naa a22 4500 528783289 20180924065515.0 cr unu---uuuuu 180924e201712 xx s 000 0 eng 10.3929/ethz-b-000192497 doi 10.1007/s00422-017-0730-1 doi (ETHRESEARCH)oai:www.research-collection.ethz.ch:20.500.11850/192497 Affective-associative two-process theory: a neurocomputational account of partial reinforcement extinction effects [Elektronische Daten] [Robert Lowe, Alexander Almér, Erik Billing, Yulia Sandamirskaya, Christian Balkenius] Open access ethresearch 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. Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 ethresearch Partial reinforcement ethresearch Reinforcement learning ethresearch Decision making ethresearch Associative two-process theory ethresearch Affect ethresearch Lowe Robert joint author Almér Alexander joint author Billing Erik joint author Sandamirskaya Yulia joint author Balkenius Christian joint author Biological Cybernetics Berlin : Springer 111 (5-6), pp. 365-388 http://hdl.handle.net/20.500.11850/192497 text/html WWW-Backlink auf das Repository (Open access) 1 Journal Article ethresearch ETHRESEARCH 856 40 http://hdl.handle.net/20.500.11850/192497 text/html WWW-Backlink auf das Repository (Open access) ETHRESEARCH 700 1- Lowe Robert joint author ETHRESEARCH 700 1- Almér Alexander joint author ETHRESEARCH 700 1- Billing Erik joint author ETHRESEARCH 700 1- Sandamirskaya Yulia joint author ETHRESEARCH 700 1- Balkenius Christian joint author ETHRESEARCH 773 0- Biological Cybernetics Berlin : Springer 111 (5-6), pp. 365-388 BK010053 XK010053 XK010000 ETHRESEARCH ETHRESEARCH ETHRESEARCH Journal Article Open access