AUTHOR=Hernandez Christopher Ivan , Afek Natalia , Gawłowska Magda , Oświęcimka Paweł , Fafrowicz Magdalena , Slowik Agnieszka , Wnuk Marcin , Marona Monika , Nowak Klaudia , Zur-Wyrozumska Kamila , Amon Mary Jean , Hancock P. A. , Marek Tadeusz , Karwowski Waldemar 

TITLE=Impact of interferon-β and dimethyl fumarate on nonlinear dynamical characteristics of electroencephalogram signatures in patients with multiple sclerosis

JOURNAL=Frontiers in Neuroinformatics

VOLUME=Volume 19 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2025.1519391

DOI=10.3389/fninf.2025.1519391

ISSN=1662-5196

ABSTRACT=IntroductionMultiple sclerosis (MS) is an intricate neurological condition that affects many individuals worldwide, and there is a considerable amount of research into understanding the pathology and treatment development. Nonlinear analysis has been increasingly utilized in analyzing electroencephalography (EEG) signals from patients with various neurological disorders, including MS, and it has been proven to be an effective tool for comprehending the complex nature exhibited by the brain.MethodsThis study seeks to investigate the impact of Interferon-β (IFN-β) and dimethyl fumarate (DMF) on MS patients using sample entropy (SampEn) and Higuchi’s fractal dimension (HFD) on collected EEG signals. The data were collected at Jagiellonian University in Krakow, Poland. In this study, a total of 175 subjects were included across the groups: IFN-β (n = 39), DMF (n = 53), and healthy controls (n = 83).ResultsThe analysis indicated that each treatment group exhibited more complex EEG signals than the control group. SampEn had demonstrated significant sensitivity to the effects of each treatment compared to HFD, while HFD showed more sensitivity to changes over time, particularly in the DMF group.DiscussionThese findings enhance our understanding of the complex nature of MS, support treatment development, and demonstrate the effectiveness of nonlinear analysis methods.