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Affective-associati...
Affective-associative two-process theory: a neurocomputational account of partial reinforcement extinction effects
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- Lowe, Robert (author)
- University of Gothenburg,Gothenburg University,Göteborgs universitet,Institutionen för tillämpad informationsteknologi (GU),Department of Applied Information Technology (GU),Department of Applied IT, University of Gothenburg, Gothenburg, Sweden,Interaction Lab
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- Almér, Alexander, 1967 (author)
- University of Gothenburg,Gothenburg University,Göteborgs universitet,Institutionen för tillämpad informationsteknologi (GU),Department of Applied Information Technology (GU),Department of Applied IT, University of Gothenburg, Gothenburg, Sweden
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- Billing, Erik, 1981- (author)
- Högskolan i Skövde,University of Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi,Interaction Lab (ILAB)
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- Sandamirskaya, Y. (author)
- Institute of Neuroinformatics, Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland,ETH Zürich
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- Balkenius, Christian (author)
- Lund University,Lunds universitet,Kognitionsvetenskap,Filosofiska institutionen,Institutioner,Humanistiska och teologiska fakulteterna,Cognitive Science,Department of Philosophy,Departments,Joint Faculties of Humanities and Theology,Cognitive Science, Lund University, Lund, Sweden
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(creator_code:org_t)
- 2017-09-14
- 2017
- English.
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In: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 111:5-6, s. 365-388
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Abstract
Subject headings
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- The partial reinforcement extinction effect (PREE) is an experimentally established phenomenon: behavioural response to a given stimulus is more persistent when previously inconsistently rewarded than when consistently rewarded. This phenomenon is, however, controversial in animal/human learning theory. Contradictory findings exist regarding when the PREE occurs. One body of research has found a within-subjects PREE, while another has found a within-subjects reversed PREE (RPREE). These opposing findings constitute what is considered the most important problem of PREE for theoreticians to explain. Here, we provide a neurocomputational account of the PREE, which helps to reconcile these seemingly contradictory findings of within-subjects experimental conditions. The performance of our model demonstrates how omission expectancy, learned according to low probability reward, comes to control response choice following discontinuation of reward presentation (extinction). We find that a PREE will occur when multiple responses become controlled by omission expectation in extinction, but not when only one omission-mediated response is available. Our model exploits the affective states of reward acquisition and reward omission expectancy in order to differentially classify stimuli and differentially mediate response choice. We demonstrate that stimulus-response (retrospective) and stimulus-expectation-response (prospective) routes are required to provide a necessary and sufficient explanation of the PREE versus RPREE data and that Omission representation is key for explaining the nonlinear nature of extinction data.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- HUMANIORA -- Filosofi, etik och religion -- Filosofi (hsv//swe)
- HUMANITIES -- Philosophy, Ethics and Religion -- Philosophy (hsv//eng)
Keyword
- Partial reinforcement
- Reinforcement learning
- Decision making
- Associative two-process theory
- orbitofrontal cortex
- behavioral momentum
- outcome expectancies
- multiple schedules
- reversed pree
- model
- hypothesis
- resistance
- persistence
- prediction
- Computer Science
- Neurosciences & Neurology
- Affect
- Partial reinforcement
- Interaction Lab (ILAB)
Publication and Content Type
- ref (subject category)
- art (subject category)
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