Deans' stroke musings: Biomarkers of stroke recovery using EEG-based resting-state functional connectivity: a systematic review

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Thursday, March 19, 2026

Biomarkers of stroke recovery using EEG-based resting-state functional connectivity: a systematic review

Prognistication and biomarkers DO NOTHING FOR SURVIVOR RECOVERY! Are you really that blitheringly stupid? Can you even get dressed in the morning? Where are the EXACT PROTOCOLS THAT DELIVER RECOVERY?

Biomarkers of stroke recovery using EEG-based resting-state functional connectivity: a systematic review

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

EEG-based resting-state functional connectivity (FC) has been widely explored as a prognostic tool in stroke recovery, offering a cost-effective alternative to fMRI. However, it remains unclear whether FC measures are reliable biomarkers for predicting stroke recovery. This systematic review provides a comprehensive overview of existing EEG-based FC measures and their clinical relevance in stroke recovery. Specifically, this study aims to identify the most reliable and predictive FC measures of recovery by examining their relationship with longitudinal changes, clinical outcomes, and neurorehabilitation protocols. Results show that while some studies report associations between FC and recovery, no consistent patterns emerge. Significant methodological heterogeneity, such as differences in sensor- vs. source-level analysis, study design, connectivity measures, and reliance on correlational rather than predictive approach, limits the interpretability and comparability of results. Overall, these inconsistencies raise concerns about the reliability of EEG-based FC measures as biomarkers of stroke recovery. Moreover, while most studies focused on motor recovery, emerging evidence suggests FC may also help predict cognitive recovery. Future research should prioritize predictive models tailored to clinical needs, explore multidimensional recovery domains, and establish standardized protocols to enhance methodological consistency. By addressing these challenges and harnessing advanced computational techniques, EEG-based FC holds the potential to transform personalized rehabilitation strategies and optimize outcomes for stroke patients. Given the wide range of analytical scenarios and the absence of a superior method, we propose that a “multiverse” analytical approach could offer valuable insights into the most promising pathways for establishing connectivity as a potential biomarker for stroke recovery.