期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 113, 期 30, 页码 E4367-E4376出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1521083113
关键词
stroke; functional connectivity; interhemispheric; memory; language
资金
- National Institute of Child Health and Human Development Health Award [5R01HD061117]
- National Institute of Neurologic Disorders and Stroke [P30 NS048056]
- National Institute of Health Medical Scientist Training Award [5T32GM007200-39]
- American Heart Association Predoctoral Fellowship Award [14PRE19610010]
Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke.
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