Sequential learning models for the Wisconsin card sort task: Assessing processes in substance dependent individuals

The Wisconsin card sort task (WCST) is a commonly used neuropsychological test of executive or frontal lobe functioning. Traditional behavioral measures from the task (e.g., perseverative errors) distinguish healthy controls from clinical populations, but such measures can be difficult to interpret. In an attempt to supplement traditional measures, we developed and tested a family of sequential learning models that allowed for estimation of processes at the individual subject level in the WCST. Testing the model with substance dependent individuals and healthy controls, the model parameters significantly predicted group membership, even when controlling for traditional behavioral measures from the task. Substance dependence was associated with (a) slower attention shifting following punished trials and (b) reduced decision consistency. Results suggest that model parameters may offer both incremental content validity and incremental predictive validity.