{"title":"神经群体计算:并行分布式处理、基本Ganglia和进化","authors":"S. Nadeau","doi":"10.33696/neurol.2.038","DOIUrl":null,"url":null,"abstract":"It has been known for some time that representations in the central nervous system (CNS) are population encoded, that is, encoded as patterns of activity involving very large numbers of highly interconnected neurons in one or more neural networks extending over large expanses of the brain [1-11]. Nonetheless, understanding the computational processes occurring in pools of cortical neurons and the subcortical nuclei with which they interact continues to be one of the major challenges facing systems neuroscience.","PeriodicalId":73744,"journal":{"name":"Journal of experimental neurology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neural Population Computing: Parallel Distributed Processing, the Basal Ganglia, and Evolution\",\"authors\":\"S. Nadeau\",\"doi\":\"10.33696/neurol.2.038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It has been known for some time that representations in the central nervous system (CNS) are population encoded, that is, encoded as patterns of activity involving very large numbers of highly interconnected neurons in one or more neural networks extending over large expanses of the brain [1-11]. Nonetheless, understanding the computational processes occurring in pools of cortical neurons and the subcortical nuclei with which they interact continues to be one of the major challenges facing systems neuroscience.\",\"PeriodicalId\":73744,\"journal\":{\"name\":\"Journal of experimental neurology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of experimental neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33696/neurol.2.038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of experimental neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33696/neurol.2.038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural Population Computing: Parallel Distributed Processing, the Basal Ganglia, and Evolution
It has been known for some time that representations in the central nervous system (CNS) are population encoded, that is, encoded as patterns of activity involving very large numbers of highly interconnected neurons in one or more neural networks extending over large expanses of the brain [1-11]. Nonetheless, understanding the computational processes occurring in pools of cortical neurons and the subcortical nuclei with which they interact continues to be one of the major challenges facing systems neuroscience.