PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 17, 2026Psychological Medicine4 citationsOpen Access

EEG-based frontal excitation/inhibition balance as an objective biomarker for cognitive fatigue across multiple sclerosis and Long COVID

View Full Paper
SLStefanie LinnhoffRKRoi Cohen KadoshTZTino Zaehle

Key Points

  • This research aims to determine whether the frontal aperiodic exponent can serve as an objective biomarker for cognitive fatigue in multiple sclerosis and Long COVID.
  • Conducted a cross-sectional study with 119 participants including healthy controls and individuals with Long COVID or MS.
  • Analyzed resting-state EEG power spectrum to derive aperiodic exponents and assess fatigue ratings.
  • Used logistic mixed-effects regression models to evaluate classification accuracy for identifying fatigue status.
  • Lower frontal aperiodic exponents were associated with higher cognitive fatigue among all participants.
  • Fatigued individuals had reduced frontal exponent values compared to nonfatigued groups.
  • Logistic regression analysis showed that frontal exponent values significantly predicted fatigue status with good sensitivity and specificity.

Abstract

Abstract Background Cognitive fatigue is a prevalent and disabling symptom in neurological and post-viral conditions, including multiple sclerosis (MS) and Long COVID. Assessment relies largely on self-report, and no validated objective biomarker exists, limiting reliable diagnosis and treatment monitoring. The aperiodic exponent of the Electroencephalogram (EEG) power spectrum, reflecting the excitation/inhibition (E/I) balance, is a promising candidate biomarker. We examined whether aperiodic exponent values can objectively identify pathological fatigue and assessed their classification accuracy. Methods We conducted a cross-sectional study, including 119 participants: 36 healthy controls, 33 with Long COVID-related fatigue (LCOF), and 50 with MS (23 fatigued and 27 nonfatigued). Resting-state EEGs were analyzed, and associations with fatigue ratings and group differences were assessed. Logistic mixed-effects regression models evaluated classification accuracy for fatigue status. Results Lower frontal aperiodic exponents were associated with higher cognitive fatigue across participants. Fatigued individuals, regardless of diagnosis, showed reduced frontal exponent values compared with nonfatigued groups, while no differences emerged in occipital regions. Logistic regression confirmed that frontal exponent values significantly predicted fatigue status, improving classification accuracy beyond age and depression, with good sensitivity and specificity. Conclusions The frontal aperiodic exponent is a regionally specific biomarker of cognitive fatigue across MS and LCOF. Mechanistic interpretation suggests an altered prefrontal E/I balance, which could inform the development of targeted interventions to alleviate cognitive fatigue. It offers a clinically accessible tool to complement self-report, support trial stratification, and enable objective treatment monitoring. Importantly, its presence across distinct disorders highlights its value as a transdiagnostic marker of fatigue.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Linnhoff et al. (2026) studied this question.

synapsesocial.com/papers/696b25a9d2a12237a93490bdhttps://doi.org/10.1017/s0033291725103024
Ask AI
Helpful
Bookmark
Share
View Full Paper