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Generative lesion pattern decomposition of cognitive impairment after stroke
Anna K Bonkhoff1, Jae-Sung Lim2, Hee-Joon Bae3
1Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, MA, Boston, USA.
Brain Communications
|June 30, 2021
Summary
Stroke can cause cognitive impairment, but how brain hemispheres interact to cause deficits is unclear. This study reveals distinct roles for the left and right hemispheres in specific cognitive functions after stroke.
Area of Science:
- Neuroscience
- Neurology
- Cognitive Science
Background:
- Cognitive impairment is a common and debilitating consequence of stroke.
- The precise mechanisms by which left and right cerebral hemisphere lesions interact to produce specific cognitive deficits remain incompletely understood.
Purpose of the Study:
- To investigate the distinct roles of left and right hemisphere lesion topographies in predicting cognitive impairments following acute ischemic stroke.
- To elucidate the relationship between specific brain regions, hemispheric lateralization, and patterns of cognitive dysfunction post-stroke.
Main Methods:
- Integrated machine learning and Bayesian hierarchical modeling for a hemisphere-aware analysis.
- Analyzed data from 1080 acute ischemic stroke patients with comprehensive cognitive assessments at approximately 3 months post-stroke.
Main Results:
- The left hemisphere was significantly relevant for predicting language and memory deficits.
- The right hemisphere was predominantly associated with visuospatial functioning impairments.
- Global cognitive impairments were predictable by lesion topographies from both hemispheres.
- Specific regions like the left hippocampus and occipital cortex related to naming/memory, while the right hippocampus/occipital cortex linked to visuospatial deficits.
Conclusions:
- Hemispheric lateralization of lesion patterns uniquely characterizes cognitive capacity loss after ischemic brain damage.
- Understanding these hemispheric contributions is crucial for predicting and potentially mitigating stroke-related cognitive sequelae.
Keywords:
Bayesian hierarchical modellingclinical outcome predictionhemisphere-aware analysisischaemic strokemachine learningMore Related Videos
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