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

Nick A. Weaver*, Muhammad Hasnain Mamdani, Jae Sung Lim, Johannes Matthijs Biesbroek, Geert Jan Biessels, Irene M.C. Huenges Wajer, Yeonwook Kang, Beom Joon Kim, Byung Chul Lee, Keon Joo Lee, Kyung Ho Yu, Hee Joon Bae, Danilo Bzdok, Hugo J. Kuijf

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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.

Original languageEnglish
Pages (from-to)2266-2278
Number of pages13
JournalHuman Brain Mapping
Volume44
Issue number6
DOIs
Publication statusPublished - 15 Apr 2023

Keywords

  • canonical correlation analysis
  • cognitive impairment
  • ischemic stroke
  • lesion location
  • lesion-symptom mapping
  • pattern-learning algorithms
  • support vector regression
  • verbal memory

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