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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.