A2 Refereed review article in a scientific journal
The use of event-related potentials in the investigation of cognitive performance in people with Multiple Sclerosis : Systematic review
Authors: Vlieger Robin, Austin Duncan, Apthorp Deborah, Daskalaki Elena, Lenskiy Artem, Walton-Sonda Dianne, Suominen Hanna, Lueck Christian J.
Publisher: Elsevier
Publication year: 2024
Journal: Brain Research
Journal name in source: Brain Research
Article number: 148827
Volume: 1832
ISSN: 0006-8993
DOI: https://doi.org/10.1016/j.brainres.2024.148827
Web address : https://doi.org/10.1016/j.brainres.2024.148827
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/387109414
A biomarker of cognition in Multiple Sclerosis (MS) that is independent from the response of people with MS (PwMS) to test questions would provide a more holistic assessment of cognitive decline. One suggested method involves event-related potentials (ERPs). This systematic review tried to answer five questions about the use of ERPs in distinguishing PwMS from controls: which stimulus modality, which experimental paradigm, which electrodes, and which ERP components are most discriminatory, and whether amplitude or latency is a better measure. Our results show larger pooled effect sizes for visual stimuli than auditory stimuli, and larger pooled effect sizes for latency measurements than amplitude measurements. We observed great heterogeneity in methods and suggest that future research would benefit from more uniformity in methods and that results should be reported for the individual subtypes of PwMS. With more standardised methods, ERPs have the potential to be developed into a clinical tool in MS.
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Funding information in the publication:
This research was funded by and has been delivered in partnership with Our Health in Our Hands (OHIOH), a strategic initiative of the Australian National University, which aims to transform health care by developing new personalised health technologies and solutions in collaboration with patients, clinicians, and health-care providers. We gratefully acknowledge the funding from the ANU School of Computing for the first author’s PhD studies.
