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

• Published in: Human brain mapping Vol. 44; no. 6; pp. 2266 - 2278
• Main Authors: Weaver, Nick A., Mamdani, Muhammad Hasnain, Lim, Jae‐Sung, Biesbroek, Johannes Matthijs, Biessels, Geert Jan, Huenges Wajer, Irene M. C., Kang, Yeonwook, Kim, Beom Joon, Lee, Byung‐Chul, Lee, Keon‐Joo, Yu, Kyung‐Ho, Bae, Hee‐Joon, Bzdok, Danilo, Kuijf, Hugo J.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 15.04.2023
• Subjects: Anatomy; Brain; Brain architecture; Brain mapping; Brain Mapping - methods; canonical correlation analysis; Cognition; Cognition Disorders - complications; Cognitive ability; cognitive impairment; Consolidation; Correlation analysis; Functional anatomy; Humans; Infarction - complications; Ischemia; ischemic stroke; Ischemic Stroke - complications; Learning; lesion location; Lesions; lesion‐symptom mapping; Magnetic resonance imaging; Mapping; Memory; Neuropsychological Tests; Neuropsychology; Patients; pattern‐learning algorithms; Recall; Registration; Stroke; Stroke - complications; Stroke - diagnostic imaging; Stroke - pathology; Support vector machines; support vector regression; Verbal learning; verbal memory; support vector regression; verbal memory; lesion location; lesion-symptom mapping; cognitive impairment; canonical correlation analysis; pattern-learning algorithms; ischemic stroke
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.26208

Studies 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.