{"title":"真实神经元网络的统计力学","authors":"Leenoy Meshulam, William Bialek","doi":"arxiv-2409.00412","DOIUrl":null,"url":null,"abstract":"Perceptions and actions, thoughts and memories result from coordinated\nactivity in hundreds or even thousands of neurons in the brain. It is an old\ndream of the physics community to provide a statistical mechanics description\nfor these and other emergent phenomena of life. These aspirations appear in a\nnew light because of developments in our ability to measure the electrical\nactivity of the brain, sampling thousands of individual neurons simultaneously\nover hours or days. We review the progress that has been made in bringing\ntheory and experiment together, focusing on maximum entropy methods and a\nphenomenological renormalization group. These approaches have uncovered new,\nquantitatively reproducible collective behaviors in networks of real neurons,\nand provide examples of rich parameter--free predictions that agree in detail\nwith experiment.","PeriodicalId":501517,"journal":{"name":"arXiv - QuanBio - Neurons and Cognition","volume":"33 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical mechanics for networks of real neurons\",\"authors\":\"Leenoy Meshulam, William Bialek\",\"doi\":\"arxiv-2409.00412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Perceptions and actions, thoughts and memories result from coordinated\\nactivity in hundreds or even thousands of neurons in the brain. It is an old\\ndream of the physics community to provide a statistical mechanics description\\nfor these and other emergent phenomena of life. These aspirations appear in a\\nnew light because of developments in our ability to measure the electrical\\nactivity of the brain, sampling thousands of individual neurons simultaneously\\nover hours or days. We review the progress that has been made in bringing\\ntheory and experiment together, focusing on maximum entropy methods and a\\nphenomenological renormalization group. These approaches have uncovered new,\\nquantitatively reproducible collective behaviors in networks of real neurons,\\nand provide examples of rich parameter--free predictions that agree in detail\\nwith experiment.\",\"PeriodicalId\":501517,\"journal\":{\"name\":\"arXiv - QuanBio - Neurons and Cognition\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Neurons and Cognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.00412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Neurons and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.00412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical mechanics for networks of real neurons
Perceptions and actions, thoughts and memories result from coordinated
activity in hundreds or even thousands of neurons in the brain. It is an old
dream of the physics community to provide a statistical mechanics description
for these and other emergent phenomena of life. These aspirations appear in a
new light because of developments in our ability to measure the electrical
activity of the brain, sampling thousands of individual neurons simultaneously
over hours or days. We review the progress that has been made in bringing
theory and experiment together, focusing on maximum entropy methods and a
phenomenological renormalization group. These approaches have uncovered new,
quantitatively reproducible collective behaviors in networks of real neurons,
and provide examples of rich parameter--free predictions that agree in detail
with experiment.