EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study

Area of Science:

• Neuroscience
• Medical Imaging
• Biomarkers

Background:

• Stroke is a leading cause of death and disability worldwide.
• Cognitive impairment post-stroke requires accurate evaluation and detection.
• Identifying reliable biomarkers for cognitive assessment is a critical research area.

Purpose of the Study:

• To explore electroencephalography (EEG) as a neuroimaging tool for evaluating cognitive impairment after stroke.
• To identify specific EEG biomarkers associated with different levels of cognitive impairment post-stroke.
• To differentiate between healthy controls and stroke patients with mild, moderate, and severe cognitive impairment using EEG.

Main Methods:

• Utilized power density spectrum (PSD) and functional connectivity mapping to analyze EEG data.
• Employed one-way ANOVA to assess differences in EEG biomarkers across cognitive impairment groups.
• Included 32 participants: 8 healthy controls and 24 stroke patients across mild, moderate, and severe cognitive impairment levels.

Main Results:

• Significant PSD differences were observed between healthy controls and all cognitive impairment groups.
• Severe cognitive impairment showed superior theta and alpha band PSD in the right frontal cortex.
• Mild and moderate cognitive impairment groups exhibited distinct PSD patterns in theta, beta, and gamma bands across frontal and parietal regions.
• The severe cognitive impairment group displayed stronger functional connectivity compared to other groups.

Conclusions:

• EEG biomarkers demonstrate potential for classifying cognitive impairment levels in stroke patients.
• These findings offer a novel approach for early detection and diagnosis of post-stroke cognitive impairment.
• The identified EEG biomarkers may aid in developing targeted treatment strategies for stroke recovery.