{"id":29093,"date":"2021-09-28T21:39:50","date_gmt":"2021-09-28T13:39:50","guid":{"rendered":"https:\/\/swarma.org\/?p=29093"},"modified":"2021-09-28T21:39:50","modified_gmt":"2021-09-28T13:39:50","slug":"pnas%ef%bc%9a%e5%a4%a7%e8%84%91%e5%a6%82%e4%bd%95%e6%95%b4%e5%90%88%e5%a4%9a%e6%84%9f%e5%ae%98%e6%a8%a1%e6%80%81%e4%bf%a1%e6%81%af%ef%bc%8c%e8%bf%9b%e8%a1%8c%e5%9b%a0%e6%9e%9c%e6%8e%a8%e6%96%ad","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=29093","title":{"rendered":"PNAS\uff1a\u5927\u8111\u5982\u4f55\u6574\u5408\u591a\u611f\u5b98\u6a21\u6001\u4fe1\u606f\uff0c\u8fdb\u884c\u56e0\u679c\u63a8\u65ad\uff1f"},"content":{"rendered":"
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Stephanie Badde,  Fangfang Hong, Michael S. Landy<\/span> | \u4f5c\u8005<\/strong><\/span><\/p>\n

\u5341\u4e09\u7ef4<\/span> | \u8bd1\u8005<\/strong><\/span><\/strong><\/span><\/p>\n

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\u8bba\u6587\u9898\u76ee\uff1aCausal inference and the evolution of opposite neurons<\/span><\/section>\n
\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/www.pnas.org\/content\/118\/36\/e2112686118<\/span><\/section>\n
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\u56fe1. \u591a\u611f\u5b98\u6574\u5408\u548c\u56e0\u679c\u63a8\u65ad\u3002(A)\u5f53\u63a8\u65ad\u51fa\u4e00\u4e2a\u5171\u540c\u539f\u56e0\u65f6\uff0c\u89c6\u89c9\u548c\u89e6\u89c9\u7684\u611f\u89c9\u4fe1\u53f7\u88ab\u6574\u5408\uff1b(B)\u5f53\u63a8\u65ad\u51fa\u5355\u72ec\u7684\u6765\u6e90\u65f6\uff0c\u4f7f\u7528\u5206\u79bb\u7684\u89c6\u89c9\u4fe1\u53f7\u3002<\/span>(C)\u5728\u8de8\u6a21\u6001\u4e0b\u6307\u5411\u65b9\u5411\u4e00\u81f4\u7684\u795e\u7ecf\u5143\u5177\u6709\u76f8\u4f3c\u7684\u8c03\u8c10\uff1b(D)\u5f02\u5411\u795e\u7ecf\u5143\u7684\u9996\u9009\u65b9\u5411\u5728\u4e0d\u540c\u6a21\u6001\u4e0b\u6709\u6240\u4e0d\u540c\u3002\u8fd9\u4e24\u79cd\u7c7b\u578b\u7684\u795e\u7ecf\u5143\u5bf9(E)\u81ea\u6211\u8fd0\u52a8\u548c(F)\u4e16\u754c\u8fd0\u52a8\u7684\u4f30\u8ba1\uff0c\u4ee5\u53ca(G)\u56e0\u679c\u63a8\u65ad\u5224\u65ad\u90fd\u6709\u8d21\u732e\uff0c\u4f46\u7a0b\u5ea6\u4e0d\u540c\u3002(H)\u5728\u8d1d\u53f6\u65af\u4f30\u8ba1\u4e2d\uff0c\u6574\u5408\u7684\u548c\u5206\u79bb\u7684\u4f30\u8ba1\u88ab\u7ed3\u5408\u8d77\u6765\uff0c\u5176\u6743\u91cd\u7b49\u4e8e\u6bcf\u79cd\u56e0\u679c\u60c5\u51b5\u7684\u6982\u7387\u3002<\/span><\/p>\n

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\u8bb8\u591a\u4ece\u4e24\u79cd\u6a21\u6001\u63a5\u6536\u8f93\u5165*\u7684\u795e\u7ecf\u5143\u90fd\u662f\u540c\u8c03\u795e\u7ecf\u5143<\/strong><\/span>\uff08congruent neurons\uff09<\/span>\uff1a\u5b83\u4eec\u5bf9\u8fd9\u4e24\u79cd\u6a21\u6001\u6709\u76f8\u4f3c\u7684\u8c03\u8c10<\/span>\uff08\u56fe1C\uff09<\/span>\u3002\u56e0\u6b64\uff0c\u540c\u8c03\u795e\u7ecf\u5143\u4f3c\u4e4e\u6ce8\u5b9a\u8981\u8fdb\u884c\u591a\u611f\u5b98\u6574\u5408<\/strong><\/span>\uff08multisensory integration\uff09<\/span>[10,11]\u3002\u4f46\u5947\u602a\u7684\u662f\uff0cMSTd \u548c VIP \u4e2d\u7684\u8bb8\u591a\u5176\u5b83\u795e\u7ecf\u5143\u662f\u5f02\u5411\u795e\u7ecf\u5143<\/span>\uff08\u56fe1D\uff09<\/span>\uff0c\u5b83\u4eec\u5bf9\u6307\u793a\u76f8\u53cd\u65b9\u5411\u7684\u89c6\u89c9\u548c\u524d\u5ead\u4fe1\u606f\u8fdb\u884c\u8c03\u8c10\uff0c\u4f8b\u5982\uff0c\u89c6\u89c9\u523a\u6fc0\u53d1\u51fa\u7684\u5411\u53f3\u8fd0\u52a8\u548c\u524d\u5ead\u7684\u5411\u5de6\u8fd0\u52a8\u4fe1\u53f7[10,12]\u3002\u5f53\u611f\u89c9\u4fe1\u53f7\u6765\u81ea\u4e0d\u540c\u6765\u6e90\u65f6\uff0c\u5f02\u5411\u795e\u7ecf\u5143\u4f3c\u4e4e\u540c\u6837\u6709\u975e\u5e38\u9002\u5408\u7684\u65b9\u5f0f\u8fdb\u884c\u68c0\u6d4b\u3002\u5982\u6b64\u4e00\u6765\uff0c\u540c\u8c03\u548c\u5f02\u5411\u795e\u7ecf\u5143\u7684\u534f\u4f5c\u5c31\u53ef\u80fd\u4f7f\u5927\u8111\u8fdb\u884c\u56e0\u679c\u63a8\u65ad<\/strong>[10,13]\u3002<\/span><\/section>\n
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3. \u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u6a21\u62df<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


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Rideaux\u7b49\u4eba[9]\u5bf9\u8fd9\u4e2a\u95ee\u9898\u91c7\u53d6\u4e86\u4e00\u4e2a\u7279\u522b\u806a\u660e\u7684\u65b9\u6cd5\u3002\u4ed6\u4eec\u6ca1\u6709\u6784\u5efa\u4e00\u4e2a\u7531\u624b\u5de5\u8c03\u8c10\u7684\u540c\u8c03\u548c\u5f02\u5411\u795e\u7ecf\u5143\u5c42\u6784\u6210\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff0c\u800c\u662f\u8bad\u7ec3\u4e86\u4e00\u4e2a\u65e0\u7ea6\u675f<\/span>\uff08unconstrained\uff09<\/span>\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff0c\u6765\u6267\u884c\u56e0\u679c\u63a8\u65ad\u5224\u65ad\u53ca\u5bf9\u81ea\u6211\u548c\u4e16\u754c\u7684\u8fd0\u52a8\u4f30\u8ba1\uff0c\u7136\u540e\u68c0\u67e5\u4e86\u591a\u611f\u5b98\u795e\u7ecf\u5143\u7684\u8c03\u8c10\u548c\u8fde\u63a5\u3002\u8fd9\u4e2a\u591a\u5c42\u524d\u9988\u7f51\u7edc\u6709\u4e24\u7ec4\u8f93\u5165\uff1a\u89c6\u89c9\u548c\u524d\u5ead\u3002\u89c6\u89c9\u8f93\u5165<\/strong>\u662f\u81ea\u7136\u56fe\u50cf\u7684\u77ed\u5e8f\u5217\uff0c\u4ee5\u4e0d\u540c\u901f\u5ea6\u5411\u56db\u4e2a\u65b9\u5411\u53d8\u6362<\/span>\uff08\u5de6-\u53f3\u3001\u4e0a-\u4e0b\u3001\u671d\u5411-\u8fdc\u79bb\u548c\u89c6\u7ebf\u65cb\u8f6c\uff09<\/span>\u3002\u524d\u5ead\u8f93\u5165<\/strong>\u6765\u81ea\u6cbf\u7740\u8fd9\u56db\u4e2a\u8f74\u8c03\u6574\u7684\u5355\u4f4d\u7684\u901f\u5ea6\uff0c\u5e76\u7565\u5fae\u53d7\u5230\u566a\u58f0\u7684\u5e72\u6270\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5bf9\u4e8e\u6bcf\u4e2a\u8fd0\u52a8\u65b9\u5411\uff0c\u795e\u7ecf\u7f51\u7edc\u8f93\u51fa\u7684\u795e\u7ecf\u5143\u5206\u522b\u786e\u5b9a\u8fd0\u52a8\u901f\u5ea6<\/span>\uff08\u8bad\u7ec3\u4e3a\u5339\u914d\u524d\u5ead\u548c\u89c6\u89c9\u8f93\u5165\u901f\u5ea6\u7684\u5e73\u5747\u503c\uff1b\u56fe1E\uff09<\/span>\u3001\u4e16\u754c\u8fd0\u52a8\u901f\u5ea6<\/span>\uff08\u8bad\u7ec3\u4e3a\u5339\u914d\u4e24\u4e2a\u8f93\u5165\u901f\u5ea6\u4e4b\u5dee\uff1b\u56fe1F\uff09<\/span>\uff0c\u5e76\u8fdb\u884c\u5171\u540c\u6765\u6e90\u5224\u65ad<\/span>\uff08\u8bad\u7ec3\u4e3a\u5339\u914d\u4e24\u4e2a\u8f93\u5165\u901f\u5ea6\u4e4b\u5dee\u662f\u5927\u662f\u5c0f\u7684\u4e8c\u5143\u5206\u7c7b\uff1b\u56fe1G\uff09<\/span>\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u5bf9\u4e16\u754c\u8fd0\u52a8\u4f30\u8ba1\u4efb\u52a1\u7684\u591a\u611f\u5b98\u6574\u5408\u4e0e\u5176\u5b83\u9886\u57df\u4e0d\u540c\uff0c\u540e\u8005\u7684\u6574\u5408\u901a\u5e38\u4e0e\u533a\u9694\u5f62\u6210\u5bf9\u7acb\uff0c\u4f8b\u5982\u4ec5\u4f9d\u8d56\u4e00\u79cd\u6a21\u6001<\/span>\uff08\u6bd4\u8f83\u56fe1A\u548cB\uff09<\/span>\u3002\u56e0\u6b64\u540e\u7eed\u4f1a\u5e26\u6765\u4e00\u4e2a\u6709\u8da3\u7684\u95ee\u9898\uff0c\u5373\u8be5\u7f51\u7edc\u5c06\u5982\u4f55\u63a8\u5e7f\u5230\u5bf9\u7a7a\u95f4\u3001\u65f6\u95f4\u6216\u5176\u5b83\u7279\u5f81\u7684\u591a\u611f\u5b98\u77e5\u89c9\u7684\u6a21\u62df\u4e2d\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u8be5\u8bba\u6587\u7684\u4e3b\u8981\u8d21\u732e\u662f\uff0c\u7ecf\u8fc7\u6210\u529f\u8bad\u7ec3\u540e\uff0c\u8be5\u7f51\u7edc\u53d1\u5c55\u51fa\u4e86\u4e0e\u7315\u7334 MSTd \u548c VIP \u4e2d\u540c\u8c03\u548c\u5f02\u5411\u76f8\u540c\u7279\u5f81\u7684\u795e\u7ecf\u5143\u3002\u66f4\u5177\u4f53\u800c\u8a00\uff0c\u5728\u7f51\u7edc\u7684\u300cMSTd\u300d\u5c42\u4e2d\uff0c\u795e\u7ecf\u5143\u5bf9\u6307\u793a\u65b9\u5411\u6709\u6e05\u6670\u7684\u8c03\u8c10<\/span>\uff08\u65b9\u5411\u6cbf\u7740\u5de6-\u53f3\u6216\u524d-\u540e\u8f74\u901f\u5ea6\u8ba1\u7b97\uff09<\/span>\uff0c\u5927\u591a\u6570\u795e\u7ecf\u5143\u8981\u4e48\u5177\u6709\u4e00\u81f4\u7684\u89c6\u89c9\u548c\u524d\u5ead\u8c03\u8c10\uff0c\u8981\u4e48\u5bf9\u8fd9\u4e24\u79cd\u6a21\u6001\u8868\u73b0\u51fa\u76f8\u53cd\u8fd0\u52a8\u65b9\u5411\u7684\u8c03\u8c10\u3002\u8fd9\u4e24\u79cd\u7c7b\u578b\u7684\u795e\u7ecf\u5143\u90fd\u4e3a\u56e0\u679c\u63a8\u65ad\u5224\u65ad\u63d0\u4f9b\u4e86\u91cd\u8981\u7684\u8f93\u5165\uff0c\u8bc1\u5b9e\u4e86\u6700\u521d\u7684\u5047\u8bbe\uff0c\u5373\u540c\u8c03\u548c\u5f02\u5411\u795e\u7ecf\u5143\u4e4b\u95f4\u7684\u6743\u8861\u5bf9\u4e8e\u63a8\u65ad\u4e24\u4e2a\u4fe1\u53f7\u662f\u5426\u6765\u81ea\u540c\u4e00\u6765\u6e90\u81f3\u5173\u91cd\u8981\u3002<\/strong><\/span><\/section>\n

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\u81f3\u4e8e\u8be5\u7f51\u7edc\u7684\u8fd0\u52a8\u901f\u5ea6\u611f\u77e5\uff0c\u540c\u8c03\u7ec6\u80de\u4e3a\u81ea\u6211\u8fd0\u52a8\u4f30\u8ba1\u63d0\u4f9b\u4e86\u66f4\u5f3a\u7684\u8f93\u5165\uff0c\u5f02\u5411\u7ec6\u80de\u5219\u4e3a\u4e16\u754c\u8fd0\u52a8\u4f30\u8ba1\u63d0\u4f9b\u4e86\u66f4\u5f3a\u7684\u8f93\u5165\u3002\u8fd9\u4e24\u79cd\u7c7b\u578b\u7684\u795e\u7ecf\u5143\u4e5f\u90fd\u80fd\u5bf9\u53e6\u4e00\u79cd\u77e5\u89c9\u4f30\u8ba1\u505a\u51fa\u8d21\u732e\uff0c\u53ea\u4e0d\u8fc7\u7a0b\u5ea6\u8f83\u5c0f\u3002\u5148\u524d\u5e26\u6709\u624b\u5de5\u8c03\u8c10\u7684\u540c\u8c03\u548c\u5f02\u5411\u795e\u7ecf\u5143\u7684\u8ba1\u7b97\u6a21\u578b\u5df2\u7ecf\u8bc1\u660e\uff0c\u8fd9\u79cd\u7f51\u7edc\u80fd\u591f\u6267\u884c\u56e0\u679c\u63a8\u65ad[13,14]\uff0c\u4e0d\u8fc7\uff0c\u6ca1\u8fd9\u4e9b\u7279\u6027\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4ea6\u5982\u6b64[15]\u3002\u4e0e\u8fd9\u4e9b\u81ea\u4e0a\u800c\u4e0b\u7684\u65b9\u6cd5\u76f8\u53cd\uff0cRideaux\u7b49\u4eba[9]\u8868\u660e\uff0c\u540c\u65f6\u8fdb\u884c\u77e5\u89c9\u548c\u56e0\u679c\u63a8\u65ad\u5224\u65ad\u7684\u8981\u6c42\u4fc3\u4f7f\u4e86\u540c\u8c03\u548c\u5f02\u5411\u795e\u7ecf\u5143\u7684\u53d1\u5c55<\/strong>\uff0c\u8868\u660e\u8fd9\u79cd\u795e\u7ecf\u57fa\u8d28<\/span>\uff08neural substrate\uff09<\/span>\u662f\u8ba1\u7b97\u7684\u6700\u4f73\u65b9\u6848\u3002<\/span><\/section>\n
 <\/span><\/section>\n

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 <\/span><\/section>\n

\u56fe2. \u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4e2d\u7684\u89c6\u89c9\u548c\u524d\u5ead\u4fe1\u53f7\u8f93\u5165\uff0c\u5728\u7ecfMSTd\u5c42\u4e09\u79cd\u4e0d\u540c\u65b9\u5f0f\u89e3\u7801\u540e\uff0c\u5206\u522b\u8f93\u51fa\u5bf9\u81ea\u6211\u3001\u573a\u666f\u548c\u56e0\u679c\u63a8\u65ad\u7684\u4f30\u8ba1<\/span><\/p>\n

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\u8be5\u7f51\u7edc\u5728\u611f\u77e5\u4efb\u52a1\u4e2d\u7684\u8868\u73b0\u5b9e\u8d28\u4e0a\u53cd\u6620\u4e86\u4eba\u7c7b\u548c\u7334\u5b50\u5728\u65b9\u5411\u8fa8\u522b\u4efb\u52a1\u4e2d\u7684\u884c\u4e3a[11]\u3002\u6210\u529f\u8bad\u7ec3\u540e\uff0c\u8be5\u7f51\u7edc\u5177\u6709\u8f83\u5c0f\u7684\u89c6\u89c9\u548c\u524d\u5ead\u8fd0\u52a8\u8f93\u5165\u7684\u8de8\u6a21\u6001\u5dee\u5f02\u3002\u8fd9\u4e9b\u6d4b\u8bd5\u4e2d\u7684\u89c6\u89c9\u523a\u6fc0\u88ab\u66f4\u6539\u4e3a\u4e00\u7ec4\u79fb\u52a8\u70b9\u96c6\uff0c\u5176\u53ef\u9760\u6027\u901a\u8fc7\u6539\u53d8\u5411\u540c\u4e00\u65b9\u5411\u79fb\u52a8\u7684\u70b9\u7684\u6bd4\u4f8b\u6765\u64cd\u7eb5\u3002\u7f51\u7edc\u5219\u6839\u636e\u5176\u53ef\u9760\u6027\u6574\u5408\u89c6\u89c9\u548c\u524d\u5ead\u8f93\u5165\uff1a\u5982\u679c\u89c6\u89c9\u8f93\u5165\u53ef\u9760\u6027\u8f83\u4f4e\uff0c\u81ea\u6211\u8fd0\u52a8\u4f30\u8ba1\u4e0e\u524d\u5ead\u8f93\u5165\u66f4\u4e00\u81f4\uff1b\u5982\u679c\u89c6\u89c9\u8f93\u5165\u53ef\u9760\u6027\u8f83\u9ad8\uff0c\u81ea\u6211\u8fd0\u52a8\u4f30\u8ba1\u5219\u4e0e\u89c6\u89c9\u8f93\u5165\u66f4\u4e00\u81f4\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u5728\u8bad\u7ec3\u671f\u95f4\uff0c\u81ea\u6211\u8fd0\u52a8\u4f30\u8ba1\u5f97\u5230\u4e86\u52a0\u5f3a\uff0c\u4ee5\u5339\u914d50-50\u7684\u5e73\u5747\u89c6\u89c9\u548c\u524d\u5ead\u4fe1\u53f7\uff0c\u8fd9\u5c31\u63d0\u51fa\u4e86\u4e00\u4e2a\u95ee\u9898\uff0c\u5373\u6267\u884c\u53ef\u9760\u6027\u52a0\u6743\u6574\u5408\u7684\u80fd\u529b\u662f\u6765\u81ea\u5bf9\u51e0\u9879\u4efb\u52a1\u7684\u8054\u5408\u8bad\u7ec3\uff0c\u8fd8\u662f\u7531\u4e8e\u7f51\u7edc\u67b6\u6784\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5f53\u7f51\u7edc\u63a8\u65ad\u51fa\u5355\u72ec\u7684\u539f\u56e0\u65f6\uff0c\u89c6\u89c9\u8f93\u5165\u5bf9\u81ea\u6211\u8fd0\u52a8\u4f30\u8ba1\u7684\u5f71\u54cd\u8981\u6bd4\u63a8\u65ad\u51fa\u4e24\u4e2a\u4fe1\u53f7\u7684\u5171\u540c\u6765\u6e90\u65f6\u4f4e\u3002\u5982\u679c\u4e00\u79cd\u6a21\u6001\u8f93\u5165\u662f\u6709\u566a\u58f0\u7684\uff0c\u5373\u76f8\u540c\u7684\u523a\u6fc0\u5bfc\u81f4\u4e0d\u540c\u8bd5\u9a8c\u7684\u5185\u90e8\u6d4b\u91cf\u7565\u6709\u4e0d\u540c\uff0c\u8fd9\u79cd\u8de8\u6a21\u6001\u504f\u5411\u7684\u5dee\u5f02\u4f1a\u81ea\u52a8\u51fa\u73b0[6]\u3002\u7136\u800c\u4ee5\u76ee\u524d\u7684\u5f62\u5f0f\uff0c\u8be5\u7f51\u7edc\u8fd8\u65e0\u6cd5\u91cd\u73b0\u56e0\u679c\u63a8\u65ad\u7684\u4ee5\u4e0b\u884c\u4e3a\u7279\u5f81\uff1a\u5f53\u4fe1\u53f7\u66f4\u4e0d\u4e00\u81f4\uff0c\u5373\u4e0d\u592a\u53ef\u80fd\u4ece\u540c\u4e00\u6765\u6e90\u51fa\u73b0\u65f6\uff0c\u8de8\u6a21\u6001\u7684\u504f\u5dee\u4e3a\u4f55\u4f1a\u51cf\u5c11\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u9274\u4e8e\u8be5\u6a21\u578b\u662f\u4e25\u683c\u7684\u524d\u9988\uff0c\u56e0\u679c\u63a8\u65ad\u53ca\u81ea\u6211\u548c\u4e16\u754c\u7684\u8fd0\u52a8\u4f30\u8ba1\u6709\u5355\u72ec\u7684\u8f93\u51fa\uff0c\u8be5\u6a21\u578b\u6839\u672c\u4e0d\u80fd\u8ba9\u56e0\u679c\u63a8\u65ad\u5224\u65ad\u5f71\u54cd\u81ea\u6211\u8fd0\u52a8\u7684\u4f30\u8ba1\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u6a21\u578b\u65e0\u6cd5\u5ffd\u89c6\u6211\u4eec\u4ecb\u7ecd\u6027\u793a\u4f8b\u4e2d\u65e7\u868a\u5b50\u53ee\u54ac\u7684\u6320\u75d2\u611f\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u8d1d\u53f6\u65af\u56e0\u679c\u63a8\u65ad\u6a21\u578b<\/strong>[6]\u5219\u590d\u5236\u4e86\u8de8\u6a21\u6001\u504f\u5dee\u5bf9\u4e24\u4e2a\u4fe1\u53f7\u4e4b\u95f4\u5dee\u5f02\u7684\u975e\u7ebf\u6027\u4f9d\u8d56\u6027[6,16]\u3002\u4ed6\u4eec\u901a\u8fc7\u5c06\u6574\u5408\u548c\u5206\u79bb\u7684\u4f30\u8ba1\u503c\u76f8\u52a0\u6765\u5b9e\u73b0\u8fd9\u4e00\u76ee\u6807\uff0c\u5e76\u5206\u522b\u4ee5\u5171\u540c\u548c\u5355\u72ec\u6765\u6e90\u7684\u63a8\u65ad\u6982\u7387\u52a0\u6743<\/span>\uff08\u56fe1H\uff09<\/span>\u3002\u5728\u8fd9\u79cd\u89c2\u70b9\u4e0b\uff0cRideaux\u7b49\u4eba[9]\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u5305\u542b\u4e86\u77e5\u89c9\u4e24\u9636\u6bb5\u8fc7\u7a0b\u7684\u7b2c\u4e00\u9636\u6bb5\u3002<\/span><\/section>\n

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1. M. O.Ernst,M. S.Banks, Humans integrate visual and haptic information in a statistically optimal fashion. Nature415, 429\u2013433 (2002).<\/span><\/p>\n

2. J.Trommersh\u00e4user,K.K\u00f6rding,M. S.LandyM. S.Landy,M. S.Banks,D. C.Knill, \u201cIdeal-observer models of cue integration\u201d in Sensory Cue Integration, J. Trommersh\u00e4user, K. K\u00f6rding, M. S. Landy, Eds. (Oxford University Press, New York, 2011), pp. 5\u201329.<\/span><\/p>\n

3. M. S.Landy,L. T.Maloney,E. B.Johnston,M.Young, Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Res.35, 389\u2013412 (1995).<\/span><\/p>\n

4. D.Alais,D.Burr, The ventriloquist effect results from near-optimal bimodal integration. Curr. Biol.14, 257\u2013262 (2004).<\/span><\/p>\n

5. S.Gepshtein,J.Burge,M. O.Ernst,M. S.Banks, The combination of vision and touch depends on spatial proximity. J. Vis.5, 1013\u20131023 (2005).<\/span><\/p>\n

6. K. P.K\u00f6rdinget al., Causal inference in multisensory perception. PLoS One2, e943 (2007).<\/span><\/p>\n

7. K.Dokka,H.Park,M.Jansen,G. C.DeAngelis,D. E.Angelaki, Causal inference accounts for heading perception in the presence of object motion. Proc. Natl. Acad. Sci. U.S.A.116, 9060\u20139065 (2019).<\/span><\/p>\n

8. W.Fanget al., Statistical inference of body representation in the macaque brain. Proc. Natl. Acad. Sci. U.S.A.116, 20151\u201320157 (2019).<\/span><\/p>\n

9. R.Rideaux,K. R.Storrs,G.Maiello,A. E.Welchman, How multisensory neurons solve causal inference. Proc. Natl. Acad. Sci. U.S.A.118, doi:10.1073\/pnas.2106235118 (2021).<\/span><\/p>\n

10. Y.Gu,D. E.Angelaki,G. C.Deangelis, Neural correlates of multisensory cue integration in macaque MSTd. Nat. Neurosci.11, 1201\u20131210 (2008).<\/span><\/p>\n

11. C. R.Fetsch,A.Pouget,G. C.DeAngelis,D. E.Angelaki, Neural correlates of reliability-based cue weighting during multisensory integration. Nat. Neurosci.15, 146\u2013154 (2011).<\/span><\/p>\n

12. A.Chen,G. C.Deangelis,D. E.Angelaki, Functional specializations of the ventral intraparietal area for multisensory heading discrimination. J. Neurosci.33, 3567\u20133581 (2013)<\/span><\/p>\n

13. H. R.Kim,X.Pitkow,D. E.Angelaki,G. C.DeAngelis, A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons. J. Neurophysiol.116, 1449\u20131467 (2016).<\/span><\/p>\n

14. W. H.Zhanget al., Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation. eLife8, e43753 (2019).<\/span><\/p>\n

15. I.Yamashita,K.Katahira,Y.Igarashi,K.Okanoya,M.Okada, Recurrent network for multisensory integration-identification of common sources of audiovisual stimuli. Front. Comput. Neurosci.7, 101 (2013).<\/span><\/p>\n

16. M. T.Wallaceet al., Unifying multisensory signals across time and space. Exp. Brain Res.158, 252\u2013258 (2004).<\/span><\/p>\n

17. T.Rohe,U.Noppeney, Cortical hierarchies perform Bayesian causal inference in multisensory perception. PLoS Biol.13, e1002073 (2015).<\/span><\/p>\n

18. Y.Cao,C.Summerfield,H.Park,B. L.Giordano,C.Kayser, Causal inference in the multisensory brain. Neuron102, 1076\u20131087.e8 (2019).<\/span><\/p>\n

19. S.Badde,K. T.Navarro,M. S.Landy, Modality-specific attention attenuates visual-tactile integration and recalibration effects by reducing prior expectations of a common source for vision and touch. Cognition197, 104170 (2020).<\/span><\/p>\n

20. R.Gau,U.Noppeney, How prior expectations shape multisensory perception. Neuroimage124 (Pt A), 876\u2013886 (2016).<\/span><\/p>\n


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