Disentangling poststroke cognitive deficits and their neuroanatomical correlates through combined multivariable and multioutcome lesion‐symptom mapping

Author:

Weaver Nick A.1ORCID,Mamdani Muhammad Hasnain2,Lim Jae‐Sung3ORCID,Biesbroek Johannes Matthijs1ORCID,Biessels Geert Jan1ORCID,Huenges Wajer Irene M. C.14,Kang Yeonwook56,Kim Beom Joon7,Lee Byung‐Chul5,Lee Keon‐Joo8,Yu Kyung‐Ho5,Bae Hee‐Joon7ORCID,Bzdok Danilo29ORCID,Kuijf Hugo J.10ORCID

Affiliation:

1. Department of Neurology and Neurosurgery UMC Utrecht Brain Center Utrecht The Netherlands

2. Department of Biomedical Engineering, Faculty of Medicine, McConnell Brain Imaging Centre, School of Computer Science Montreal Neurological Institute (MNI), McGill University Montreal Canada

3. Department of Neurology, Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea

4. Experimental Psychology Helmholtz Institute, Utrecht University Utrecht The Netherlands

5. Department of Neurology Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine Anyang Republic of Korea

6. Department of Psychology Hallym University Chuncheon Republic of Korea

7. Department of Neurology Seoul National University Bundang Hospital, Seoul National University College of Medicine Seongnam Republic of Korea

8. Department of Neurology Korea University Guro Hospital Seoul Republic of Korea

9. Mila—Quebec Artificial Intelligence Institute Montreal Canada

10. Image Sciences Institute University Medical Center Utrecht Utrecht The Netherlands

Abstract

AbstractStudies in patients with brain lesions play a fundamental role in unraveling the brain's functional anatomy. Lesion‐symptom mapping (LSM) techniques can relate lesion location to cognitive performance. However, a limitation of current LSM approaches is that they can only evaluate one cognitive outcome at a time, without considering interdependencies between different cognitive tests. To overcome this challenge, we implemented canonical correlation analysis (CCA) as combined multivariable and multioutcome LSM approach. We performed a proof‐of‐concept study on 1075 patients with acute ischemic stroke to explore whether addition of CCA to a multivariable single‐outcome LSM approach (support vector regression) could identify infarct locations associated with deficits in three well‐defined verbal memory functions (encoding, consolidation, retrieval) based on four verbal memory subscores derived from the Seoul Verbal Learning Test (immediate recall, delayed recall, recognition, learning ability). We evaluated whether CCA could extract cognitive score patterns that matched prior knowledge of these verbal memory functions, and if these patterns could be linked to more specific infarct locations than through single‐outcome LSM alone. Two of the canonical modes identified with CCA showed distinct cognitive patterns that matched prior knowledge on encoding and consolidation. In addition, CCA revealed that each canonical mode was linked to a distinct infarct pattern, while with multivariable single‐outcome LSM individual verbal memory subscores were associated with largely overlapping patterns. In conclusion, our findings demonstrate that CCA can complement single‐outcome LSM techniques to help disentangle cognitive functions and their neuroanatomical correlates.

Funder

ZonMw

Fondation Brain Canada

Health Canada

Publisher

Wiley

Subject

Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

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