Recent neuroscientific models of human behavior distinguish between different cognitive controllers: two instrumental systems (goal-directed and habitual) that maximize utility through learned actions, and a so-called Pavlovian system, which implements innate reactive responses. Although the interaction between instrumental and Pavlovian controllers has been suggested as a key process underlying emotional phenomena and surprising forms of misbehavior, few is known about it, especially in the sensorimotor aversive domain. With a combined experimental and computational approach, we study the interactions between instrumental (goal-directed) and Pavlovian processes in the aversive domain. First, we present a human experiment in which goal-directed and Pavlovian systems compete in order to control responses. The results indicate that Pavlovian processes can significantly interfere with goal-directed behavior. Second, we compare four alternative Bayesian models for their accuracy in modeling human performance. The results indicate a better fit for an architecture in which the Pavlovian controller can use both model-based and model-free features.

Interaction of goal-directed and pavlovian systems in aversive domains

Giovanni Pezzulo
2011

Abstract

Recent neuroscientific models of human behavior distinguish between different cognitive controllers: two instrumental systems (goal-directed and habitual) that maximize utility through learned actions, and a so-called Pavlovian system, which implements innate reactive responses. Although the interaction between instrumental and Pavlovian controllers has been suggested as a key process underlying emotional phenomena and surprising forms of misbehavior, few is known about it, especially in the sensorimotor aversive domain. With a combined experimental and computational approach, we study the interactions between instrumental (goal-directed) and Pavlovian processes in the aversive domain. First, we present a human experiment in which goal-directed and Pavlovian systems compete in order to control responses. The results indicate that Pavlovian processes can significantly interfere with goal-directed behavior. Second, we compare four alternative Bayesian models for their accuracy in modeling human performance. The results indicate a better fit for an architecture in which the Pavlovian controller can use both model-based and model-free features.
2011
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Istituto di Scienze e Tecnologie della Cognizione - ISTC
978-954-535-660-5
Goal-directed system
Pavlovian system
Bayesian model
implicit classical conditioning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/214968
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