No abstract

Performance deficits on the Wisconsin Card Sorting Test (WCST) in patients with prefrontal cortex (PFC) lesions are traditionally interpreted as evidence for a role of the PFC in cognitive flexibility. However, WCST deficits do not occur exclusively after PFC lesions, but also in various neurological and psychiatric disorders. We propose a multi-component approach that can accommodate this pattern of omnipresent WCST deficits: the WCST is not a pure test of cognitive flexibility, but relies on the effective functioning of multiple dissociable cognitive components. Our review of recent efforts to decompose WCST performance deficits supports this view by revealing that WCST deficits in different neurological disorders can be attributed to alterations in different components. Frontoparietal changes underlying impaired set shifting seem to give rise to WCST deficits in patients with amyotrophic lateral sclerosis, whereas the WCST deficits associated with primary dystonia and Parkinson's disease are rather related to frontostriatal changes underlying deficient rule inference. Clinical implications of these findings and of a multi-component view of WCST performance are discussed.

Rule inference on WCST-like card-sorting tasks appeared to be selectively impaired when the amount of information to be integrated in working memory increases or when working memory capacity is reduced (as in older individuals). Our findings indicate that measuring integration errors as an index of a distinct rule-inference process can improve the understanding and interpretability of WCST performance. (PsycINFO Database Record

The neural mechanisms of cognitive dysfunctions in neurological diseases remain poorly understood. Here, we conjecture that this unsatisfying state-of-the-art is in part due to the non-specificity of the typical behavioral indicators for cognitive dysfunctions. Our study addresses the topic by advancing the assessment of cognitive dysfunctions through computational modeling. We investigate bradyphrenia in Parkinson’s disease (PD) as an exemplary case of cognitive dysfunctions in neurological diseases. Our computational model conceptualizes trial-by-trial behavioral data as resulting from parallel cognitive and sensorimotor reinforcement learning. We assessed PD patients ‘on’ and ‘off’ their dopaminergic medication and matched healthy control (HC) participants on a computerized version of the Wisconsin Card Sorting Test. PD patients showed increased retention of learned cognitive information and decreased retention of learned sensorimotor information from previous trials in comparison to HC participants. Systemic dopamine replacement therapy did not remedy these cognitive dysfunctions in PD patients but incurred non-desirable side effects such as decreasing cognitive learning from positive feedback. Our results reveal novel insights into facets of bradyphrenia that are indiscernible by observable behavioral indicators of cognitive dysfunctions. We discuss how computational modeling may contribute to the advancement of future research on brain–behavior relationships and neuropsychological assessment.