Adaptive Compensatory Neurophysiological Biomarkers of Motor Recovery Post-Stroke: Electroencephalography and Transcranial Magnetic Stimulation Insights from the DEFINE Cohort Study
2024

Neurophysiological Biomarkers for Motor Recovery After Stroke

Sample size: 102 publication 10 minutes Evidence: moderate

Author Information

Author(s): Lacerda Guilherme J. M., Silva Fernanda M. Q., Pacheco-Barrios Kevin, Battistella Linamara Rizzo, Fregni Felipe

Primary Institution: Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School

Hypothesis

A decreased EEG-TAR will be related to better functional improvement in stroke patients.

Conclusion

The study found that a lower baseline theta/alpha ratio (TAR) in the lesioned hemisphere is associated with better motor function recovery post-stroke.

Supporting Evidence

  • A higher baseline TAR in the lesioned hemisphere was associated with poorer motor outcomes.
  • An increase in TAR post-intervention was linked to better motor function improvements.
  • Neurophysiological measures like TAR and TMS metrics can guide personalized rehabilitation strategies.

Takeaway

This study looked at how brain activity can help predict how well stroke patients will recover their ability to move their arms. It found that certain brain measurements can show if a patient is likely to get better.

Methodology

This longitudinal cohort study analyzed neurophysiological, clinical, and demographic data from 102 stroke patients, focusing on EEG and TMS metrics.

Potential Biases

The study did not report specific risks of bias.

Limitations

The relatively small sample size may have impacted the statistical power, and the study was conducted in a single center, which may affect the generalizability of the findings.

Participant Demographics

Mean age of 56 years, 57% male, mostly white, with 81% having ischemic strokes.

Statistical Information

P-Value

0.04

Confidence Interval

0.04–0.82

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3390/brainsci14121257

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