{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T07:04:15Z","timestamp":1790319855389,"version":"4.1.0"},"reference-count":53,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2021,2,5]],"date-time":"2021-02-05T00:00:00Z","timestamp":1612483200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Neural activity is often low dimensional and dominated by only a few prominent neural covariation patterns. It has been hypothesised that these covariation patterns could form the building blocks used for fast and flexible motor control. Supporting this idea, recent experiments have shown that monkeys can learn to adapt their neural activity in motor cortex on a timescale of minutes, given that the change lies within the original low-dimensional subspace, also called neural manifold. However, the neural mechanism underlying this within-manifold adaptation remains unknown. Here, we show in a computational model that modification of recurrent weights, driven by a learned feedback signal, can account for the observed behavioural difference between within- and outside-manifold learning. Our findings give a new perspective, showing that recurrent weight changes do not necessarily lead to change in the neural manifold. 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Michaels","year":"2019","journal-title":"bioRxiv"},{"issue":"7","key":"pcbi.1008621.ref045","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1038\/s41593-019-0414-3","article-title":"Circuit mechanisms for the maintenance and manipulation of information in working memory","volume":"22","author":"NY Masse","year":"2019","journal-title":"Nature neuroscience"},{"key":"pcbi.1008621.ref046","doi-asserted-by":"crossref","first-page":"e43299","DOI":"10.7554\/eLife.43299","article-title":"Local online learning in recurrent networks with random feedback","volume":"8","author":"JM Murray","year":"2019","journal-title":"eLife"},{"key":"pcbi.1008621.ref047","article-title":"Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets","author":"G Bellec","year":"2019","journal-title":"arXiv"},{"issue":"7","key":"pcbi.1008621.ref048","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1016\/S0959-4388(99)00028-8","article-title":"Internal models for motor control and trajectory planning","volume":"9","author":"M Kawato","year":"1999","journal-title":"Current Opinion in Neurobiology"},{"issue":"4","key":"pcbi.1008621.ref049","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1038\/s41593-018-0095-3","article-title":"Learning by neural reassociation","volume":"21","author":"MD Golub","year":"2018","journal-title":"Nature neuroscience"},{"issue":"11","key":"pcbi.1008621.ref050","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1038\/81497","article-title":"Computational principles of movement neuroscience","volume":"3","author":"DM Wolpert","year":"2000","journal-title":"Nature neuroscience"},{"issue":"11","key":"pcbi.1008621.ref051","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1038\/nn963","article-title":"Optimal feedback control as a theory of motor coordination","volume":"5","author":"E Todorov","year":"2002","journal-title":"Nature 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