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A Dynamic Model of Response Times in the Go/No-Go Discrimination Task

Dynamic cognitive models can capture underlying cognitive processes that arise from the closed-loop interaction between an agent and its environment. A dynamic cognitive model of response times in a Go/No-Go Discrimination task with six motivationally distinct conditions is developed. The Go/No-Go Discrimination task is a reliable measure of passive avoidance, and it is considered an analog for real world approach-avoidance motivational conflict. We show that the cognitive model of response times provides more insight into the dynamics of cognitive processes involved in reward-approach and punishment-avoidance decisions than standard data analysis techniques. The parameters of the model inform us of underlying cognitive mechanisms because they have an established psychological meaning and allow us to quantify a subject’s ability and response caution. Using these model parameters, we focus on the differences between subjects with varying degrees of substance abuse and antisocial behavioral disorders and show that there are reliable differences between the decision mechanisms of these subjects. Using data from executive working memory tasks, we postulate that these differences in cognitive processes might be due to differences in working memory capacity. Ultimately, we show that dynamic cognitive modeling has the potential to provide valuable insights into clinical phenomena that cannot be captured by traditional data analysis techniques.