Role of EEG-Based Biomarkers in Stroke Rehabilitation and Recovery

Since they don't say what specific treatment approach is needed for recovery this is useless.  The mentors and senior researchers in this need to be retrained in the whole point of stroke research. 100% RECOVERY! Not biomarkers.

Role of EEG-Based Biomarkers in Stroke Rehabilitation and Recovery 

Electroencephalography (EEG)-based biomarkers, especially low-frequency oscillations (LFOs), may assist in identifying patients that may benefit from a specific treatment approach compared to another, according to study results published in Stroke.
As EEG captures electrical potentials from underlying neural tissue, EEG measures may serve as potential biomarkers of brain function. Previously, the researchers focused on 2 frequency bands of interest: (1) LFOs in the delta frequency band (1-3 Hz) that are associated with brain injury and also reflect biological phenomena important to brain function; (2) high-beta frequency band (beta2, 20-30 Hz), as beta2 activity decreases after stroke and reflects brain injury. In the current study, the researchers assessed the use of EEG measures as potential biomarkers of injury and motor recovery poststroke.
The study cohort included adults with confirmed ischemic stroke or intracerebral hemorrhage. All participants completed structural neuroimaging as well as a 3-minute awake, resting-state EEG recording and clinical testing. A subset of inpatients from a rehabilitation facility also underwent serial EEG recording and clinical assessments over time. The relationship between EEG measures overlying ipsilesional and contralesional primary motor cortex (iM1, cM1) had with injury and motor status was assessed, focusing on delta (1–3 Hz) and high-beta (20–30 Hz) bands.
The final cohort included 62 participants with stroke, including 18 patients with available serial EEG recording.

In the delta band, infarct volume was positively related to EEG power in leads overlying a large bilateral fronto-parietal area, and to coherence with iM1 in bilateral leads especially over contralesional frontoparietal areas. In the beta2 band, the direction of the relationship with power was reversed, being negatively correlated with infarct volume throughout leads overlying bilateral frontal regions.
To examine injury findings with respect to time post stroke, patients were divided into 2 groups: subacute (n=24), who were 12.6±6.4 days post stroke, and chronic (n=36), who were 19.5±24.6 months poststroke.
In the subacute group, there was a positive correlation between delta power in leads overlying bilateral motor cortices with the total infarct volume. Beta2 coherence with iM1 showed a positive correlation with infarct volume in scattered regions in the subacute group that was absent in the chronic group.
In the chronic phase, there was a positive association between injury and delta power in leads overlying M1 and involved widespread bilateral areas, particularly a large posterior ipsilesional area where higher delta power also correlated with better motor status. While in the subacute phase LFOs reflected stroke injury, in chronic stroke, posterior ipsilesional LFOs was not simply a marker of neural injury as higher delta power corresponded to better motor status.
A subgroup of 18 patients completed multiple EEG recordings during their inpatient stay at a rehabilitation facility. The data were compared to 22 controls (16 females, mean age 57.3 years) and confirmed the coherence findings from the cross-sectional study.

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At the time of admission, interhemispheric coherence between leads overlying iM1 and contralesional M1 was elevated (0.22±0.10), compared to 22 healthy controls (0.12±0.11, P =.0008). Of these 18 patients, 17 completed a 90-day follow-up, and delta iM1-cM1 coherence was comparable to controls. Decreases in interhemispheric coherence between iM1 and contralesional M1 correlated with better motor recovery.
The study had several limitations, according to the researchers, including the modest sample size in the serial data, obtaining EEG recording only at rest, and limitations secondary to not applying Laplacian transformations, source localization, and head modeling.
“The informative potential of electroencephalography, combined with its portability and accessibility, may offer clinicians an additional tool to incorporate in their practice to enhance patient prognostication, treatment allocation, and assessment of therapeutic response,” concluded the researchers.
Reference
Cassidy JM, Wodeyar A, Wu J, et al. Low-frequency oscillations are a biomarker of injury and recovery after stroke. Stroke. 2020;51(5):1442‐1450. doi:10.1161/STROKEAHA.120.028932