{"id":48439,"date":"2024-02-20T20:54:19","date_gmt":"2024-02-20T12:54:19","guid":{"rendered":"https:\/\/swarma.org\/?p=48439"},"modified":"2024-02-20T20:54:19","modified_gmt":"2024-02-20T12:54:19","slug":"%e7%a5%9e%e7%bb%8f%e7%a7%91%e5%ad%a6%e4%b8%8e%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e4%ba%a4%e5%8f%89%e8%b7%af%e7%ba%bf%e5%9b%be%e4%b8%a8%e8%ae%a1%e7%ae%97%e7%a5%9e%e7%bb%8f%e7%a7%91%e5%ad%a6%e8%af%bb","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=48439","title":{"rendered":"\u795e\u7ecf\u79d1\u5b66\u4e0e\u673a\u5668\u5b66\u4e60\u4ea4\u53c9\u8def\u7ebf\u56fe\u4e28\u8ba1\u7b97\u795e\u7ecf\u79d1\u5b66\u8bfb\u4e66\u4f1a\u00b7\u5468\u56db\u76f4\u64ad"},"content":{"rendered":"
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Glaser, J. I., Benjamin, A. S., Farhoodi, R., & Kording, K. P. (2019). The roles of supervised machine learning in systems neuroscience. Progress in Neurobiology<\/em>, 175<\/em>, 126\u2013137.<\/span><\/section>\n

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HJ Cole, K Franke, Predicting Aging Using Neuroimaging: Innovative Brain Ageing Biomarkers, Trends in Neuroscience<\/em> 2017.<\/span><\/section>\n

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Devereux, B. J., Clarke, A., & Tyler, L. K. (2018). Integrated deep visual and semantic attractor neural networks predict fMRI pattern-information along the ventral object processing pathway. Scientific reports<\/em>, 8<\/em>(1), 10636.<\/span><\/section>\n

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\u6587\u7ae0\u901a\u8fc7\u8bad\u7ec3\u5355\u4e2a\u7f51\u7edc\u6a21\u578b\u6765\u6267\u884c 20 \u9879\u4f9d\u8d56\u4e8e\u5de5\u4f5c\u8bb0\u5fc6\u3001\u51b3\u7b56\u3001\u5206\u7c7b\u548c\u6291\u5236\u63a7\u5236\u7684\u8ba4\u77e5\u4efb\u52a1\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7814\u7a76\u8bb8\u591a\u8ba4\u77e5\u4efb\u52a1\u7684\u795e\u7ecf\u8868\u5f81\u7684\u8ba1\u7b97\u5e73\u53f0\u3002<\/strong><\/span><\/section>\n
Guangyu Robert Yang, Madhura R. Joglekar, H. Francis Song, William T. Newsome and Xiao-Jing Wang, Task representations in neural networks trained to perform many cognitive tasks.Nature neuroscience<\/em>, 2019.<\/span><\/section>\n

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Song HF, Yang GR, Wang XJ (2016) Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework. PLOS Computational Biology 12(2): e1004792<\/span><\/section>\n

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\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff08ANN\uff09\u662f\u673a\u5668\u5b66\u4e60\u7684\u91cd\u8981\u5de5\u5177\uff0c\u5728\u795e\u7ecf\u79d1\u5b66\u9886\u57df\u80fd\u591f\u4e8e\u6784\u5efa\u590d\u6742\u884c\u4e3a\u3001\u5f02\u6784\u795e\u7ecf\u6d3b\u52a8\u548c\u7535\u8def\u8fde\u63a5\u7684\u6a21\u578b\uff0c\u5e76\u4ee5\u4f20\u7edf\u6a21\u578b\u65e0\u6cd5\u8bbe\u8ba1\u7684\u65b9\u5f0f\u63a2\u7d22\u795e\u7ecf\u7cfb\u7edf\u7684\u4f18\u5316\u3002\u8fd9\u662f\u4e00\u7bc7\u7ed9\u795e\u7ecf\u79d1\u5b66\u5bb6\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4f7f\u7528\u6559\u7a0b\uff1a\u9996\u5148\u8ba8\u8bba\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u57fa\u672c\u6982\u5ff5\u548c\u65b9\u6cd5\u3002\u7136\u540e\uff0c\u91cd\u70b9\u5173\u6ce8\u5982\u4f55\u4f7f\u8fd9\u4e2a\u6570\u5b66\u6846\u67b6\u66f4\u63a5\u8fd1\u795e\u7ecf\u751f\u7269\u5b66\uff0c\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u5b9a\u5236\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u5206\u6790\u3001\u7ed3\u6784\u548c\u5b66\u4e60\uff0c\u4ee5\u66f4\u597d\u5730\u89e3\u51b3\u5927\u8111\u7814\u7a76\u4e2d\u7684\u5404\u79cd\u6311\u6218\u3002<\/strong><\/span><\/section>\n
Guangyu Robert Yang, Xiao-Jing Wang.Artificial neural networks for neuroscientists: A primer. Neuron<\/em>. 2020.<\/span><\/section>\n

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Zedong Bi and Changsong Zhou, Understanding the computation of time using neural network models, Proc Natl Acad Sci USA<\/em>, 117, 10530 (2020).<\/span><\/section>\n

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