Literature DB >> 24602013

Lesions of dorsal striatum eliminate lose-switch responding but not mixed-response strategies in rats.

Ivan Skelin1, Rhys Hakstol, Jenn VanOyen, Dominic Mudiayi, Leonardo A Molina, Victoria Holec, Nancy S Hong, David R Euston, Robert J McDonald, Aaron J Gruber.   

Abstract

We used focal brain lesions in rats to examine how dorsomedial (DMS) and dorsolateral (DLS) regions of the striatum differently contribute to response adaptation driven by the delivery or omission of rewards. Rats performed a binary choice task under two modes: one in which responses were rewarded on half of the trials regardless of choice; and another 'competitive' one in which only unpredictable choices were rewarded. In both modes, control animals were more likely to use a predictable lose-switch strategy than animals with lesions of either DMS or DLS. Animals with lesions of DMS presumably relied more on DLS for behavioural control, and generated repetitive responses in the first mode. These animals then shifted to a random response strategy in the competitive mode, thereby performing better than controls or animals with DLS lesions. Analysis using computational models of reinforcement learning indicated that animals with striatal lesions, particularly of the DLS, had blunted reward sensitivity and less stochasticity in the choice mechanism. These results provide further evidence that the rodent DLS is involved in rapid response adaptation that is more sophisticated than that embodied by the classic notion of habit formation driven by gradual stimulus-response learning.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Entities:  

Keywords:  decision-making; dorsolateral striatum; dorsomedial striatum; matching pennies; win-stay lose-switch

Mesh:

Year:  2014        PMID: 24602013     DOI: 10.1111/ejn.12518

Source DB:  PubMed          Journal:  Eur J Neurosci        ISSN: 0953-816X            Impact factor:   3.386


  11 in total

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2.  Distinct Medial Orbitofrontal-Striatal Circuits Support Dissociable Component Processes of Risk/Reward Decision-Making.

Authors:  Nicole L Jenni; Griffin Rutledge; Stan B Floresco
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3.  Concomitant Processing of Choice and Outcome in Frontal Corticostriatal Ensembles Correlates with Performance of Rats.

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Journal:  Cereb Cortex       Date:  2021-07-29       Impact factor: 5.357

4.  Role of dopamine D2 receptors in optimizing choice strategy in a dynamic and uncertain environment.

Authors:  Shinae Kwak; Namjung Huh; Ji-Seon Seo; Jung-Eun Lee; Pyung-Lim Han; Min W Jung
Journal:  Front Behav Neurosci       Date:  2014-10-28       Impact factor: 3.558

5.  The Memory Trace Supporting Lose-Shift Responding Decays Rapidly after Reward Omission and Is Distinct from Other Learning Mechanisms in Rats.

Authors:  Aaron J Gruber; Rajat Thapa
Journal:  eNeuro       Date:  2016-11-17

6.  Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning.

Authors:  Eric Chalmers; Artur Luczak; Aaron J Gruber
Journal:  Front Comput Neurosci       Date:  2016-12-12       Impact factor: 2.380

7.  Feeder Approach between Trials Is Increased by Uncertainty and Affects Subsequent Choices.

Authors:  Aaron J Gruber; Rajat Thapa; Sienna H Randolph
Journal:  eNeuro       Date:  2018-01-08

8.  CACNA1C gene regulates behavioral strategies in operant rule learning.

Authors:  Georgia Koppe; Anne Stephanie Mallien; Stefan Berger; Dusan Bartsch; Peter Gass; Barbara Vollmayr; Daniel Durstewitz
Journal:  PLoS Biol       Date:  2017-06-12       Impact factor: 8.029

9.  Lose-Shift Responding in Humans Is Promoted by Increased Cognitive Load.

Authors:  Victorita E Ivan; Parker J Banks; Kris Goodfellow; Aaron J Gruber
Journal:  Front Integr Neurosci       Date:  2018-03-08

10.  Cognitive impairment in a young marmoset reveals lateral ventriculomegaly and a mild hippocampal atrophy: a case report.

Authors:  A Sadoun; K Strelnikov; E Bonté; C Fonta; P Girard
Journal:  Sci Rep       Date:  2015-11-03       Impact factor: 4.379

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