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      Information normally considered task-irrelevant drives decision-making and affects premotor circuit recruitment

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          Abstract

          Decision-making is a continuous and dynamic process with prior experience reflected in and used by the brain to guide adaptive behavior. However, most neurobiological studies constrain behavior and/or analyses to task-related variables, not accounting for the continuous internal and temporal space in which they occur. We show mice rely on information learned through recent and longer-term experience beyond just prior actions and reward - including checking behavior and the passage of time - to guide self-initiated, self-paced, and self-generated actions. These experiences are represented in secondary motor cortex (M2) activity and its projections into dorsal medial striatum (DMS). M2 integrates this information to bias strategy-level decision-making, and DMS projections reflect specific aspects of this recent experience to guide actions. This suggests diverse aspects of experience drive decision-making and its neural representation, and shows premotor corticostriatal circuits are crucial for using selective aspects of experiential information to guide adaptive behavior.

          Abstract

          Prior experience is used by the brain to guide adaptive behaviour during decision making. Here, the authors show that mice also selectively use information learned through recent and longer-term experience beyond just prior actions and reward to guide adaptive behaviour.

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          Most cited references43

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          Neuroscience Needs Behavior: Correcting a Reductionist Bias.

          There are ever more compelling tools available for neuroscience research, ranging from selective genetic targeting to optogenetic circuit control to mapping whole connectomes. These approaches are coupled with a deep-seated, often tacit, belief in the reductionist program for understanding the link between the brain and behavior. The aim of this program is causal explanation through neural manipulations that allow testing of necessity and sufficiency claims. We argue, however, that another equally important approach seeks an alternative form of understanding through careful theoretical and experimental decomposition of behavior. Specifically, the detailed analysis of tasks and of the behavior they elicit is best suited for discovering component processes and their underlying algorithms. In most cases, we argue that study of the neural implementation of behavior is best investigated after such behavioral work. Thus, we advocate a more pluralistic notion of neuroscience when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.
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            Actions and Habits: The Development of Behavioural Autonomy

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              Scalar Timing in Memory

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                Author and article information

                Contributors
                cgremel@ucsd.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 April 2022
                19 April 2022
                2022
                : 13
                : 2134
                Affiliations
                [1 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Psychology, , University of California San Diego, ; La Jolla, CA 92093 USA
                [2 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, The Neurosciences Graduate Program, , University of California San Diego, ; La Jolla, CA 92093 USA
                Author information
                http://orcid.org/0000-0002-8899-2109
                http://orcid.org/0000-0002-8710-0543
                Article
                29807
                10.1038/s41467-022-29807-2
                9018678
                35440120
                4ea5eea2-0405-475c-b6a2-423b6a0e688f
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 July 2021
                : 24 March 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000027, U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA);
                Award ID: F31AA027439
                Award ID: F32AA026776
                Award ID: R01AA026077
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: DGE-1650112
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: FundRef https://doi.org/10.13039/100001391, Whitehall Foundation (Whitehall Foundation, Inc.);
                Award ID: Whitehall Foundation Award
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Categories
                Article
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                © The Author(s) 2022

                Uncategorized
                operant learning,cortex,decision
                Uncategorized
                operant learning, cortex, decision

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