ArticleJournal of neural engineering2020
Causal relationship between neuronal activity and cerebral hemodynamics in patients with ischemic stroke.
Article in Journal of neural engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Contralateral Neurovascular Coupling in Patients with Ischemic Stroke After Endovascular Thrombectomy.Neurocritical care · 2025Article
- Review
- Local Neuronal Activity and the Hippocampal Functional Network Can Predict the Recovery of Consciousness in Individuals With Acute Disorders of Consciousness Caused by Neurological Injury.CNS neuroscience & therapeutics · 2024Article
- Age-dependent neurovascular coupling characteristics in children and adults during general anesthesia.Biomedical optics express · 2023Article
- Multimodal and autoregulation monitoring in the neurointensive care unit.Frontiers in neurology · 2023Review
- Cerebral Autoregulation and Neurovascular Coupling in Acute and Chronic Stroke.Frontiers in neurology · 2021Article
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Authors and funding
8 authors.
Funding
Abstract
objectiveNeurovascular coupling enables rapid adaptation of cerebral blood flow (CBF) to support neuronal activity. Modern techniques enable the simultaneous recording of neuronal activities and hemodynamic parameters. However, the causal relationship between electrical brain activity and CBF is still unclarified. In this study, we investigated the causal relationship between surface electroencephalogram (EEG) and cerebral blood flow velocity (FV) from transcranial Doppler using Granger causality (GC) analysis. APPROACH: Twenty simultaneous recordings of EEG and FV from 17 acute ischemic stroke patients were studied. Each patient had simultaneous, continuous monitoring of EEG and bilateral FVs in either the middle cerebral arteries or posterior cerebral arteries. The causal interactions between FV (0.006-0.4 Hz) and EEG (delta, theta, alpha, beta and gamma bands) were investigated through GC index (GCI). In order to make the GCIs comparable, the proportion of GCI (PGCI) values where G-causality is statistically significant were calculated. Scores on the NIH Stroke Scale (NIHSS) and the modified Rankin Scale (mRS) for neurologic disability were recorded respectively at discharge. Patients were divided into a deceased (mRS = 6) and a survival group (mRS = 1 to 5), and a favorable (mRS: 1 to 2) and unfavorable outcome group (mRS: 3 ~ 6). MAIN
resultsThis study identified a causal relationship from EEG→FV, indicating EEG contained information that can be used for FV prediction. PGCI was negatively related with mRS (p < 0.05), indicating that stronger causalities between EEG and FV exist in patients with better outcome. The NIHSS was negatively related with the asymmetry of the two-side PGCI, calculated as the difference between the lesional side and non-lesional side PGCI. SIGNIFICANCE: A causal relationship from EEG→FV may exist in patients with ischemic stroke. The strength of G-causality may be related to stroke severity at discharge.
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