{"id":35855,"date":"2022-07-15T19:03:00","date_gmt":"2022-07-15T11:03:00","guid":{"rendered":"https:\/\/swarma.org\/?p=35855"},"modified":"2022-07-15T19:03:00","modified_gmt":"2022-07-15T11:03:00","slug":"%e7%9f%a5%e8%a7%89%e5%86%b3%e7%ad%96%e7%9a%84%e7%a5%9e%e7%bb%8f%e8%ae%a1%e7%ae%97%e6%9c%ba%e5%88%b6-%e5%91%a8%e6%97%a5%e7%9b%b4%e6%92%ad%c2%b7%e7%a5%9e%e7%bb%8f%e5%8a%a8%e5%8a%9b%e5%ad%a6%e8%af%bb","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=35855","title":{"rendered":"\u77e5\u89c9\u51b3\u7b56\u7684\u795e\u7ecf\u8ba1\u7b97\u673a\u5236 | \u5468\u65e5\u76f4\u64ad\u00b7\u795e\u7ecf\u52a8\u529b\u5b66\u8bfb\u4e66\u4f1a"},"content":{"rendered":"
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\u4fe1\u53f7\u68c0\u6d4b\u7406\u8bba\uff08signal detection theory\uff09<\/span><\/p>\n

\u6269\u6563\u98d8\u79fb\u6a21\u578b\uff08Drift diffusion model\uff09<\/span><\/p>\n

\u8d1d\u53f6\u65af\u63a8\u65ad\uff08Bayesian inference\uff09<\/span><\/p>\n

\u653e\u7535\u795e\u7ecf\u7f51\u7edc\u6a21\u578b(spiking neural network)<\/span><\/p>\n

\u5e73\u5747\u573a\u8fd1\u4f3c\u65b9\u7a0b(Mean field model)<\/span><\/p>\n

\u5927\u5c3a\u5ea6\u591a\u8111\u533a\u6a21\u62df(Large scale brain simulation)<\/span><\/section>\n


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\u53c2\u8003\u6587\u732e<\/span><\/strong><\/h4>\n
1.Xiaojing Wang\uff082002\uff09Probabilistic Decision Making by Slow Reverberation in Cortical Circuits Neuron, 36, 955\u2013968<\/span><\/section>\n
2.Kong-Fatt Wong and Xiao-Jing Wang(2006) A Recurrent Network Mechanism of Time Integration in Perceptual Decisions. The Journal of Neuroscience, 26(4):1314 \u20131328<\/span><\/section>\n
3.Hongzhi You , Mengya Zhang , Da-Hui Wang(2020)Neural mechanism underlying risk attitude and probability distortion: One two-stage model of valuation and choice.Neurocomputing 375:32\u201342<\/span><\/section>\n
4.Luozheng Li, DaHui Wang(2021)Adaptive neurons compute confidence in a decision network.Scientific Reports  11:22190<\/span><\/section>\n


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\u7814\u7a76\u65b9\u5411\uff1a<\/span><\/strong>\u76ee\u524d\u4e13\u6ce8\u4e8e\u5229\u7528\u795e\u7ecf\u7cfb\u7edf\u7684\u8fde\u63a5\u7ec4\u3001\u795e\u7ecf\u7535\u751f\u7406\u548c\u5f71\u50cf\u7684\u5927\u6570\u636e\uff0c\u5efa\u7acb\u5927\u5c3a\u5ea6\u7684\u8111\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u53ca\u5176\u5206\u6790\u3002<\/span><\/section>\n


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\u672c\u7740\u4fc3\u8fdb\u795e\u7ecf\u79d1\u5b66\u3001\u7cfb\u7edf\u79d1\u5b66\u4ee5\u53ca\u8ba1\u7b97\u673a\u79d1\u5b66\u7b49\u4e0d\u540c\u9886\u57df\u7684\u5b66\u672f\u5de5\u4f5c\u8005\u7684\u4ea4\u6d41\u4e0e\u5408\u4f5c<\/strong>\uff0c\u6fc0\u53d1<\/strong>\u6709\u5fd7\u4e8e\u52a0\u5165\u8111\u79d1\u5b66\u4e0e\u7c7b\u8111\u7814\u7a76\u8fd9\u4e00\u9886\u57df\u7684\u540c\u5b66\u4eec\u7684\u7814\u7a76\u5174\u8da3<\/strong>\uff0c\u96c6\u667a\u4ff1\u4e50\u90e8\u548c\u5929\u6865\u8111\u79d1\u5b66\u7814\u7a76\u9662\u8054\u5408\u53d1\u8d77\u4e86\u795e\u7ecf\u52a8\u529b\u5b66\u6a21\u578b\u8bfb\u4e66\u4f1a<\/a>\u3002\u805a\u7126\u4e8e<\/strong>\u795e\u7ecf\u79d1\u5b66\u4e2d\u7684\u52a8\u529b\u5b66\u5efa\u6a21\u8fd9\u4e00\u524d\u6cbf\u8bfe\u9898\uff0c\u56f4\u7ed5\u795e\u7ecf\u7f51\u7edc\u591a\u5c3a\u5ea6\u5efa\u6a21\u53ca\u5176\u5728\u8111\u75be\u75c5\u3001\u8111\u8ba4\u77e5\u65b9\u9762\u7684\u5e94\u7528\u8fdb\u884c\u7814\u8ba8\u3002\u8bfb\u4e66\u4f1a\u5df2\u4e8e2022\u5e743\u670819\u65e5\u5f00\u59cb\uff0c\u6bcf\u5468\u516d\u4e0b\u534814:00-16:00\uff08\u6216\u6bcf\u5468\u4e94\u665a\u4e0a19:00-21:00\uff0c\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u8c03\u6574\uff09\u8fdb\u884c\uff0c\u9884\u8ba1\u6301\u7eed10-12\u5468\u3002<\/span><\/section>\n

<\/span><\/section>\n

\u8bfb\u4e66\u4f1a\u5927\u7eb2\u4e00\u89c8\uff1a<\/span><\/strong><\/p>\n

    \n
  1. \n
    \u590d\u6742\u795e\u7ecf\u52a8\u529b\u5b66\uff1a\u5206\u6790\u4e0e\u5efa\u6a21<\/span><\/section>\n<\/li>\n
  2. \n
    \u795e\u7ecf\u5143\u52a8\u529b\u5b66<\/span><\/section>\n<\/li>\n
  3. \n
    \u795e\u7ecf\u52a8\u529b\u5b66\u573a\u8bba<\/span><\/section>\n<\/li>\n
  4. \n
    \u5168\u8111\u52a8\u6001\u6a21\u62df<\/span><\/section>\n<\/li>\n
  5. \n
    \u591a\u5c3a\u5ea6\u751f\u6210\u6a21\u578b<\/span><\/section>\n<\/li>\n
  6. \n
    \u7761\u7720\u8c03\u63a7<\/span><\/section>\n<\/li>\n
  7. \n
    \u766b\u75eb\u53d1\u4f5c\u7684\u795e\u7ecf\u52a8\u529b\u5b66<\/span><\/section>\n<\/li>\n
  8. \n
    \u795e\u7ecf\u8c03\u63a7<\/span><\/section>\n<\/li>\n
  9. \n
    \u51b3\u7b56\u7684\u795e\u7ecf\u8ba1\u7b97\u673a\u5236<\/span><\/section>\n<\/li>\n
  10. \n
    \u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7684\u5e94\u7528<\/span><\/section>\n<\/li>\n
  11. \n
    \u603b\u7ed3\u5706\u684c\u4f1a<\/span><\/section>\n

    <\/section>\n<\/li>\n<\/ol>\n

    <\/span><\/a>
    <\/p>\n


    <\/p>\n

    <\/section>\n

    <\/section>\n

    <\/section>\n

    \u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u76f4\u64ad<\/span><\/p>\n<\/section><\/div>\n","protected":false},"excerpt":{"rendered":"

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