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Multimodal Brain Network Analysis of Resting-State fNIRS Reveals Cortical Compensation and Integration Imbalance in Acute Stroke
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DOI：10.1002/jbio.70248.png)
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Abstract
En 中文
This study utilized resting-state functional near-infrared spectroscopy to investigate the alterations in brain functional networks resulting from acute stroke. By implementing a comprehensive multimodal analytical approach, we assessed functional connectivity, effective connectivity, and graph-theoretical topology in resting-state fNIRS data. A total of 26 patients with acute stroke and 18 age- and sex-matched healthy controls participated in the study. The findings indicated a significant increase in effective connectivity from the affected supplementary motor area and a decrease in nodal degree centrality in the affected premotor cortex. While the global small-world topology remained intact, no notable differences in functional connectivity were observed between the groups. Notably, effective connectivity and graph-theoretical metrics proved to be more sensitive than functional connectivity in identifying acute stroke pathology. These results suggest a cortical compensation mechanism characterized by enhanced effective connectivity, even in the presence of impaired nodal integration in motor-related regions during the acute phase.
Keywords:
acute ischemic stroke
brain networks
effective connectivity
functional connectivity
functional near-infrared spectroscopy (fNIRS)
graph theory
multimodal integration
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2.3
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133
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