{"title":"突触可塑性的形式和功能。","authors":"Jeffrey C Magee, Christine Grienberger","doi":"10.1146/annurev-neuro-090919-022842","DOIUrl":null,"url":null,"abstract":"<p><p>Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":"43 ","pages":"95-117"},"PeriodicalIF":12.1000,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-090919-022842","citationCount":"261","resultStr":"{\"title\":\"Synaptic Plasticity Forms and Functions.\",\"authors\":\"Jeffrey C Magee, Christine Grienberger\",\"doi\":\"10.1146/annurev-neuro-090919-022842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.</p>\",\"PeriodicalId\":8008,\"journal\":{\"name\":\"Annual review of neuroscience\",\"volume\":\"43 \",\"pages\":\"95-117\"},\"PeriodicalIF\":12.1000,\"publicationDate\":\"2020-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1146/annurev-neuro-090919-022842\",\"citationCount\":\"261\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual review of neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-neuro-090919-022842\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/2/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual review of neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1146/annurev-neuro-090919-022842","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/2/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.
期刊介绍:
The Annual Review of Neuroscience is a well-established and comprehensive journal in the field of neuroscience, with a rich history and a commitment to open access and scholarly communication. The journal has been in publication since 1978, providing a long-standing source of authoritative reviews in neuroscience.
The Annual Review of Neuroscience encompasses a wide range of topics within neuroscience, including but not limited to: Molecular and cellular neuroscience, Neurogenetics, Developmental neuroscience, Neural plasticity and repair, Systems neuroscience, Cognitive neuroscience, Behavioral neuroscience, Neurobiology of disease. Occasionally, the journal also features reviews on the history of neuroscience and ethical considerations within the field.