Multiple sclerosis and related disorders · 2026
EEG functional connectivity as a neurophysiological biomarker of cognitive function in relapsing remitting multiple sclerosis patients.
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Elkholy Mostafa M, Hosny Hanan, Hussein Mona, Bayoumi Hiam M
Аннотация
OBJECTIVE: Multiple Sclerosis (MS) is a common neuroinflammatory disorder in young adults. Disrupted neural connectivity due to demyelination and axonal degeneration contributes to cognitive impairment. The aim is to examine EEG functional connectivity (coherence and phase lag) in relapsing-remitting MS (RRMS) and explore its correlation with cognitive function.
METHODS: Thirty-five RRMS patients and 35 age- and sex-matched healthy controls (HC) were included. Neurological (Expanded Disability Status Scale), MRI, and cognitive (Paced Auditory Serial Addition Test) assessment were conducted, in addition to neurophysiological evaluation using quantitative EEG (coherence and phase lag) and P300 response.
RESULTS: RRMS patients showed lower PASAT scores (30.2 ± 10 RRMS, 36.8 ± 9.6 HC (P = 0.024)) and significant disruption in resting-state EEG functional connectivity; lower coherence of alpha at inter-temporal (P = 0.001), inter-parietal (P = 0.005), and inter-temporal beta (P = 0.001). Phase lag of beta band was higher in patients at the left frontal-temporal (P = 0.002), left frontal-parietal (P = 0.007) and inter-temporal (P = 0.01) levels. This disruption correlated with disease severity markers. Phase lag alterations were linked to cognitive performance. (PASAT correlated with: left frontal-temporal beta phase lag (r = -0.626, P ≤ 0.001) and global theta phase lag (r = -0.398, P = 0.02) CONCLUSION: EEG functional connectivity measures provide valuable insights into cognitive impairment in RRMS. These findings are preliminary and require independent validation in future studies.
SIGNIFICANCE: Understanding the cognitive-connectivity inter-relation may help to tailor treatment and rehabilitation plans.
METHODS: Thirty-five RRMS patients and 35 age- and sex-matched healthy controls (HC) were included. Neurological (Expanded Disability Status Scale), MRI, and cognitive (Paced Auditory Serial Addition Test) assessment were conducted, in addition to neurophysiological evaluation using quantitative EEG (coherence and phase lag) and P300 response.
RESULTS: RRMS patients showed lower PASAT scores (30.2 ± 10 RRMS, 36.8 ± 9.6 HC (P = 0.024)) and significant disruption in resting-state EEG functional connectivity; lower coherence of alpha at inter-temporal (P = 0.001), inter-parietal (P = 0.005), and inter-temporal beta (P = 0.001). Phase lag of beta band was higher in patients at the left frontal-temporal (P = 0.002), left frontal-parietal (P = 0.007) and inter-temporal (P = 0.01) levels. This disruption correlated with disease severity markers. Phase lag alterations were linked to cognitive performance. (PASAT correlated with: left frontal-temporal beta phase lag (r = -0.626, P ≤ 0.001) and global theta phase lag (r = -0.398, P = 0.02) CONCLUSION: EEG functional connectivity measures provide valuable insights into cognitive impairment in RRMS. These findings are preliminary and require independent validation in future studies.
SIGNIFICANCE: Understanding the cognitive-connectivity inter-relation may help to tailor treatment and rehabilitation plans.