\u3059\u304e\u305a\u306b\u5bfe\u5fdc\u3067\u304d\u305f\u305f\u3081\uff0c\u51b7\u9759\u306b\u8cea\u554f\u3092\u805e\u304f\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3057\u304b\u3057\uff0c\u307e\u3060\u82f1\u8a9e\u529b\u304c\u4e4f\u3057\u304f\u8b70\u8ad6\u304c\u6df1\u3081\u3089\u308c\u306a\u3044\u5834\u9762\u3082\u3042\u308a\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u8a08\u753b\u6027\u304c\u8db3\u308a\u305a\u6e96\u5099\u3082\u304b\u306a\u308a\u304e\u308a\u304e\u308a\u3068\u306a\u3063\u3066\u3057\u307e\u3063\u305f\u3068\u3053\u308d\u3082\u53cd\u7701\u70b9\u3067\u3059\uff0e\u3057\u304b\u3057\uff0c\u4eca\u56de\u306e\u5b66\u4f1a\u3092\u901a\u3057\u3066\u76f4\u524d\u307e\u3067\u3084\u308a\u7d9a\u3051\u308b\u7c98\u308a\u5f37\u3055\u3092\u3055\u3089\u306b\u8eab\u306b\u3064\u3051\uff0c\u82f1\u8a9e\u529b\u5411\u4e0a\uff0c\u305d\u3057\u3066\u81ea\u5206\u306e\u7814\u7a76\u306b\u5bfe\u3059\u308b\u30e2\u30c1\u30d9\u30fc\u30b7\u30e7\u30f3\u3082\u4e0a\u3052\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u4eca\u5f8c\u6d3b\u304b\u3059\u3053\u3068\u304c\u3067\u304d\u308b\u3088\u3046\uff0c\u82f1\u8a9e\u529b\u3082\u9ad8\u3081\uff0c\u81ea\u5206\u306e\u7814\u7a76\u3082\u3055\u3089\u306b\u6df1\u3081\u306a\u304c\u3089\u9032\u3081\u3066\u3044\u304d\u305f\u3044\u3068\u5f37\u304f\u601d\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"3\">\n<li>\u8074\u8b1b<\/li>\n<\/ol>\n<p>\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e6\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000fNIRS Technology and Applications<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Robert J Cooper<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a fNIRS Training Course\uff0cPrinciples &amp; Methodology<br \/>\n&nbsp;<br \/>\nIn this session, I will outline the past, present and future of fNIRS technologies, with a specific emphasis on what are and what are not appropriate experimental applications of fNIRS methodologies. I will also review a number of key papers that have employed fNIRS technology over the last 25 years.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u306f\uff0c\u4eca\u307e\u3067\uff0c\u305d\u3057\u3066\u3053\u308c\u304b\u3089\u306efNIRS\u6280\u8853\u306e\u8aac\u660e\u3067\u3057\u305f\uff0e\u307e\u305aNIRS\u6280\u8853\u306b\u306f\u4e3b\u306a\u30ab\u30c6\u30b4\u30ea\u30fc\u304c4\u3064\u3042\u308b\u3068\u3044\u3046\u3068\u3053\u308d\u304b\u3089\u59cb\u307e\u308a\u307e\u3057\u305f\u304c\uff0c\u305d\u3053\u304b\u3089\u3088\u304f\u77e5\u3089\u306a\u304b\u3063\u305f\u306e\u3067\u52c9\u5f37\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u666e\u6bb5\u3042\u307e\u308a\u77e5\u308b\u3053\u3068\u306e\u306a\u3044\u30ec\u30fc\u30b6\u30fc\u3084\u30d5\u30a1\u30a4\u30d0\u306a\u3069\u306e\u30cf\u30fc\u30c9\u30a6\u30a7\u30a2\u306e\u8a71\u3082\u805e\u304f\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3055\u3089\u306b\uff0c\u4eca\u307e\u306725\u5e74\u9593\u306e\u91cd\u8981\u306a\u8ad6\u6587\u306e\u30ec\u30d3\u30e5\u30fc\u3082\u591a\u304f\u7d39\u4ecb\u3057\u3066\u304f\u3060\u3055\u3063\u305f\u306e\u3067\uff0c\u53c2\u8003\u306b\u3067\u304d\u308b\u3082\u306e\u3084\u8208\u5473\u304c\u3042\u308b\u3082\u306e\u3092\u81ea\u5206\u3067\u3082\u8aad\u3093\u3067\u307f\u3088\u3046\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Guide to the probabilistic spatial registration methods for fNIRS : Brain atlas handling<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Daiske Tsuzuki<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a fNIRS Training Course\uff0cMeasurement &amp; Analysis<br \/>\n&nbsp;<br \/>\nFunctional near-infrared spectroscopy (fNIRS) measures regional cerebral blood flow and monitors relative regional changes of hemoglobin concentration noninvasively from the head surface. On the other hand, fNIRS in a standalone setting lacks structural and anatomical information of the underlying brain. In this session, I will introduce both the concept of atlas model based on the standardized brain space such as Montreal Neurogical Institute (MNI) space, and methods to solve the spatial registration issue and realize the functional mapping at the gyrus level through the technical descriptions of Virtual spatial registration, Probabilistic registration, Anchor-based probabilistic registration, and Anatomical labeling.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u306f\uff0c\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u306e\u65b9\u6cd5\u306b\u95a2\u3057\u3066\u6559\u3048\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u79c1\u305f\u3061\u306e\u7814\u7a76\u5ba4\u3067\u306f\uff0cNIRS\u306eCH\u4f4d\u7f6e\u3092MNI\u6a19\u6e96\u8133\u5ea7\u6a19\u7cfb\u306b\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3059\u308b\u78ba\u7387\u7684\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u7528\u3044\u3066\u3044\u307e\u3059\u304c\uff0c\u305d\u306e\u4ed6\u306b\u3082\u4eee\u60f3\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3068\u3044\u3046\u65b9\u6cd5\u304c\u7d39\u4ecb\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u4eca\u307e\u3067\u805e\u3044\u305f\u3053\u3068\u306f\u3042\u308a\u307e\u3057\u305f\u304c\uff0c\u3042\u307e\u308a\u77e5\u3089\u306a\u304b\u3063\u305f\u306e\u3067\u3059\u3054\u304f\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\uff0e\u8a73\u7d30\u306f\u3042\u307e\u308a\u5206\u304b\u3089\u306a\u304b\u3063\u305f\u306e\u3067\uff0c\u53c2\u8003\u6587\u732e\u306a\u3069\u3082\u8aad\u3093\u3067\u3082\u3063\u3068\u8a73\u3057\u304f\u77e5\u308a\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aFunctional Connectivity Patterns in Monolingual and Bilingual Infants<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a B. Blanco, M. Molnar, E. Amico, M. Carreiras and C. Caballero-Gaudes<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Neonatal, pediatric &amp; developmental neuroscience I<br \/>\n&nbsp;<br \/>\nIntroduction. In this work we evaluated whether brain adaptations are induced by the effect of an early and continued exposure to a bilingual vs. a monolingual environment by testing between group differences in resting state functional connectivity (RSFC). We also assessed the reliability of our previous results by testing sleeping, as opposed to awake infants, in order to maximize signal quality.<br \/>\nMethods. Spontaneous hemodynamic activity was recorded (9 min.) using nearinfrared spectroscopy (NIRS) in 4-month-old infants (n=27 bilinguals, n=25 Spanish and n=26 Basque monolinguals). Within each group we measured the antiphase relationship between deoxy- (HbR) and oxyhemoglobin (HbO2), and perform a hierarchical spatio-temporal clustering. Network based statistics (NBS) (Zalesky et al., 2010) and connICA (Amico et al., 2017) procedures were also employed to explore differences in functional connectivity patterns between groups.<br \/>\nResults and Discussion. In our three experimental groups we observed an antiphase relationship between HbR and HbO2 (Fig. 1A) which resembles the results of Watanabe et al., (2017). The spatial configuration of clusters (Fig. 1B) across groups also demonstrates a high degree of consistency with previously reported results (Homae et al., 2010). These results were not replicated in our previous study in awake infants. We assume that our previously reported effects were probably caused by motion artifacts in the signal, and recognize the importance of correct data quality assessment in NIRS studies with infants to avoid this type of spurious results. Pairwise comparisons with NBS revealed a network (Fig. 1C) involving spatially homologous channels of both hemispheres showing stronger synchronization in Spanish monolingual infants than in Basque monolingual infants (p=0.04). The same difference between groups is also observed in HbO2 (p=0.04) in a network showing a similar spatial disposition. ConnICA revealed a FC pattern (Fig. 1C) showing a significantly larger presence in Spanish than in Basque monolingual infants, in HbR (p=0.04) and HbO2 (p=0.04), which resembles the results obtained with NBS. Despite their small effect, the observed between group differences are consistent across HbR and HbO2, and show a similar spatial pattern regardless of the procedure being employed.<br \/>\nWatanabe H. et al. (2017). Hemoglobin phase of oxygenation and\u3000deoxygenation in early brain development measured using fNIRS. Proc. Natl. Acad. Sci. 114(9), E1737\u2013E1744. Homae F. et al. (2010). Development of global cortical networks in early infancy. J. Neurosci. 30(14), 4877\u2013 4882. Zalesky A. et al. (2010). Network-based statistic: identifying differences in brain networks. Neuroimage, 53(4), 1197-1207. Amico E. et al. (2017). Mapping the functional connectome traits of levels of consciousness. NeuroImage, 148, 201-211.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u7814\u7a76\u306f\uff0c\u5358\u4e00\u8a00\u8a9e\u3068\u4e8c\u8a00\u8a9e\u306e\u5e7c\u5150\u306b\u304a\u3051\u308b\u6a5f\u80fd\u7684\u30b3\u30cd\u30af\u30c6\u30a3\u30d3\u30c6\u30a3\u306e\u30d1\u30bf\u30fc\u30f3\u306b\u3064\u3044\u3066\u306e\u5185\u5bb9\u3067\u3057\u305f\uff0e\u30b3\u30cd\u30af\u30c6\u30a3\u30d3\u30c6\u30a3\u306e\u30d1\u30bf\u30fc\u30f3\u3092\u8abf\u3079\u308b\u969b\u306b\uff0c\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u3060\u3051\u3067\u306f\u306a\u304f\uff0c\u30c7\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u3082\u7528\u3044\u3066\u89e3\u6790\u3055\u308c\u3066\u3044\u307e\u3057\u305f\uff0e\u4eca\u307e\u3067\u30c7\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u306e\u30c7\u30fc\u30bf\u306b\u3064\u3044\u3066\u306f\u7528\u3044\u3066\u3044\u306a\u304b\u3063\u305f\u306e\u3067\uff0c\u4eca\u5f8c\u4ed6\u306e\u8ad6\u6587\u3067\u3082\u8abf\u67fb\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u3068\u30c7\u30aa\u30ad\u30b7\u30d8\u30e2\u30b0\u30ed\u30d3\u30f3\u306e\u4f4d\u76f8\u5dee\u306b\u3064\u3044\u3066\u3082\u8ff0\u3079\u3089\u308c\u3066\u3044\u307e\u3057\u305f\u304c\uff0c\u306f\u3058\u3081\u3066\u898b\u3066\u7406\u89e3\u3057\u304d\u308c\u306a\u304b\u3063\u305f\u306e\u3067\u5b66\u3093\u3067\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Dynamics of Functional Networks in the Developing Brain<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Fumitaka Homae<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Neonatal, pediatric &amp; developmental neuroscience I [invited talk]<br \/>\nIntroduction: Structural and functional organization of the brain occurs rapidly in early infancy. Previous studies report that in neonates and young infants, this neural organization is sensitive to speech sounds, and related functions in distinct brain regions have been partially elucidated (Homae et al., 2014). It is known that short speech sounds induce eventrelated activation in the temporal brain regions in young infants; increases in oxygenated hemoglobin (oxy-Hb) signals are followed by signal decreases to the onset level within a 10- to 20-second time scale. We can also visualize the static aspects of functional relationships, such as correlations between spontaneous activations in homologous regions (Homae et al., 2010). However, we have limited information on the dynamics of cortico-cortical interactions during the presentation of speech sounds to infants. In the present study, we calculated the dynamic functional connectivity (dFC) of cortical activation in neonates and 3- and 6-monthold infants in response to short sentences in Japanese. We hypothesized that functional relationships will not be constant, but will instead be modulated, during typical cortical hemodynamic responses to speech sounds. We further predicted that functional connectivity between distant cortical regions would change from a local to a global state depending on the stage of development.<br \/>\nMethods: We analyzed data obtained from quietly sleeping neonates (N = 28) and 3- and 6- month-old infants (N = 26 and 27, respectively). We presented auditory sentences while measuring brain activation using 94-channel fNIRS (ETG-7000, Hitachi). The continuous oxy-Hb signals were band-pass filtered from 0.01 to 0.2 Hz. The signal changes in response to speech sounds were examined by averaging the signals over segmented data blocks. We applied the Hilbert transform to the continuous data to estimate the phase of the signals in all channels. We defined dFC using the following equation (Cabral et al., 2017): dFC(p, q, t) = cos(\u03b8(p,t) \u2013 \u03b8(q,t)), where p and q are channels and t is a time point.<br \/>\nResults and Discussion: We found that the frontal and temporal regions in all participant groups demonstrated increases in oxy-Hb signals when the sentences were presented. In addition, 3- and 6-month-old infants exhibited similar changes in the occipital regions, as in our previous studies (Homae et al., 2011; Taga et al., 2018). The dFC between homologous regions increased with age, consistent with our previous findings (Homae et al., 2010). Although frontal regions exhibit dense clusters in all groups, clusters over the temporal, parietal, and occipital regions were observed only in 3- and 6-month-old infants. Overall, we found that the dFC between the frontal and temporal regions changed with the presentation of speech sounds, and the organization of functional networks depended on age. These results support our hypotheses and suggest that the dynamics of functional networks will help in revealing how infants hear speech sounds and acquire their native language.<br \/>\nAcknowledgements: This study was partly supported by Japan Society for Promotion of Science KAKENHI Grant Nos. JP16H06524, JP16H06525 and 26220004.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>NIRS\u3067\u65e9\u3044\u6642\u671f\u304b\u3089\u7d50\u5408\u89e3\u6790\u3092\u3055\u308c\u3066\u3044\u308b\u4fdd\u524d\u5148\u751f\u306e\uff0c\u52d5\u7684\u6a5f\u80fd\u7684\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u3064\u3044\u3066\u306e\u767a\u8868\u3067\u3057\u305f\uff0e\u7d50\u679c\u3068\u3057\u3066\uff0c\u767a\u8a71\u97f3\u63d0\u793a\u306b\u4f34\u3046\u6a5f\u80fd\u7684\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u69cb\u6210\u306f\u5e74\u9f62\u306b\u4f9d\u5b58\u3059\u308b\u3068\u306e\u3053\u3068\u3067\uff0c\u975e\u5e38\u306b\u8208\u5473\u6df1\u304b\u3063\u305f\u3067\u3059\uff0e\u4eca\u56de\uff0c3\u30f6\u6708\u30686\u30f6\u6708\u306e\u4e73\u5150\u3092\u5bfe\u8c61\u3068\u3057\u3066\u5b9f\u9a13\u3092\u884c\u3063\u3066\u3044\u307e\u3057\u305f\u304c\uff0c\u305f\u3063\u305f3\u30f6\u6708\u3067\u5909\u5316\u304c\u8d77\u3053\u308b\u3053\u3068\u306b\u9a5a\u304d\u307e\u3057\u305f\uff0e\u307e\u305f\uff0c\u7814\u7a76\u5ba4\u3067\u3082\u7528\u3044\u3089\u308c\u3066\u3044\u308b\u52d5\u7684\u89e3\u6790\u3092\u3084\u3089\u308c\u3066\u3044\u305f\u306e\u3067\u52d5\u7684\u89e3\u6790\u306e\u30e1\u30ea\u30c3\u30c8\u3082\u77e5\u3063\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000NIRSTORM, a Brainstorm plugin inspired by electrophysiology dedicated to fNIRS data analysis, advanced 3D reconstructions and optimal probe design<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a T. Vincent, Z. Cai, F. Tadel, A. Spilkin, A. Machado, S. Baillet, L. Bherer, J.M. Lina, C. Grova<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Data analysis &amp; algorithms<br \/>\n&nbsp;<br \/>\nAbstract: Measurements of bioelectrical activity using EEG or hemodynamic processes using fNIRS enable wearable neuroimaging in realistic lifestyle and clinical conditions. Despite measuring different physiological signals, EEG and fNIRS are sharing several similarities: (i) they consist in scalp measurements, (ii) they offer an excellent temporal resolution, (iii) their spatial resolution is limited and 3D reconstruction of the generators of these scalp recordings requires solving an ill-posed inverse problem. Brainstorm software is internationally recognized for EEG\/MEG processing [Tadel et al. Comp Intell Neurosci 2011], featuring advanced databasing, visualization, signal processing, source localization and statistical analysis methods. Benefiting from powerful ergonomic features available in Brainstorm, we are proposing NIRSTORM, a plugin dedicated to fNIRS data analysis.<br \/>\nMethods: NIRSTORM provides classical channel-space fNIRS processing consisting in band pass filtering, Modified Beer-Lambert Law, motion correction and window averaging. To allow advanced fNIRS modeling, NIRSTORM is now featuring integration with MCXLab software [Fang and Boas Opt. Express 2009] to estimate light sensitivity profiles within head tissue, using head models derived either from a standard template MRI (Colin 27) or a subject-specific MRI. Segmentation of the template was carefully computed and accurate Monte Carlo simulations were launched to generate fluence data for 690 and 830 nm wavelengths. This fluence template consists in ~6000 head vertices with a spatial resolution of ~5mm (Fig.A). Using light sensitivity profiles estimated from any vertex of the scalp, we implemented our proposed personalized optimal montage design targeting a predefined brain region. This method consists in linear programming optimization maximizing light sensitivity to the target region, while ensuring spatial overlap between sensors to allow local 3D reconstruction [Machado et al JBO 2014, JNS-Meth. in rev, Pellegrino et al Front. Neurosc. 2016] (Fig.B: optimal montages targeting the hand knob). The optimal montage can be estimated from the MRI template or from an individual MRI, using any freely defined optode position available on the scalp or positions from the 10\/20 system. Integration within Brainstorm allowed adapting to NIRS advanced 3D reconstruction methods we developed and validated for EEG\/MEG source imaging [Pellegrino et al HBM 2018] within the Maximum Entropy on the Mean framework [Cai et al submitted] (Fig.C: 3D reconstruction for a visual task, left checkerboard reversal).<br \/>\nConclusion: NIRSTORM is an open-source initiative and welcomes any contribution. It is currently hosted on github(https:\/\/github.com\/Nirstorm\/nirstorm), where the wiki pages of our first training session organized in Montreal in May 2018 are available. We expect NIRSTORM to become an ideal platform for multimodal EEG\/fNIRS integration.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u306f\uff0cNIRSTORM\u3068\u3044\u3046NIRS\u3084EEG\u306e\u30c7\u30fc\u30bf\u51e6\u7406\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u308b\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u306b\u3064\u3044\u3066\u3067\u3057\u305f\uff0e\u3053\u306e\u30bd\u30d5\u30c8\u306fBrainstorm\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u304b\u3089\u958b\u767a\u3055\u308c\u305f\u3082\u306e\u3067\u3042\u308a\uff0c\u7d50\u5408\u89e3\u6790\u3082\u53ef\u80fd\u3068\u306e\u3053\u3068\u3067\u3057\u305f\uff0e\u5b66\u4f1a\u306e\u76f4\u524d\u306b\u306f\u3058\u3081\u3066\u77e5\u308a\uff0c\u307e\u3060\u307b\u3068\u3093\u3069\u77e5\u3089\u306a\u304b\u3063\u305f\u305f\u3081\u8208\u5473\u3092\u6301\u3061\u307e\u3057\u305f\uff0e\u4fbf\u5229\u306a\u30bd\u30d5\u30c8\u3060\u3068\u601d\u3046\u306e\u3067\uff0c\u3069\u3093\u306a\u51e6\u7406\u304c\u3067\u304d\u308b\u306e\u304b\u3092\u77e5\u308b\u3068\u3068\u3082\u306b\u89e6\u308c\u3066\u307f\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a The Role of Mirror Neuron System in Encoding Motor Complexity<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Xinge Li, Manon A. Krol, Sahar Jahani, David A. Boas, Helen Tager-Flusberg\u3000and Meryem A. Y\u00fccel<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Cognitive &amp; social neuroscience<br \/>\nBackground: The mirror neuron system (MNS), including pars opercularis of the inferior frontal gyrus (IFG) and adjacent ventral premotor cortex (PMv) and inferior parietal lobule (IPL), is activated when individuals execute an action and when they observe a similar action performed by another individual\u00b9. Converging neuroimaging evidence has shown the functional role of the MNS in action understanding. Although most studies have focused on the effects of modulations in goals and kinematics of observed actions on MNS activity, little research has explored the effects of manipulations in motor complexity. Thus, the present study adopted fNIRS to examine MNS activity, aiming to better understand the functional role of this system in encoding motor complexity. We hypothesized that, compared with observed and executed simple actions, MNS will activate more during observed and executed complex actions in order to reinforce motor planning and precision.<br \/>\nMethods: Twenty-one healthy adults executed as well as observed two hand actions that differed in motor complexity. The simple action was to place a card into an open box, while the complex action was to insert a card into a box with a narrow slot on the lid (Fig.1 c-f). MNS activity was recorded by an fNIRS system with 16 sources and 24 long-separation and 8 short-separation detectors. Hemodynamic response function was estimated by a general linear model with short separation regression.<br \/>\nResults: Our results show that the observation complex and execution complex tasks both resulted in stronger brain response in the ipsilateral mirror neuron regions compared to contralateral. Motor complexity, represented as the contrast between the simple and complex task conditions, on the other hand, is represented in IFG, IPL and motor regions during execution and in IPL and motor regions during observation (Fig.2). Discussion: Our findings suggest that the MNS encodes motor representation of varying motor complexity in the observed and executed actions and facilitates action understanding in a direct, pre-cognitive and motor-based way.<br \/>\nReferences 1. Rizzolatti, G., &amp; Sinigaglia, C. (2016). The mirror mechanism: A basic principle of brain function. Nature Reviews Neuroscience, 17(12), 757\u2013765.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u306f\uff0c\u30df\u30e9\u30fc\u30cb\u30e5\u30fc\u30ed\u30f3\u30b7\u30b9\u30c6\u30e0\u306e\u5f79\u5272\u306b\u3064\u3044\u3066\u8abf\u3079\u3066\u3044\u307e\u3057\u305f\uff0e\u305d\u306e\u305f\u3081\u306b\uff0c\u8907\u96d1\u3055\u304c\u7570\u306a\u308b2\u3064\u306e\u624b\u306e\u52d5\u304d\u3092\u30bf\u30b9\u30af\u3068\u3057\u3066\u7528\u3044\u3066\u3044\u307e\u3057\u305f\u304c\uff0c\u624b\u306e\u52d5\u304d\u3092\u3059\u308b\u3053\u3068\u306b\u3088\u3063\u3066\u982d\u3082\u52d5\u3044\u3066\u3057\u307e\u3044\uff0c\u4f53\u52d5\u304c\u4e57\u3063\u3066\u3044\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u3068\u601d\u3044\u6c17\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u30d7\u30ed\u30fc\u30d6\u914d\u7f6e\u306e\u56f3\u306a\u3069\uff0c\u767a\u8868\u3059\u308b\u898b\u305b\u65b9\u306b\u304a\u3044\u3066\u53c2\u8003\u306b\u3067\u304d\u308b\u70b9\u3082\u3042\u3063\u305f\u306e\u3067\u6d3b\u304b\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<br \/>\n\u53c2\u8003\u6587\u732e<\/p>\n<ul>\n<li>fNIRS2018\uff0c http:\/\/fnirs2018.org\/<\/li>\n<\/ul>\n<p><strong>\u5b66\u4f1a\u53c2\u52a0\u5831\u544a\u66f8<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"147\"><strong>\u00a0<\/strong><br \/>\n<strong>\u5831\u544a\u8005\u6c0f\u540d<\/strong><\/td>\n<td width=\"373\">&nbsp;<br \/>\n\u8c37\u53e3\u3000\u5c1a<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">\u5354\u8abf\u8ab2\u984c\u6642\u306e\u8133\u9593\u795e\u7d4c\u540c\u671f\u306efNIRS\u3092\u7528\u3044\u305fhyperscanning\u306e\u7814\u7a76<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u767a\u8868\u8ad6\u6587\u82f1\u30bf\u30a4\u30c8\u30eb<\/strong><\/td>\n<td width=\"373\">A fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8457\u8005<\/strong><\/td>\n<td width=\"373\">Megumi Mizuno, Sho Taniguchi, Satoru Hiwa, Tomoyuki Hiroyasu<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4e3b\u50ac<\/strong><\/td>\n<td width=\"373\">The Society for fNIRS<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u8b1b\u6f14\u4f1a\u540d<\/strong><\/td>\n<td width=\"373\">fNIRS2018<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u4f1a\u5834<\/strong><\/td>\n<td width=\"373\">\u6771\u4eac\u5927\u5b66\u3000\u672c\u90f7\u30ad\u30e3\u30f3\u30d1\u30b9<\/td>\n<\/tr>\n<tr>\n<td width=\"147\"><strong>\u958b\u50ac\u65e5\u7a0b<\/strong><\/td>\n<td width=\"373\">2018\/10\/05-2018\/10\/08<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n<ol>\n<li>\u8b1b\u6f14\u4f1a\u306e\u8a73\u7d30<\/li>\n<\/ol>\n<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u304b\u3051\u3066\uff0c\u6771\u4eac\u5927\u5b66\u672c\u90f7\u30ad\u30e3\u30f3\u30d1\u30b9\u306b\u3066\u958b\u50ac\u3055\u308c\u307e\u3057\u305ffNIRS2018\u306b\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u3053\u306e\u5b66\u4f1a\u306f\uff0cThe Society for fNIRS\u306b\u3088\u3063\u3066\u4e3b\u50ac\u3055\u308c\uff0c\u5149\u5b66\u7684\u65b9\u6cd5\u3092\u7528\u3044\u3066\u751f\u7269\u7d44\u7e54\uff0c\u7279\u306b\u8133\u306e\u6a5f\u80fd\u7279\u6027\u3092\u7406\u89e3\u3057\u3088\u3046\u3068\u3059\u308b\u57fa\u790e\u79d1\u5b66\u8005\u304a\u3088\u3073\u81e8\u5e8a\u79d1\u5b66\u8005\u306e\u96c6\u307e\u308a\u3067\uff0c\u30a2\u30a4\u30c7\u30a2\u306e\u4ea4\u63db\uff0c\u5b66\u969b\u7684\u5354\u529b\uff0c\u6559\u80b2\u3092\u4fc3\u9032\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u306b\u958b\u50ac\u3055\u308c\u3066\u3044\u307e\u3059\uff0e<br \/>\n\u79c1\u306f2018\/10\/05\u304b\u30892018\/10\/08\u306e\u5168\u65e5\u53c2\u52a0\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u672c\u7814\u7a76\u5ba4\u304b\u3089\u306f\u4ed6\u306b\u5ee3\u5b89\u5148\u751f\uff0c\u65e5\u548c\u5148\u751f\uff0c\u6c60\u7530\uff0c\u897f\u6fa4\uff0c\u6c34\u91ce\uff0c\u5c71\u672c\u304c\u53c2\u52a0\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<ol start=\"2\">\n<li>\u7814\u7a76\u767a\u8868\n<ul>\n<li>\u767a\u8868\u6982\u8981<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\u79c1\u306f10\/07\u306ePoster Session\u300cPoster\u2161\u300d\u306b\u3066\u6c34\u91ce\u3068\u5171\u306b\u767a\u8868\u3044\u305f\u3057\u307e\u3057\u305f\uff0e\u767a\u8868\u306e\u5f62\u5f0f\u306f\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\uff0c\u5348\u524d\uff0c\u5348\u5f8c\u5171\u306b\uff11\u6642\u9593\u305a\u3064\u81ea\u7531\u306b\u767a\u8868\u3068\u8cea\u7591\u5fdc\u7b54\u3092\u884c\u3046\u6642\u9593\u3068\u306a\u3063\u3066\u304a\u308a\u307e\u3057\u305f\uff0e<br \/>\n\u4eca\u56de\u306e\u767a\u8868\u306f\uff0c\u300cA fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task\u300d\u3067\u3059\uff0e\u4ee5\u4e0b\u306b\u6284\u9332\u3092\u8a18\u8f09\u81f4\u3057\u307e\u3059\uff0e<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">Introduction: Social interaction is a dynamic behavior between individuals who modify their actions and reactions depending on the actions of their partner. In this study, we investigate the relationship between social interaction and brain functions. Cui et al. analyzed the neural synchronization between two subjects who played a cooperation game involving synchronizing each other\u2019s response timing and revealed that the interpersonal brain coherence of the subjects increased during the cooperative task [1]. In this study, to easily facilitate the cooperative behavior of the participants, we improved the experimental design and examined the inter-brain neural synchronization during the cooperative task.<br \/>\nMethods: Twenty-two healthy adult males (11 pairs, age: 22.7 \u00b1 1.0 years old, right-handed) participated in this experiment. The experimental environment is shown in Fig 1. The brains of the two participants during their social interaction were simultaneously measured by hyperscanning using a single functional near-infrared spectroscopy (fNIRS) device (ETG-7100, Hitachi, Ltd.). A 3 \u00d7 10 probe consisting of 47 measurement channels was attached to the forehead of each subject. Participants were instructed: (1) to synchronize the response timing of their partner after the cue (synchronization task), (2) to respond faster than their partner (competition task), and (3) to respond quickly to the cue (single A\/B task) [1]. In the synchronization task, the time difference between the responses of the two participants were fed back to each of them. Each participant predicted his partner&#8217;s behavior based on the time difference, and was asked to synchronize his responses at the next cue. Wavelet transform coherence was calculated from two sets of time-series data of cerebral blood flow changes. Then we performed a one-sample t-test (p &lt; 0.05) of the coherence increase of each task and investigated the brain regions where the coherence increased.<br \/>\nResults &amp; Discussion: The difference in response time between the two participants in the synchronization task was significantly larger than that of the single A and B task (p &lt; 0.05). This result indicates that the participants not only responded quickly to the cue, but also reacted by anticipating the behavior of their opponents. A t-score map of coherence increase is shown in Fig 2. The coherence within the left superior frontal gyrus (SFG) and left middle frontal gyrus (MFG) increased significantly in the synchronization task. The left SFG is involved in building a trust relationship [2]. Hence, it is assumed that this region affects cooperative behavior. Furthermore, the coherence in these two regions did not increase significantly in either the competitive or single task. Therefore, we suggest that the inter-brain synchronization in these brain regions can be utilized as a metric of cooperativeness.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<ul>\n<li>\u8cea\u7591\u5fdc\u7b54<\/li>\n<\/ul>\n<p>\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<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>1<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\nSingle\u8ab2\u984c\u306e\u7d50\u679c\u306b\u5bfe\u3057\u3066\u3069\u306e\u3088\u3046\u306b\u8003\u3048\u3066\u3044\u308b\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u540c\u3058\u72b6\u614b\u3067\u3042\u308b\u3068\u8003\u3048\u3066\u3044\u305fSingleA\u8ab2\u984c\u3068SingleB\u8ab2\u984c\u306e\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u5897\u52a0\u91cf\u306et-map\u304c\u7570\u306a\u3063\u3066\u304a\u308a\uff0c\u3053\u308c\u306f\u5404\u88ab\u9a13\u8005\u3092\u5bfe\u8c61\u306b\u3057\u3066\u3068\u3063\u305fEQS\u306e\u30a2\u30f3\u30b1\u30fc\u30c8\u7d50\u679c\u304b\u3089\uff0c\u500b\u4eba\u306e\u6027\u8cea\u306a\u3069\u306e\u9055\u3044\u304c\u5f71\u97ff\u3092\u4e0e\u3048\u305f\u3068\u8003\u3048\u3066\u3044\u308b\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>2<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\nSynchronization\u8ab2\u984c\u306e\u5f71\u97ff\u3068\u307f\u306a\u3057\u305f\u3082\u306e\u304c\u305d\u306e\u8ab2\u984c\u306b\u3088\u308b\u5f71\u97ff\u3060\u3068\u306f\u5206\u304b\u3089\u306a\u3044\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u306f\u540c\u3058\u76f8\u624b\u3092\u5fc5\u8981\u3068\u3059\u308bCompetition\u8ab2\u984c\u3068\u6bd4\u8f03\u3092\u3057\uff0cCompetition\u8ab2\u984c\u306b\u73fe\u308c\u3066\u3044\u306a\u3044\u3082\u306e\u304cSynchronization\u8ab2\u984c\u306e\u5f71\u97ff\u3067\u3042\u308b\u3068\u307f\u306a\u3057\u305f\u3068\u304a\u7b54\u3048\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>3<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\n\u306a\u305c\u524d\u982d\u90e8\u3092\u6e2c\u5b9a\u3057\u305f\u306e\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u3053\u306e\u8cea\u554f\u306b\u5bfe\u3057\u3066\u306f\uff0c\u307e\u305a\u306f\u53c2\u8003\u306b\u3057\u305f\u5148\u884c\u7814\u7a76\u3067\u6e2c\u5b9a\u3057\u3066\u3044\u305f\u524d\u982d\u90e8\u3092\u4e2d\u5fc3\u306b\u3088\u308a\u591a\u304f\u306e\u9818\u57df\u3092\u8a08\u6e2c\u3057\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e\u73fe\u5728\u306f\u5074\u982d\u982d\u9802\u63a5\u5408\u90e8\u306a\u3069\u3092\u6e2c\u5b9a\u3057\u3066\u3044\u308b\u793e\u4f1a\u6027\u306ehyperscanning\u7814\u7a76\u3082\u591a\u3005\u3042\u308b\u305f\u3081\uff0c\u4eca\u5f8c\u306f\u3055\u3089\u306b\u6587\u732e\u3092\u8abf\u67fb\u3057\u3066\u95a2\u5fc3\u9818\u57df\u306b\u3064\u3044\u3066\u6c7a\u3081\u3066\u3044\u304f\u5fc5\u8981\u304c\u3042\u308b\u3068\u8003\u3048\u3066\u3044\u307e\u3059\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>4<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\nWavelet\u5909\u63db\u306b\u3088\u308b\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u3068\u79fb\u52d5\u7a93\u3092\u7528\u3044\u305fFourier\u5909\u63db\u306b\u3088\u308b\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u3092\u6c42\u3081\u305f\u306e\u306f\u305d\u306e\u9055\u3044\u3092\u898b\u305f\u304b\u3063\u305f\u305f\u3081\u304b\u3068\u3044\u3046\u3082\u306e\u3067\u3057\u305f\uff0e\u305d\u306e\u9055\u3044\u306e\u691c\u8a0e\u306b\u306f\u307e\u3060\u81f3\u3063\u3066\u304a\u3089\u305a\uff0c\u307e\u305a\u306f\u4e21\u65b9\u306e\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u304b\u3089\u5f97\u3089\u308c\u308b\u7d50\u679c\u306b\u95a2\u3057\u3066\u7dcf\u5408\u7684\u306b\u8003\u5bdf\u3092\u884c\u3063\u305f\u3068\u56de\u7b54\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n<strong>\u30fb\u8cea\u554f\u5185\u5bb9<\/strong><strong>5<\/strong><br \/>\n\u8cea\u554f\u8005\u306e\u6c0f\u540d\u3092\u63a7\u3048\u640d\u306d\u3066\u3057\u307e\u3044\u307e\u3057\u305f\uff0e<br \/>\n\u9055\u3046\u8ab2\u984c\u3068\u306e\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u3092\u7b97\u51fa\u3057\u6bd4\u8f03\u3059\u308b\u3053\u3068\u3067\u7d50\u679c\u306e\u4fe1\u983c\u6027\u304c\u5897\u3059\u306e\u3067\u306f\u306a\u3044\u304b\u3068\u3054\u610f\u898b\u3092\u3044\u305f\u3060\u304d\u307e\u3057\u305f\uff0e\u73fe\u5728\u306f\u540c\u3058\u8ab2\u984c\u306e\u540c\u3058CH\u3067\u8a55\u4fa1\u3092\u884c\u3063\u3066\u3044\u307e\u3059\u304c\uff0c\u3054\u6307\u6458\u3044\u305f\u3060\u3044\u305f\u3088\u3046\u306b\u8ab2\u984c\u306e\u5f71\u97ff\u304c\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u306b\u73fe\u308f\u308c\u305f\u3053\u3068\u3092\u88cf\u4ed8\u3051\u308b\u305f\u3081\u306b\u3082\u305d\u306e\u3088\u3046\u306a\u3053\u3068\u3092\u4eca\u5f8c\u691c\u8a0e\u3057\u3066\u3044\u304f\u5fc5\u8981\u304c\u3042\u308b\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<\/p>\n<ul>\n<li>\u611f\u60f3<\/li>\n<\/ul>\n<p>\u4eca\u56de\u306f\uff12\u5ea6\u76ee\u306e\u5b66\u4f1a\u53c2\u52a0\u3067\u306f\u3042\u308a\u307e\u3057\u305f\u304c\u521d\u306e\u56fd\u969b\u5b66\u4f1a\u3067\u3042\u308a\uff0c\u30dd\u30b9\u30bf\u30fc\u767a\u8868\u3067\u3057\u305f\uff0e\u6700\u521d\u306f\u82f1\u8a9e\u3068\u3044\u3046\u3053\u3068\u3082\u3042\u308a\u7dca\u5f35\u3057\u3066\u306a\u304b\u306a\u304b\u601d\u3046\u3088\u3046\u306b\u81ea\u5206\u306e\u4f1d\u3048\u305f\u3044\u3053\u3068\u3092\u4f1d\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\uff0e\u3057\u304b\u3057\uff0c\u6163\u308c\u3066\u3044\u304f\u306b\u3064\u308c\uff0c\u81ea\u5206\u304b\u3089\u7a4d\u6975\u7684\u306b\u58f0\u3092\u304b\u3051\u8b70\u8ad6\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\uff0c\u697d\u3057\u3081\u307e\u3057\u305f\uff0e\u540c\u3058\u5206\u91ce\u306e\u65b9\u3068\u8a71\u3059\u6a5f\u4f1a\u304c\u7814\u7a76\u5ba4\u5916\u3067\u306f\u3042\u307e\u308a\u306a\u304b\u3063\u305f\u305f\u3081\uff0c\u767a\u8868\u3084\u8074\u8b1b\u3092\u901a\u3057\u3066\u65b0\u305f\u306a\u6c17\u3065\u304d\u3084\u5b66\u3073\u304c\u3042\u308b\u3068\u3068\u3082\u306b\uff0c\u81ea\u5206\u306e\u7814\u7a76\u3092\u3088\u308a\u5ba2\u89b3\u7684\u306b\u898b\u3064\u3081\u76f4\u3059\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e\u3057\u3063\u304b\u308a\u632f\u308a\u8fd4\u308a\u3092\u884c\u3044\uff0c\u4eca\u56de\u306e\u5b66\u4f1a\u53c2\u52a0\u3092\u901a\u3057\u3066\u5f97\u3089\u308c\u305f\u3082\u306e\u3092\u81ea\u5206\u306e\u307f\u306a\u3089\u305a\u7814\u7a76\u5ba4\u5168\u4f53\u306b\u9084\u5143\u3057\u3066\u3044\u304d\u305f\u3044\u3067\u3059\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<ol start=\"3\">\n<li>\u8074\u8b1b<\/li>\n<\/ol>\n<p>\u4eca\u56de\u306e\u8b1b\u6f14\u4f1a\u3067\u306f\uff0c\u4e0b\u8a18\u306e\uff14\u4ef6\u306e\u767a\u8868\u3092\u8074\u8b1b\u3057\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a\u3000Verifying wavelet coherence analysis to measure neural coupling using pseudo-random visual stimulation sequences and fNIRS<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Xian Zhang, J. Adam Noah, Swethasri Dravida, Joy Hirsch<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster\u2160<br \/>\nAbstruct\u00a0\u00a0\u00a0 \uff1a Neural mechanisms that underlie dynamic interpersonal interactions are thought to include temporally synchronous signals that reflect coupled processes between two brains [1]. Wavelet coherence analysis of hemodynamic signals acquired simultaneously during hyper-scanning experiments has been proposed for analysis of these neural processes [2,3]. However, this computational approach has not been validated against known markers. Here we generate a set of known neural coherences using pseudo random sequences of reversing checkerboard patterns. It is expected that input sequences that were more highly correlated generated higher cross-brain output correlations of wavelets in the visual cortex across pairs of subjects. Each visual stimulus event was a 2-second full-field reversing checkerboard pattern. Three random sequences, called sequence A, B and C (inset in figure), of such visual stimuli were presented for 2 minutes and repeated twice. The sequences were generated to have varying levels of correlation (e g: A-B more correlated than A-C). The expected coherence (left panel) was obtained by coherence analysis on the modeled fNIRS waveform, which was generated by convolving the stimulus sequence and the hemodynamic response function (HRF).The overall<br \/>\nexpected coherence is summarized as the average coherence within 0-30 second wavelength range (horizontal lines and numbers in left panel). Ten subjects participated. Subject\u2019s data were randomly paired with every other subject\u2019s data, resulting in ninety possible pairs. The combinations included A-A, B-B, or C-C, where both subjects viewed identical sequences of the stimuli (green). The other pairings were A- B (red), A-C (blue) and B-C (cyan). The wavelet coherence results from measured fNIRS deOxyHB data (right panel) confirmed the expected coherence. Our results validate wavelet coherence as a technique for quanitfying the coherence of brain signals across participants during hyperscanning to study social interaction in ecologically valid paradigms.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u306fhyperscanning\u7814\u7a76\u3067\u3088\u304f\u4f7f\u308f\u308c\u3066\u3044\u308bwavelet coherence\u89e3\u6790\u306e\u691c\u8a3c\u3092\u884c\u3063\u3066\u3044\u307e\u3057\u305f\uff0e\u7a7a\u9593\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3055\u308c\u305f\u30c7\u30fc\u30bf\u306e\u65b9\u304c\u751f\u30c7\u30fc\u30bf\u3088\u308a\u3082\u672c\u6765\u306e\u4e88\u6e2c\u3055\u308c\u305f\u30b3\u30d2\u30fc\u30ec\u30f3\u30b9\u306e\u5024\u3092\u3088\u308a\u3088\u304f\u8868\u3057\u3066\u3044\u308b\u3068\u306e\u3053\u3068\u3067\u3057\u305f\uff0e\u4eca\u5f8c\u306e\u89e3\u6790\u65b9\u6cd5\u306a\u3069\u306b\u53c2\u8003\u306b\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aTransition of phase synchrony of fNIRS signals depending on sleep states in infants<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a G. Taga, H. Watanabe, R. Saji, F. Homae<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster\u2162<br \/>\nAbstruct\u00a0\u00a0\u00a0 \uff1a Sleep reflects spontaneous activity of the brain and includes sleep state transitions such as NREM sleep and REM sleep. The gold standard for classification of sleep state is to use electroencephalogram (EEG) and electrooculogram (EOG). On the other hand, fNIRS can measure brain tissue oxygenation dynamics related to spontaneous activity of the brain and is expected to provide complementary information to the electric method with respect to the sleep state. Especially, studying infants\u2019 sleep is important for elucidating the developmental mechanism of the brain. fNIRS has been used to study spontaneous activity (Taga et al. 2000), stimulus induced activity (Taga et al. 2018), functional network (Homae et al. 2010), and hemoglobin phase of oxygenation and deoxygenation (hPod) (Watanabe et al. 2017) in sleeping infants. The present study aims to clarify the spatiotemporal dynamics of spontaneous activity of the brain according to sleep state of infants using fNIRS.<br \/>\nWe measured 2- and 3-month-old infants. 94 channel probe of the NIRS device (ETG 7000, Hitachi) and the electrodes of electroencephalogram (EEG) and electrooculogram (EOG) were attached to infants while they were naturally sleeping in the laboratory in the daytime. Measurement was terminated when the infant woke up or when 25 minutes passed while sleeping. Sleep states were classified into active sleep (AS), quiet sleep (QS), AS\/QS and wake every 30 seconds using EEG, EOG and video recordings. Data on infants whose sleeping states showed transition from AS to QS, each of which lasted more than 10 minutes, were selected, and 16 2-month-old (2M) and 19 3-month-old (3M) infants were used for the further analysis. Time-series data of oxygenated hemoglobin were bandpass-filtered (0.05 to 0.1 Hz) and subjected to Hilbert transformation to obtain instantaneous phases. Furthermore, the vector sum of instantaneous phases of 94 channels were taken at each time, and then time series of phase synchronization index (PSI) was obtained (Taga et al. 2011). PSIs were time-averaged within the sleep state and compared between the states.<br \/>\nIn the 2M group, PSI = 0.70 for AS and PSI = 0.48 for QS. In the 3M group, PSI = 0.73 for AS and PSI = 0.46 for QS. Analysis of variance of age x sleep state showed a significant main effect on sleep state (p &lt;0.001). This result implies that when the sleep changes from AS to QS, the synchrony decreases from spatially synchronous state to asynchronous state. There was no significant difference in age.<br \/>\nIt has been assumed that AS and QS in infants correspond to REM and NREM sleep in adults, respectively. REM and NREM sleep have been thought to reflect synchronous and asynchronous neural activity of the cerebral cortex, respectively. While the spatiotemporal scale of the signals is different between EEG and fNIRS, the present study showed that the sleep state dependence on synchronization property of fNIRS signals is opposite to the one of EEG. This study suggests that the functional connectivity among the global network is enhanced in AS and diminished in QS. In future, further investigations are needed to understand functional roles of cortical activity in different sleep states in infants.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3053\u306e\u767a\u8868\u3067\u306ffNIRS\u3092\u7528\u3044\u3066\u5e7c\u5150\u306e\u7761\u7720\u72b6\u614b\u306b\u5fdc\u3058\u305f\u8133\u306e\u81ea\u767a\u6d3b\u52d5\u306e\u6642\u7a7a\u9593\u30c0\u30a4\u30ca\u30df\u30af\u30b9\u3092\u660e\u3089\u304b\u306b\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u3068\u3057\u3066\u3044\u307e\u3057\u305f\uff0eEEG\u3092\u7528\u3044\u308b\u3082\u306e\u306f\u77e5\u3063\u3066\u3044\u307e\u3057\u305f\u304cfNIRS\u3092\u7528\u3044\u305f\u7761\u7720\u306e\u7814\u7a76\u306f\u3042\u307e\u308a\u805e\u3044\u305f\u3053\u3068\u304c\u306a\u304f\u65b0\u9bae\u3067\u3057\u305f\uff0e\u307e\u305f\u89e3\u6790\u306b\u7528\u3044\u3066\u3044\u305f\u77ac\u6642\u4f4d\u76f8\u3092\u81ea\u5206\u306e\u7814\u7a76\u3067\u3082\u5229\u7528\u3067\u304d\u306a\u3044\u304b\u3068\u8003\u3048\u3066\u3044\u305f\u305f\u3081\u3068\u3066\u3082\u53c2\u8003\u306b\u306a\u308a\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1aInter-brain synchronization during a freestyle PC game: an fNIRS hyperscanning study<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a M. Xu, S. Morimoto, E. Hoshino,<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Poster\u2162<br \/>\nAbstruct\u00a0\u00a0\u00a0 \uff1a <strong><em>Motivation: <\/em><\/strong>Human social interaction is a highly dynamic process consisting of continuous live social signal exchanges. Thus, studying interaction between multiple humans is critical to understanding the brain basis of social behavior, which is an emerging field of interest. fNIRS hyperscanning has played a significant role in advancing this field by enabling real-world neuroimaging. However, previous studies mainly adopted tasks during which multiple participants had performed synchronized actions. It remains largely unclear about the underlying mechanisms and any influential factors of inter-brain couplings during real-world interactions when participants have a common goal but much flexibility in action.<br \/>\n<strong><em>Method: <\/em><\/strong>Thirty-nine same-sex dyads played a turn-based PC game (Fig.1) cooperatively or independently while their hemodynamic responses in the right frontal and temporal regions were measured simultaneously. At the same time, their physiological responses (heart rate and skin conductance response) were recorded simultaneously as well. Any type of verbal\/nonverbal interaction was allowed during the cooperative sessions (the dyads were prompted to design the interiors of a big room that satisfy both themselves and their partners) but not during the independent sessions (to design the interiors of two small rooms without considering their partners). Their behaviors during the tasks were videotaped. The inter-brain synchronization (IBS) was evaluated using wavelet transform coherence (WTC) (1).<br \/>\n<strong><em>Results and discussion: <\/em><\/strong>The IBS was found to display different patterns during the cooperative sessions and the independent sessions, and the IBS was more prominent during cooperation. Moreover, the period during which the IBS occurred was shown to correlate with the dyads\u2019 span of turn-takings. These findings indicate that cooperative behaviors facilitate between-brain neural couplings. The relationship between the IBS and other types of interactive signals (e.g., eye contact, verbal communication, etc.) and physiological synchronization will be further examined.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u90e8\u5c4b\u306e\u30c7\u30b6\u30a4\u30f3\u3092\u884c\u3046\u30b2\u30fc\u30e0\u3092\u5229\u7528\u3057\u305f\u30aa\u30ea\u30b8\u30ca\u30eb\u306a\u5b9f\u9a13\u8a2d\u8a08\u3067\u3057\u305f\uff0e\u8133\u3060\u3051\u3067\u306a\u304f\u4ed6\u306e\u8a08\u6e2c\u6a5f\u5668\u3092\u7528\u3044\u3066\u5fc3\u96fb\u56f3\u3084\u76ae\u819a\u30b3\u30f3\u30c0\u30af\u30bf\u30f3\u30b9\u53cd\u5fdc\u306a\u3069\u306e\u751f\u7406\u5b66\u7684\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u3066\u3044\u307e\u3057\u305f\uff0e\u4eca\u5f8c\u306f\uff0c\u305d\u308c\u3089\u306b\u52a0\u3048\u3066\uff0c\u64ae\u5f71\u3057\u305f\u52d5\u753b\u306a\u3069\u304b\u3089\u30a2\u30a4\u30b3\u30f3\u30bf\u30af\u30c8\u3084\u8a00\u8449\u306b\u3088\u308b\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u306a\u3069\u306e\u884c\u52d5\u30c7\u30fc\u30bf\u3068\u8133\u6d3b\u52d5\u306e\u95a2\u4fc2\u3082\u307f\u3066\u3044\u304d\u305f\u3044\u3068\u306e\u3053\u3068\u3067\u3057\u305f\uff0e\u4ed6\u306e\u751f\u7406\u5b66\u7684\u30c7\u30fc\u30bf\u3084\u884c\u52d5\u30c7\u30fc\u30bf\u3092\u8c4a\u5bcc\u306b\u53d6\u3063\u3066\u304a\u308a\uff0c\u8133\u6d3b\u52d5\u3068\u306e\u95a2\u9023\u304c\u5206\u304b\u308c\u3070\u9762\u767d\u3044\u3068\u601d\u3044\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"529\">\u767a\u8868\u30bf\u30a4\u30c8\u30eb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a THE NEW NEUROSCIENCE OF TWO: HYPERSCANNING WITH fNIRS TO UNDERSTAND COMMUNICATING BRAINS<br \/>\n\u8457\u8005\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Joy Hirsch<br \/>\n\u30bb\u30c3\u30b7\u30e7\u30f3\u540d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \uff1a Cognitive &amp; social neuroscience<br \/>\nAbstruct\u00a0\u00a0\u00a0 \uff1a Humans are a profoundly social species. However, little is known about the most fundamental brain functions that mediate live social interactions. This knowledge gap between single and social brain processes, is, in part, a consequence of conventional neural imaging methods that are generally restricted to single individuals, static tasks, and nonverbal responses. However, recent developments of fNIRS hyperscanning (imaging two individuals simultaneously) enables rigorous investigation of this unexplored neural domain of human social behavior.<br \/>\nTwo existing theoretical frameworks converge as a foundation for this new \u201cneuroscience of two\u201d. The first is the Interactive Brain Hypothesis (De Jaegher, et al, 2016) which proposes that social interactions are mediated by dedicated brain processes. This hypothesis provides a general framework for the investigation of neural mechanisms underlying social interaction. The second is a quantifiable model of dynamic neural coupling, i.e. the correlation between temporal patterns of neural signals across two interacting partners (Hasson and Frith, 2016). This model proposes that dynamic coupling is the mechanism by which information is shared between the sender and the receiver across brains. Hyperscanning with fNIRS, together with these emerging theoretical frameworks, establishes fNIRS as the neuroimaging method of choice for investigations of live human-to-human interactions.<br \/>\nParadigms for investigation of two individuals engaged in live and spontaneous communications include developments for imaging in natural environments as well as the computational methods necessary to quantify live cross-brain interactions. We have applied these tools to test specific cases of the interactive brain hypothesis using fNIRS hyperscanning and primary social cues such as real eye-to-eye contact compared to eye gaze at a picture-face (Hirsch, et al., 2017), a video-face (Noah, et al.,2018), and talking and listening (Hirsch, et al., 2018) with and without social interaction. Consistent with the Interactive Brain Hypothesis cross-brain coherence measured by Wavelet Coherence Analysis (MATLAB Wavelet Toolbox) between local brain areas is greater for interactive than non-interactive conditions. Specifically, dynamic neural coupling increases during interactions such as eye-to-eye contact and interactive speaking and listening. Further, the dynamic neural coupling is associated with neural activity in temporal-parietal regions of the brain consistent with specialized cross-brain neural mechanisms for live social interaction regardless of the modality or task. These, and other similar findings recently reported using fNIRS hyperscanning, contribute to an expanding experimental and theoretical foundation for a new neuroscience where the aim is to understand the dynamic signal exchanges and neural mechanisms within a dyad that underlie live episodes of social interaction in natural conditions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5c0e\u5165\u306b\u304a\u3044\u3066hyperscanning\u306e\u7814\u7a76\u306b\u3064\u3044\u3066\u4e01\u5be7\u306b\u8aac\u660e\u3092\u3057\u3066\u304a\u308a\uff0chyperscanning\u7814\u7a76\u306e\u904e\u53bb\u30fb\u73fe\u5728\u30fb\u672a\u6765\u306b\u3064\u3044\u3066\u3088\u304f\u5206\u304b\u308a\uff0c\u8a71\u306e\u69cb\u6210\u3084\u4eee\u8aac\u306e\u7acb\u3066\u65b9\u306a\u3069\u5927\u5909\u52c9\u5f37\u306b\u306a\u308a\u307e\u3057\u305f\uff0e\u307e\u305f\uff0cfNIRS\u3092\u7528\u3044\u305fhyperscanning\u7814\u7a76\u304c\u8133\u306e\u793e\u4f1a\u6027\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306e\u4e3b\u6d41\u306b\u306a\u308b\u3060\u308d\u3046\u3068\u304a\u3063\u3057\u3083\u3063\u3066\u304a\u308a\uff0c\u81ea\u5206\u306e\u7814\u7a76\u306e\u610f\u7fa9\u3092\u518d\u78ba\u8a8d\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\uff0e<br \/>\n&nbsp;<br \/>\n&nbsp;<br \/>\n\u53c2\u8003\u6587\u732e<\/p>\n<ul>\n<li>fNIRS2018, http:\/\/fnirs2018.org<\/li>\n<\/ul>\n<p>&nbsp;<br \/>\n&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>2018\/10\/05\u304b\u30892018\/10\/08\u306b\u6771\u4eac\u5927\u5b66\u306b\u3066\u958b\u50ac\u3055\u308c\u305f\u3000fNIRS2018\u306b\u7814\u7a76\u5ba4\u304b\u30894\u4ef6\u306e\u767a\u8868\u3092\u884c\u3044\u307e\u3057\u305f\u3002 A fNIRS-based hyperscanning study of inter-brai &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/is.doshisha.ac.jp\/news\/?p=5545\" class=\"more-link\"><span class=\"screen-reader-text\">&#8220;\u3010\u901f\u5831\u3011&#8221; \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10,3],"tags":[],"class_list":["post-5545","post","type-post","status-publish","format-standard","hentry","category-10","category-3"],"_links":{"self":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/5545","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=5545"}],"version-history":[{"count":0,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=\/wp\/v2\/posts\/5545\/revisions"}],"wp:attachment":[{"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5545"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5545"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/is.doshisha.ac.jp\/news\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5545"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}