The Transformation of Dynamic Network State in Ischemic Stroke - Li, Moxin (International Journal of Computer Science and Information Technology, 2024)
Ischemic stroke is a common disease of the nervous system, which poses a serious threat to human health due to its high disability rate and mortality rate, among which ischemic stroke occupies the first place. According to the Chinese National Stroke Registry Study, the crude and standardized prevalence of stroke in people over 40 years of age is 2.0% and 1.9% [1]. Because of its high disability rate and mortality, it is very important to accurately evaluate the disease condition and prognosis in the early stage of the disease. There are many methods to judge the severity of stroke patients, and the most widely used ones are clinical scale and imaging examination. In order to detect the onset of ischemic stroke early, it is important to identify specific electroencephalogram (EEG) dynamics and resting state fMRI for the transformation of brain activity during the onset of ischemic stroke. In this study, we investigated the transition of brain activity from interseizure to preseizure states, combining EEG networks at different frequency bands and cluster analysis combined with resting state fMRI to consider changes in patients’ brain networks. These findings may provide useful insights into the pathogenesis of ischemic stroke and can also be used for prediction and subsequent intervention of ischemic stroke onset.