Multiple Levels of Control Processes for Wisconsin Card Sorts: An Observational Study

Abstract

We explored short-term behavioral plasticity on the Modified Wisconsin Card Sorting Test (M-WCST) by deriving novel error metrics by stratifying traditional set loss and perseverative errors. Separating the rule set and the response set allowed for the measurement of performance across four trial types, crossing rule set (i.e., maintain vs. switch) and response demand (i.e., repeat vs. alternate). Critically, these four trial types can be grouped based on trial-wise feedback on t − 1 trials. Rewarded (correct) maintain t − 1 trials should lead to error enhancement when the response demands shift from repeat to alternate. In contrast, punished (incorrect) t − 1 trials should lead to error suppression when the response demands shift from repeat to alternate. The results supported the error suppression prediction: An error suppression effect (ESE) was observed across numerous patient samples. Exploratory analyses show that the ESE did not share substantial portions of variance with traditional neuropsychological measures of executive functioning. They further point into the direction that striatal or limbic circuit neuropathology may be associated with enhanced ESE. These data suggest that punishment of the recently executed response induces behavioral avoidance, which is detectable as the ESE on the WCST. The assessment of the ESE might provide an index of response-related avoidance learning on the WCST.

Cognitive impairment in patients with Neuro‐Sjögren

“…The CERAD‐PLUS is an established cognitive test battery originally developed as a screening for Alzheimer´s disease and designed to test executive functions, visuospatial understanding, language, and memory function through 12 subtests 16,18,19 . Table 1 displays a short description of the applied subtests following our previously published methodology 20 …”

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

“…Behavioral WCST indicators are typically the number of perseveration errors (i.e., erroneous category repetitions following negative feedback) and the number of set-loss errors (i.e., erroneous category switches following positive feedback) [27]. Performance on the WCST can be conceptualized as feedback-driven learning [42][43][44] because in order to identify the prevailing category, participants have to rely on feedback about the correctness of their current sorts: Positive feedback indicates that the executed sort was correct, whereas negative feedback indicates that the executed sort was incorrect. We showed in an earlier study [43] that WCST feedback affects both the cognitive selection of sorting categories and the sensorimotor selection of a particular response.…”

“…Performance on the WCST can be conceptualized as feedback-driven learning [42][43][44] because in order to identify the prevailing category, participants have to rely on feedback about the correctness of their current sorts: Positive feedback indicates that the executed sort was correct, whereas negative feedback indicates that the executed sort was incorrect. We showed in an earlier study [43] that WCST feedback affects both the cognitive selection of sorting categories and the sensorimotor selection of a particular response. 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).…”

“…We also incorporated a simple retention mechanism [64,65], which ensured that what was learned from feedback stimuli on a particular WCST trial remained available in mind for short periods of time. Furthermore, we conceptualized WCST performance at two parallel, yet distinct levels of learning [43,44]: The higher-level cognitive learning (which may also be referred to as cortical, declarative, or goal-directed) is completed by lower-level sensorimotor learning (which may also be referred to as striatal, procedural, or automatic). In the context of the WCST, cognitive learning considers objects of thought (i.e., which category to apply on a particular trial) that guide the selection of task-appropriate responses.…”

Parallel model-based and model-free reinforcement learning for card sorting performance

“…Following positive feedback, set-loss errors should be more frequent when their commitment implies repeating the previously executed responses. Kopp et al 50 reported asymmetrical behavioral evidence for response-level learning, namely a modulation of perseveration propensity by response demands in the absence of modulatory effects with regard to set-loss errors. Please note that we do not wish to imply that these processes are conscious (i.e., the depicted clouds might just as well reflect implicit processes).…”