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Model-based lesion mapping of cognitive control using the Wisconsin Card Sorting Test

Gläscher, Jan and Adolphs, Ralph and Tranel, Daniel (2019) Model-based lesion mapping of cognitive control using the Wisconsin Card Sorting Test. Nature Communications, 10 . Art. No. 20. ISSN 2041-1723. PMCID PMC6318292.

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The role of the frontal lobes in cognition and behavior has long been enigmatic. Over the past decade, computational models have provided a powerful approach to understanding cognition and decision-making. Here, we used a model-based approach to analyze data from a classical task used to assess frontal lobe function, the Wisconsin Card Sorting Test. We applied computational modeling and voxel-based lesion-symptom mapping in 328 patients with focal lesions, to uncover cognitive processes and neural correlates of test scores. Our results reveal that lesions in the right prefrontal cortex are associated with elevated perseverative errors and reductions in the model parameter of sensitivity to punishment. These findings indicate that the capacity to flexibly switch between task sets requires the detection of contingency changes, which are enabled by a sensitivity to punishment that reduces perseverative errors. We demonstrate the power of model-based approaches in understanding patterns of deficits on classical neuropsychological tasks.

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URLURL TypeDescription CentralArticle
Gläscher, Jan0000-0002-1020-7115
Adolphs, Ralph0000-0002-8053-9692
Additional Information:© 2018 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Received 22 August 2017; Accepted 06 December 2018; Published 03 January 2019. We thank Friederike Irmen, Arnina Frank, and Anne Bert for help with coding the original test sheets into a digital format. This work was supported by the German Ministry of Education and Research (Bernstein Award for Computational Neuroscience, 01GQ1006) and the German Research Foundation (SFB TRR 169 “Crossmodal Learning”) to J.G., by a McDonnell Foundation Collaborative Action Award (#220020387) to D.T., by a Conte Center grant from the NIMH to R.A. and D.T. (2P50MH094258), and by the Carver Mead New Adventures Fund to R.A. Code availability: Custom-made MATLAB code is available upon request from the authors. Data availability: Data are available upon request from the authors, as permitted under HIPAA regulations. Author Contributions: J.G. and R.A. designed the research, D.T. collected the data, J.G. analyzed the data, and all authors wrote the paper. The authors declare no competing interests.
Funding AgencyGrant Number
Bundesministerium für Bildung und Forschung (BMBF)01GQ1006
Deutsche Forschungsgemeinschaft (DFG)SFB TRR 169
James S. McDonnell Foundation220020387
Carver Mead New Adventures FundUNSPECIFIED
PubMed Central ID:PMC6318292
Record Number:CaltechAUTHORS:20190107-103200381
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92110
Deposited By: Tony Diaz
Deposited On:07 Jan 2019 19:32
Last Modified:17 Jan 2020 22:53

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