Literature DB >> 31021132

Time-scale-invariant information-theoretic contingencies in discrimination learning.

Abigail Kalmbach1, Eileen Chun2, Kathleen Taylor1, Charles R Gallistel3, Peter D Balsam1.   

Abstract

Animals optimize their behavior to maximize rewards by utilizing cues from the environment. In discrimination learning, cues signal when rewards can and cannot be earned by making a particular response. In our experiment, we trained male mice to press a lever to receive a reward on a random interval schedule. We then introduced a prolonged tone (20, 40, or 80 sec), during which no rewards could be earned. We sought to test our hypothesis that the duration of the tone and frequency of reward during the inter-tone-intervals affect the informativeness of cues and led to differences in discriminative behavior. Learning was expressed as an increase in lever pressing during the intertrial interval (ITI) and, when the informativeness of the cue was high, animals also reduced their lever pressing during the tone. Additionally, we found that the depth of discriminative learning was linearly related to the informativeness of the cues. Our results show that the time-scale invariant information-theoretic definition of contingency applied to excitatory conditioning can also be applied to inhibitory conditioning. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Year:  2019        PMID: 31021132      PMCID: PMC7771212          DOI: 10.1037/xan0000205

Source DB:  PubMed          Journal:  J Exp Psychol Anim Learn Cogn        ISSN: 2329-8456            Impact factor:   2.478


  37 in total

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Review 8.  Interactions of timing and prediction error learning.

Authors:  Kimberly Kirkpatrick
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Authors:  Charles R Gallistel; Peter D Balsam
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10.  Role of the Perigenual Anterior Cingulate and Orbitofrontal Cortex in Contingency Learning in the Marmoset.

Authors:  Stacey A W Jackson; Nicole K Horst; Andrew Pears; Trevor W Robbins; Angela C Roberts
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  3 in total

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2.  Dopamine encodes real-time reward availability and transitions between reward availability states on different timescales.

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