A Computational Study of Executive Dysfunction in Amyotrophic Lateral Sclerosis

Steinke, Alexander; Lange, Florian; Seer, Caroline; Petri, Susanne; Kopp, Bruno

doi:10.3390/jcm9082605

Cited by 6 publications

(11 citation statements)

References 141 publications

(316 reference statements)

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“…Our exemplary comparison of profiles of covert cognitive symptoms of patients with PD and patients with ALS corroborates this hypothesis [ 109 , 115 ]. Computational modeling revealed a disease-nonspecific alteration in latent variables.…”

Section: Toward a Computational Neuropsychology Of Cognitive Flexisupporting

confidence: 71%

“…In another computational study [ 115 ], we characterized covert cognitive symptoms associated with ALS pathophysiology. Therefore, we reanalyzed data from 18 patients with ALS and 21 matched HC participants who completed a cWCST variant [ 29 ] by means of the parallel RL model.…”

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

“…Haphazard responding may relate to motor impairments in patients with ALS. For example, haphazard responding could arise from deficient fine motor skills of patients with ALS that obstruct successful cWCST responding [ 115 , 131 ].…”

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

“…The reported covert cognitive symptoms in patients with PD and patients with ALS demonstrate that computational neuropsychology possesses the potential to reveal nosologically specific profiles of covert cognitive symptoms. Figure 8 summarizes profiles of covert cognitive symptoms in patients with PD and patients with ALS [ 109 , 115 ].…”

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

“…The present review demonstrates how computational neuropsychology may provide progress with regard to the neuropsychological assessment of cognitive flexibility [ 109 , 115 ]. First, as delineated above, computational neuropsychology possesses the potential to reveal nosologically specific profiles of covert cognitive symptoms, which remain yet undetectable by traditional behavioral methods of neuropsychological assessment.…”

Section: Implications For Neuropsychological Assessmentmentioning

confidence: 99%

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Toward a Computational Neuropsychology of Cognitive Flexibility

Steinke

Kopp

2020

Brain Sciences

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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.

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Section: Toward a Computational Neuropsychology Of Cognitive Flexisupporting

confidence: 71%

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

Section: Toward a Computational Neuropsychology Of Cognitive Fleximentioning

confidence: 99%

Section: Implications For Neuropsychological Assessmentmentioning

confidence: 99%

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Toward a Computational Neuropsychology of Cognitive Flexibility

Steinke

Kopp

2020

Brain Sciences

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Anhedonia and sensitivity to punishment in schizophrenia, depression and opiate use disorder

Ossola

Garrett

Biso

et al. 2023

Journal of Affective Disorders

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

Steinke

Lange

Kopp

2020

Sci Rep

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The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the assessment of cognitive flexibility. On the WCST, repeating a sorting category following negative feedback is typically treated as indicating reduced cognitive flexibility. Therefore such responses are referred to as ‘perseveration’ errors. Recent research suggests that the propensity for perseveration errors is modulated by response demands: They occur less frequently when their commitment repeats the previously executed response. Here, we propose parallel reinforcement-learning models of card sorting performance, which assume that card sorting performance can be conceptualized as resulting from model-free reinforcement learning at the level of responses that occurs in parallel with model-based reinforcement learning at the categorical level. We compared parallel reinforcement-learning models with purely model-based reinforcement learning, and with the state-of-the-art attentional-updating model. We analyzed data from 375 participants who completed a computerized WCST. Parallel reinforcement-learning models showed best predictive accuracies for the majority of participants. Only parallel reinforcement-learning models accounted for the modulation of perseveration propensity by response demands. In conclusion, parallel reinforcement-learning models provide a new theoretical perspective on card sorting and it offers a suitable framework for discerning individual differences in latent processes that subserve behavioral flexibility.

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A Computational Study of Executive Dysfunction in Amyotrophic Lateral Sclerosis

Cited by 6 publications

References 141 publications

Toward a Computational Neuropsychology of Cognitive Flexibility

Toward a Computational Neuropsychology of Cognitive Flexibility

Anhedonia and sensitivity to punishment in schizophrenia, depression and opiate use disorder

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

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