A systematic review of quantitative EEG findings in Fibromyalgia, Chronic Fatigue Syndrome and Long COVID.
Silva-Passadouro, Bárbara, Tamasauskas, Arnas, Khoja, Omar et al. · Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024 · DOI
Quick Summary
This study reviewed research on brain wave patterns in three related conditions: fibromyalgia, ME/CFS, and Long COVID. Researchers found that ME/CFS and fibromyalgia show different patterns of brain activity when measured using EEG, a test that records electrical activity in the brain. The study suggests these conditions may involve different changes in how the brain functions, which could eventually help doctors identify and treat each condition more specifically.
Why It Matters
Understanding the brain's electrical activity patterns in ME/CFS could lead to objective diagnostic tools and personalized treatments. This review suggests that ME/CFS has a distinct neurophysiological signature different from similar conditions, supporting the biological basis of the illness and potentially validating patients' experiences of neurological dysfunction.
Observed Findings
Fibromyalgia showed decreased low-frequency EEG activity (delta, theta, alpha bands) and increased high-frequency beta activity compared to controls.
ME/CFS demonstrated different qEEG patterns than fibromyalgia, suggesting distinct neurophysiological mechanisms.
Long COVID studies produced mixed and inconsistent findings, particularly regarding cognitive impairment measures.
All 17 included studies scored moderate to high quality on the Newcastle-Ottawa quality assessment scale.
Only 17 studies met rigorous selection criteria from an initial pool of 2,510 identified articles.
Inferred Conclusions
ME/CFS and fibromyalgia have distinct patterns of brain wave activity, suggesting these are different neurobiological conditions despite symptom overlap.
EEG signatures may eventually serve as objective diagnostic markers and guide targeted neuromodulation therapies for each condition.
Long COVID may represent a heterogeneous condition with different subtypes that align with either FMS or ME/CFS neurophysiological patterns.
Further standardized research is needed to establish EEG biomarkers and understand the neuropathophysiology underlying these syndromes.
Remaining Questions
Do EEG patterns in ME/CFS patients correlate with specific symptom clusters or disease severity, and can they predict treatment response?
What This Study Does Not Prove
This review does not establish that EEG changes cause ME/CFS symptoms or definitively prove these biomarkers can be used clinically for diagnosis. The findings show correlation between EEG patterns and disease states, not causation, and the limited Long COVID data means conclusions about that condition remain preliminary. Individual variation within each condition may be substantial, so group-level findings may not apply to all patients.