Evidence map›Paper›PMID 41536211›Full record

ArticlePsychological medicine2026

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

Stefanie Linnhoff, Roi Cohen Kadosh, Tino Zaehle

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Article in Psychological medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Stefanie LinnhoffDepartment of Neurology, Otto-von-Guericke University, Magdeburg, Germany.ORCID https://orcid.org/0000-0001-6241-2949
Roi Cohen KadoshSchool of Psychology, University of Surrey, Guildford, UK.
Tino ZaehleDepartment of Neurology, Otto-von-Guericke University, Magdeburg, Germany.ORCID https://orcid.org/0000-0003-3673-4869

Funding

Deutsche Forschungsgemeinschaft 539530253
6 · The paper itself

Abstract

backgroundCognitive 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.

methodsWe 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.

resultsLower 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.

conclusionsThe 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.

Indexed as

COVID-19ElectroencephalographyFatigueFrontal LobeMultiple SclerosisAdultBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedPost-Acute COVID-19 SyndromeBiomarkersaperiodic exponentEEG biomarkerexcitation/inhibition balancefatigueLong COVIDmultiple sclerosis

Identifiers

PMID41536211
PMCPMC12885349

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.