{"title":"眶额叶和腹内侧前额叶皮层的表征空间:任务状态、价值及其他。","authors":"Nir Moneta, Shany Grossman, Nicolas W Schuck","doi":"10.1016/j.tins.2024.10.005","DOIUrl":null,"url":null,"abstract":"<p><p>The orbitofrontal cortex (OFC) and ventromedial-prefrontal cortex (vmPFC) play a key role in decision-making and encode task states in addition to expected value. We review evidence suggesting a connection between value and state representations and argue that OFC / vmPFC integrate stimulus, context, and outcome information. Comparable encoding principles emerge in late layers of deep reinforcement learning (RL) models, where single nodes exhibit similar forms of mixed-selectivity, which enables flexible readout of relevant variables by downstream neurons. Based on these lines of evidence, we suggest that outcome-maximization leads to complex representational spaces that are insufficiently characterized by linear value signals that have been the focus of most prior research on the topic. Major outstanding questions concern the role of OFC/ vmPFC in learning across tasks, in encoding of task-irrelevant aspects, and the role of hippocampus-PFC interactions.</p>","PeriodicalId":23325,"journal":{"name":"Trends in Neurosciences","volume":" ","pages":"1055-1069"},"PeriodicalIF":14.6000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Representational spaces in orbitofrontal and ventromedial prefrontal cortex: task states, values, and beyond.\",\"authors\":\"Nir Moneta, Shany Grossman, Nicolas W Schuck\",\"doi\":\"10.1016/j.tins.2024.10.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The orbitofrontal cortex (OFC) and ventromedial-prefrontal cortex (vmPFC) play a key role in decision-making and encode task states in addition to expected value. We review evidence suggesting a connection between value and state representations and argue that OFC / vmPFC integrate stimulus, context, and outcome information. Comparable encoding principles emerge in late layers of deep reinforcement learning (RL) models, where single nodes exhibit similar forms of mixed-selectivity, which enables flexible readout of relevant variables by downstream neurons. Based on these lines of evidence, we suggest that outcome-maximization leads to complex representational spaces that are insufficiently characterized by linear value signals that have been the focus of most prior research on the topic. Major outstanding questions concern the role of OFC/ vmPFC in learning across tasks, in encoding of task-irrelevant aspects, and the role of hippocampus-PFC interactions.</p>\",\"PeriodicalId\":23325,\"journal\":{\"name\":\"Trends in Neurosciences\",\"volume\":\" \",\"pages\":\"1055-1069\"},\"PeriodicalIF\":14.6000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Neurosciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.tins.2024.10.005\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/14 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Neurosciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.tins.2024.10.005","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/14 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Representational spaces in orbitofrontal and ventromedial prefrontal cortex: task states, values, and beyond.
The orbitofrontal cortex (OFC) and ventromedial-prefrontal cortex (vmPFC) play a key role in decision-making and encode task states in addition to expected value. We review evidence suggesting a connection between value and state representations and argue that OFC / vmPFC integrate stimulus, context, and outcome information. Comparable encoding principles emerge in late layers of deep reinforcement learning (RL) models, where single nodes exhibit similar forms of mixed-selectivity, which enables flexible readout of relevant variables by downstream neurons. Based on these lines of evidence, we suggest that outcome-maximization leads to complex representational spaces that are insufficiently characterized by linear value signals that have been the focus of most prior research on the topic. Major outstanding questions concern the role of OFC/ vmPFC in learning across tasks, in encoding of task-irrelevant aspects, and the role of hippocampus-PFC interactions.
期刊介绍:
For over four decades, Trends in Neurosciences (TINS) has been a prominent source of inspiring reviews and commentaries across all disciplines of neuroscience. TINS is a monthly, peer-reviewed journal, and its articles are curated by the Editor and authored by leading researchers in their respective fields. The journal communicates exciting advances in brain research, serves as a voice for the global neuroscience community, and highlights the contribution of neuroscientific research to medicine and society.