Abstract

Cognitive inflexibility is a well-documented, yet non-specific corollary of many neurological diseases. Computational modeling of covert cognitive processes supporting cognitive flexibility may provide progress toward nosologically specific aspects of cognitive inflexibility. We review computational models of the Wisconsin Card Sorting Test (WCST), which represents a gold standard for the clinical assessment of cognitive flexibility. A parallel reinforcement-learning (RL) model provides the best conceptualization of individual trial-by-trial WCST responses among all models considered. Clinical applications of the parallel RL model suggest that patients with Parkinson’s disease (PD) and patients with amyotrophic lateral sclerosis (ALS) share a non-specific covert cognitive symptom: bradyphrenia. Impaired stimulus-response learning appears to occur specifically in patients with PD, whereas haphazard responding seems to occur specifically in patients with ALS. Computational modeling hence possesses the potential to reveal nosologically specific profiles of covert cognitive symptoms, which remain undetectable by traditionally applied behavioral methods. The present review exemplifies how computational neuropsychology may advance the assessment of cognitive flexibility. We discuss implications for neuropsychological assessment and directions for future research.

Highlights

  • Cognitive inflexibility is a well-documented, yet non-specific corollary of many neurological diseases

  • These results suggest a modulation of Perseveration errors (PEs) propensities by response demands; PEs become less likely when they imply repeating the response that has received a negative feedback on the previous trial

  • The dissociation of patterns of erroneous responses does not represent a satisfactory approach to the Analyses of patterns of erroneous responses may allow for the detection of particular behavioral effects on the Wisconsin Card Sorting Test (WCST), which in turn allow inferences about covert cognitive processes

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Summary

The Neuropsychology of Cognitive Flexibility

Maintaining goal-directed behavior in the face of novel situations is a fundamental requirement for everyday life. An impairment of any of these covert cognitive processes could become behaviorally manifest as increased PE propensities [11] Due to this process impurity, PE propensities may not achieve nosological specificity across a range of neurological diseases and psychiatric disorders. At the level of overt behavior on Trial t, the execution of response 1 indicates the application of the color category, i.e., a successful switch away from the number category. In this example, impaired updating results in the assumption that the number category is still correct, the received negative feedback indicates that the application of the number category was incorrect. Please note that we do not wish to imply that these covert cognitive processes are conscious (i.e., the depicted clouds might just as well reflect implicit processes)

Assessing Covert Cognitive Processes on the WCST
Dissociating Patterns of Erroneous Responses
Participants showed response onfound
Identifying and Isolating Latent Variables
Factor Analyses
Computational Modeling
Toward a Computational Neuropsychology of Cognitive Flexibility
The Attentional-Updating Model
The Parallel Reinforcement-Learning Model
Comparison of Mechanistic Models
Assessing Covert Cognitive Symptoms in Neurological Diseases
Parkinson’s Disease
The execution
Dopamine Replacement Therapy in Patients with PD
Amyotrophic Lateral Sclerosis
Comparison
Implications for Neuropsychological Assessment
Outlook
Conclusions
Methods

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