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      Dopamine transients follow a striatal gradient of reward time horizons

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          Abstract

          Animals make predictions to guide their behavior and update those predictions through experience. Transient increases in dopamine (DA) are thought to be critical signals for updating predictions. However, it is unclear how this mechanism handles a wide range of behavioral timescales—from seconds or less (for example, if singing a song) to potentially hours or more (for example, if hunting for food). Here we report that DA transients in distinct rat striatal subregions convey prediction errors based on distinct time horizons. DA dynamics systematically accelerated from ventral to dorsomedial to dorsolateral striatum, in the tempo of spontaneous fluctuations, the temporal integration of prior rewards and the discounting of future rewards. This spectrum of timescales for evaluative computations can help achieve efficient learning and adaptive motivation for a broad range of behaviors.

          Abstract

          Mohebi et al. report that dopamine (DA) pulses in different rat striatal subregions signal prediction errors across different timescales. In this way, one learning process may achieve a range of adaptive behaviors.

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          Most cited references87

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          Long Short-Term Memory

          Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We briefly review Hochreiter's (1991) analysis of this problem, then address it by introducing a novel, efficient, gradient-based method called long short-term memory (LSTM). Truncating the gradient where this does not do harm, LSTM can learn to bridge minimal time lags in excess of 1000 discrete-time steps by enforcing constant error flow through constant error carousels within special units. Multiplicative gate units learn to open and close access to the constant error flow. LSTM is local in space and time; its computational complexity per time step and weight is O(1). Our experiments with artificial data involve local, distributed, real-valued, and noisy pattern representations. In comparisons with real-time recurrent learning, back propagation through time, recurrent cascade correlation, Elman nets, and neural sequence chunking, LSTM leads to many more successful runs, and learns much faster. LSTM also solves complex, artificial long-time-lag tasks that have never been solved by previous recurrent network algorithms.
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            Golden Eggs and Hyperbolic Discounting

            D. Laibson (1997)
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              Human and rodent homologies in action control: corticostriatal determinants of goal-directed and habitual action.

              Recent behavioral studies in both humans and rodents have found evidence that performance in decision-making tasks depends on two different learning processes; one encoding the relationship between actions and their consequences and a second involving the formation of stimulus-response associations. These learning processes are thought to govern goal-directed and habitual actions, respectively, and have been found to depend on homologous corticostriatal networks in these species. Thus, recent research using comparable behavioral tasks in both humans and rats has implicated homologous regions of cortex (medial prefrontal cortex/medial orbital cortex in humans and prelimbic cortex in rats) and of dorsal striatum (anterior caudate in humans and dorsomedial striatum in rats) in goal-directed action and in the control of habitual actions (posterior lateral putamen in humans and dorsolateral striatum in rats). These learning processes have been argued to be antagonistic or competing because their control over performance appears to be all or none. Nevertheless, evidence has started to accumulate suggesting that they may at times compete and at others cooperate in the selection and subsequent evaluation of actions necessary for normal choice performance. It appears likely that cooperation or competition between these sources of action control depends not only on local interactions in dorsal striatum but also on the cortico-basal ganglia network within which the striatum is embedded and that mediates the integration of learning with basic motivational and emotional processes. The neural basis of the integration of learning and motivation in choice and decision-making is still controversial and we review some recent hypotheses relating to this issue.
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                Author and article information

                Contributors
                joshua.berke@ucsf.edu
                Journal
                Nat Neurosci
                Nat Neurosci
                Nature Neuroscience
                Nature Publishing Group US (New York )
                1097-6256
                1546-1726
                6 February 2024
                6 February 2024
                2024
                : 27
                : 4
                : 737-746
                Affiliations
                [1 ]Department of Neurology, University of California San Francisco, ( https://ror.org/043mz5j54) San Francisco, CA USA
                [2 ]Department of Psychiatry and Behavioral Sciences, University of California San Francisco, ( https://ror.org/043mz5j54) San Francisco, CA USA
                [3 ]Neuroscience Graduate Program, University of California San Francisco, ( https://ror.org/043mz5j54) San Francisco, CA USA
                [4 ]Kavli Institute for Fundamental Neuroscience, University of California San Francisco, ( https://ror.org/043mz5j54) San Francisco, CA USA
                [5 ]Weill Institute for Neurosciences, University of California San Francisco, ( https://ror.org/043mz5j54) San Francisco, CA USA
                Author information
                http://orcid.org/0000-0001-7291-3448
                http://orcid.org/0000-0003-1436-6823
                Article
                1566
                10.1038/s41593-023-01566-3
                11001583
                38321294
                767ffd73-0ea1-40be-9ce4-94e4873c3a26
                © The Author(s) 2024

                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
                : 12 May 2022
                : 21 December 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000026, U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA);
                Award ID: R01DA045783
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000065, U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS);
                Award ID: R01NS123516
                Award ID: R01NS116626
                Award Recipient :
                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: R21AA027157
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000874, Brain and Behavior Research Foundation (Brain & Behavior Research Foundation);
                Award ID: NARSAD YIA 29361
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: K01MH126223
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature America, Inc. 2024

                Neurosciences
                learning and memory,psychology,reward,neurotransmitters
                Neurosciences
                learning and memory, psychology, reward, neurotransmitters

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