Causal relationship between neuronal activity and cerebral hemodynamics in patients with ischemic stroke.

Journal Article (Journal Article)

Objective

Neurovascular 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 results

This 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.

Full Text

Duke Authors

Cited Authors

  • Wu, D; Liu, X; Gadhoumi, K; Pu, Y; Hemphill, JC; Zhang, Z; Liu, L; Hu, X

Published Date

  • March 19, 2020

Published In

Volume / Issue

  • 17 / 2

Start / End Page

  • 026006 -

PubMed ID

  • 32050174

Pubmed Central ID

  • PMC7958312

Electronic International Standard Serial Number (EISSN)

  • 1741-2552

International Standard Serial Number (ISSN)

  • 1741-2560

Digital Object Identifier (DOI)

  • 10.1088/1741-2552/ab75af

Language

  • eng