Single-trial neural dynamics are dominated by richly varied movements
When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and...
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Published in | Nature neuroscience Vol. 22; no. 10; pp. 1677 - 1686 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.10.2019
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Abstract | When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered ‘noise’. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity.
The authors use a linear model to reveal how neural activity patterns are related to cognition or movements. They find that uninstructed movements dominate single-cell and population activity throughout the brain, outpacing task-related activity. |
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AbstractList | When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered 'noise'. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity. When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered ‘noise’. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity. The authors use a linear model to reveal how neural activity patterns are related to cognition or movements. They find that uninstructed movements dominate single-cell and population activity throughout the brain, outpacing task-related activity. When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered 'noise'. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity. The authors use a linear model to reveal how neural activity patterns are related to cognition or movements. They find that uninstructed movements dominate single-cell and population activity throughout the brain, outpacing task-related activity. |
Audience | Academic |
Author | Churchland, Anne K. Gluf, Steven Kaufman, Matthew T. Musall, Simon Juavinett, Ashley L. |
AuthorAffiliation | 1 Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, NY 2 Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 3 Division of Biological Sciences, UC San Diego, San Diego, CA 4 These authors contributed equally to this work |
AuthorAffiliation_xml | – name: 3 Division of Biological Sciences, UC San Diego, San Diego, CA – name: 4 These authors contributed equally to this work – name: 1 Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, NY – name: 2 Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL |
Author_xml | – sequence: 1 givenname: Simon surname: Musall fullname: Musall, Simon organization: Cold Spring Harbor Laboratory, Neuroscience – sequence: 2 givenname: Matthew T. surname: Kaufman fullname: Kaufman, Matthew T. organization: Cold Spring Harbor Laboratory, Neuroscience, Department of Organismal Biology and Anatomy, The University of Chicago, The Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, The University of Chicago – sequence: 3 givenname: Ashley L. surname: Juavinett fullname: Juavinett, Ashley L. organization: Cold Spring Harbor Laboratory, Neuroscience, Division of Biological Sciences, University of California, San Diego – sequence: 4 givenname: Steven surname: Gluf fullname: Gluf, Steven organization: Cold Spring Harbor Laboratory, Neuroscience – sequence: 5 givenname: Anne K. orcidid: 0000-0002-3205-3794 surname: Churchland fullname: Churchland, Anne K. email: churchland@cshl.edu organization: Cold Spring Harbor Laboratory, Neuroscience |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31551604$$D View this record in MEDLINE/PubMed |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 S.M., M.T.K. and A.K.C. designed the experiments. S.M. and S.G. trained animals and recorded widefield data. S.M. performed surgeries. M.T.K. and S.M. acquired 2-photon data, designed the linear model and performed data analysis. A.L.J. recorded and spike-sorted Neuropixels data. A.K.C., M.T.K and S.M. wrote the paper with assistance from S.G. and A.L.J.. S.M. and M.T.K. contributed equally. Author contributions |
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Snippet | When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks... |
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SubjectTerms | 14/63 14/69 631/378 631/378/116/2395 631/378/2649 631/378/2649/1409 64/60 Analysis Animal cognition Animal Genetics and Genomics Animals Auditory Perception - physiology Behavioral Sciences Biological Techniques Biomedical and Life Sciences Biomedicine Cerebral Cortex - diagnostic imaging Cerebral Cortex - physiology Cognition Cognition - physiology Cognitive ability Cognitive tasks Decision making Decision Making - physiology Human mechanics Laboratories Linear Models Mice Mice, Inbred C57BL Movement - physiology Neural circuitry Neurobiology Neuroimaging Neurons - physiology Neurosciences Physiological aspects Psychological aspects Psychomotor Performance - physiology Variables Variation Visual Perception - physiology |
Title | Single-trial neural dynamics are dominated by richly varied movements |
URI | https://link.springer.com/article/10.1038/s41593-019-0502-4 https://www.ncbi.nlm.nih.gov/pubmed/31551604 https://www.proquest.com/docview/2296636751 https://search.proquest.com/docview/2297125828 https://pubmed.ncbi.nlm.nih.gov/PMC6768091 |
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