Brain Network Connectivity During Resting-State and a Visuospatial Task as a Biomarker for Spatial Neglect in Stroke Patients.
Golnaz Haddadshargh, Richard Gall, Emily S Grattan and 3 others
PMID 41773346WHAT IT FOUND
EEG connectivity patterns, especially beta-band centrality changes in frontal and parietal regions, distinguished stroke patients with spatial neglect from those without in this small cross-sectional study.
These findings suggest potential biomarkers for neglect but do not yet support clinical diagnosis or treatment decisions.
Key findings
01Resting-state EEG connectivity analysis using Gradient Boosting achieved 87.0% accuracy and 94.9% sensitivity in distinguishing stroke patients with spatial neglect from those without, with an AUC of 0.90.
02Patients with neglect showed decreased beta-band closeness centrality in right frontal and right parieto-occipital electrodes, and increased eigenvector centrality in central regions compared to those without neglect.
03Task-based EEG analysis showed no significant difference in classification performance between contralesional and ipsilesional conditions, leading to combined analysis with 80.9% accuracy using LDA.
STILL TO COME
How it was doneWhat they found
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What it does not show
Small sample size (16-23 participants analyzed) limits generalizability and statistical power. Cross-sectional design prevents assessment of how connectivity changes over time or with recovery. High variability in lesion laterality and time since stroke in the non-neglect group may confound results. 16-channel EEG has limited spatial resolution, preventing source localization and potentially missing subtle connectivity patterns. Task design was low-demand to accommodate acute/subacute patients, possibly reducing sensitivity to lateralized differences. No behavioral responses were collected during the task-based EEG, limiting correlation with functional performance.
Declared interests
The authors declared no potential conflicts of interest. The study was supported by NIH grants and conducted at the University of Pittsburgh.
The easy way to misread this
Do not use these EEG connectivity patterns for clinical diagnosis or treatment planning. The study had a very small sample, used a novel research system, and has not been validated in independent cohorts. These findings are exploratory biomarkers that require further replication and validation before any clinical application.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →