AUTHOR=Proteau-Lemieux Mélodie , Knoth Inga Sophia , Agbogba Kristian , Côté Valérie , Barlahan Biag Hazel Maridith , Thurman Angela John , Martin Charles-Olivier , Bélanger Anne-Marie , Rosenfelt Cory , Tassone Flora , Abbeduto Leonard J. , Jacquemont Sébastien , Hagerman Randi , Bolduc François , Hessl David , Schneider Andrea , Lippé Sarah 

TITLE=EEG Signal Complexity Is Reduced During Resting-State in Fragile X Syndrome

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.716707

DOI=10.3389/fpsyt.2021.716707

ISSN=1664-0640

ABSTRACT=Introduction: Fragile X syndrome (FXS) is a genetic disorder caused by a mutation of the fragile X mental retardation 1 gene (FMR1). FXS is associated with neurophysiological abnormalities, including cortical hyperexcitability. Alterations in electroencephalogram (EEG) resting-state power spectral density (PSD) are well defined in FXS and were found to be linked to neurodevelopmental delays. Whether non-linear dynamics of brain signal are also altered remains to be studied. Methods: In this study, resting-state EEG power, including alpha peak frequency (APF) and theta/beta ratio (TBR), as well as signal complexity using multi-scale entropy (MSE) were compared between 26 FXS participants (ages 5-28 years), and 78 neurotypical (NT) controls with a similar age distribution. Subsequently a replication study was carried out, comparing our cohort to 19 FXS participants independently recorded at a different site, using a different EEG system. Results: PSD results showed the known FXS EEG pattern, such as increased gamma and decreased alpha power and APF in FXS participants, compared to NT controls. No alterations in TBR were found. Importantly, results also revealed reduced signal complexity in FXS participants, specifically in higher scales, suggesting that altered signal complexity is sensitive to brain alterations in this population. The replication study mostly confirmed these results and suggested critical points of stagnation in the neurodevelopmental curve of FXS. Conclusion: Signal complexity is a powerful feature that can be added to the electrophysiological biomarkers of brain maturation in FXS.