Toward a computational cognitive neuropsychology of Wisconsin card sorts: a showcase study in Parkinson’s disease

Abstract

The Wisconsin Card Sorting Test (WCST) is an instrument for the clinical assessment of executive functions. Computational modeling of latent cognitive processes offers a route toward improved interpretability of performance on neuropsychological tests. We implemented a computational model by Bishara et al. (Journal of Mathematical Psychology, 54(1), 5-13, 2010) that allows for evaluating the role of feedback-based attentional learning. We investigated if the model differentiates between Parkinson's disease (PD) patients on and off dopaminergic medication. We reanalyzed data from 32 patients with idiopathic PD and 35 matched healthy controls, which completed a computerized version of the WCST. The PD sample was divided into patients tested on (n = 18) and off (n = 14) dopaminergic medication. Model performance was assessed via posterior probabilities and simulations of WCST error scores. Individual model parameters were used for group comparisons. The best performing model configuration showed a single learning rate parameter for positive and negative feedback and recovered the observed WCST perseveration error and set-loss error rates. The occurrence of inference errors could not be accounted for by that model configuration. We did not observe evidence for differences in model parameters between the examined groups of individuals. Our results indicate that assuming distinct, feedback-specific learning processes are not superior to feedback-type unspecific processes in accounting for performance on the computerized WCST. Specifically, the studied model successfully accounted for some, but not all, aspects of test performance. The model parameters did not differentiate between PD patients on and off their dopaminergic medication, a finding that we discuss in the context of study design. (WCST;Berg 1948;Grant and Berg 1948;Heaton et al. 1993; Schretlen 2010) represents a standard tool for the neuropsychological assessment of executive functions (Diamond 2013;Miller and Cohen 2001). Performance on the WCST is sensitive to frontal lobe lesions (e.g., Alvarez and Emory 2006;Barceló and Knight 2002;Demakis 2003;Milner 1963) and to numerous neurological diseases, including Parkinson's disease (PD; e.g., Kudlicka et al. 2011;Dirnberger and Jahanshahi 2013) or amyotrophic lateral sclerosis (e.g., Lange et al. 2016c). However, the complexity of the WCST renders it difficult to infer which cognitive processes generate the observable behavior on the test. In this study, we apply computational modeling as a possible route toward a better interpretability of WCST performance.The WCST is considered as an assessment instrument for individual abilities in cognitive flexibility (Diamond 2013;Miller and Cohen 2001). Participants are instructed to sort a stimulus according to one of four key cards. Card sorts can accord to one of three viable rules that refer to the color, the shape, or the number of displayed objects. In order to figure out the prevailing rule, the participant has to follow the examiners feedback, as shown...

Computational Modeling for Neuropsychological Assessment of Bradyphrenia in Parkinson’s Disease

“…To account for a potential effect of the repeated assessment on cWCST performance, we also assessed HC participants at two testing sessions, and we included the testing session as an additional within-subjects factor in the analyses. Note that analyses of first testing sessions were reported by [48,66].…”

“…We thus conceptualized feedback-driven learning on the WCST as occurring at two distinguishable levels in parallel, i.e., as sensorimotor learning at the lower level (i.e., which response to execute) and as cognitive learning at the higher level (i.e., which category to apply). [27,[45][46][47][48]. On Trial t, a stimulus card (one green cross) could be sorted by the color category (inner left key card, response 2), the number category (far left key card, response 1), or the shape category (inner right key card, response 3).…”

“…A subsequently presented negative feedback stimulus (i.e., the visually presented Figure 1. An exemplary trial sequence on the computerized Wisconsin Card Sorting Test (WCST) [27,[45][46][47][48]. On Trial t, a stimulus card (one green cross) could be sorted by the color category (inner left key card, response 2), the number category (far left key card, response 1), or the shape category (inner right key card, response 3).…”

“…In our opinion, such progress primarily depends on further improvements at the hitherto much neglected behavioral level. These improvements include (though are not limited to) applying more elaborate data analysis methods such as computational modeling techniques [42,[48][49][50][51][52].…”

“…The second goal was characterizing the specific learning dysfunctions that are associated with disease pathology and/or DA replacement therapy in patients with PD. In order to achieve these goals, we studied patients with PD and matched healthy control (HC) participants twice on a computerized version of the WCST (cWCST) [27,[45][46][47][48]. Patients with PD were assessed 'on' DA medication and 'off' DA medication (i.e., after withdrawal of DA medication).…”