Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

Pilar Garcés (1) , Sarah Baumeister (2, 3) , Luke Mason (4) , Christopher Chatham (1) , Stefan Holiga (1) , Juergen Dukart (5) , Emily Jones (4) , Tobias Banaschewski (3, 2) , Simon Baron-Cohen (6) , Sven Bölte (7, 8) , Jan Buitelaar (9) , Sarah Durston (10) , Bob Oranje (10) , Antonio Persico (11) , Christian Beckmann (9) , Thomas Bougeron (12) , Flavio Dell’acqua (13) , Christine Ecker (14) , Carolin Moessnang (15) , Tony Charman , Julian Tillmann , Declan Murphy , Mark Johnson , Eva Loth (13) , Daniel Brandeis , Joerg Hipp , Jumana Ahmad , Sara Ambrosino , Bonnie Auyeung , Tobias Banaschewski , Simon Baron-Cohen , Sarah Baumeister , Christian Beckmann , Sven Bölte , Thomas Bourgeron (12) , Carsten Bours , Michael Brammer , Daniel Brandeis , Claudia Brogna , Yvette de Bruijn , Jan Buitelaar , Bhismadev Chakrabarti , Tony Charman , Ineke Cornelissen , Daisy Crawley , Flavio Dell’acqua , Guillaume Dumas , Sarah Durston , Christine Ecker , Jessica Faulkner , Vincent Frouin , Pilar Garcés , David Goyard , Lindsay Ham , Hannah Hayward , Joerg Hipp , Rosemary Holt , Mark Johnson , Emily Jones , Prantik Kundu , Meng-Chuan Lai , Xavier Liogier D’ Ardhuy , Michael Lombardo , Eva Loth , David Lythgoe , René Mandl , Andre Marquand , Luke Mason , Maarten Mennes , Andreas Meyer-Lindenberg , Carolin Moessnang , Nico Mueller , Declan Murphy , Bethany Oakley , Laurence O’dwyer , Marianne Oldehinkel , Bob Oranje , Gahan Pandina , Antonio Persico , Barbara Ruggeri , Amber Ruigrok , Jessica Sabet , Roberto Sacco , Antonia San José Cáceres , Emily Simonoff , Will Spooren , Julian Tillmann , Roberto Toro , Heike Tost , Jack Waldman , Steve Williams , Caroline Wooldridge , Marcel Zwiers , The Eu-Aims Leap Group

1 Roche Innovation Center [Basel, Switzerland]
2 Heidelberg University
3 Medical Faculty [Mannheim]
4 University of London [London]
5 INM-7 - Institute of Neuroscience and Medicine, Brain and Behaviour [Jülich, Germany]
6 Autism Research Centre [Cambridge, Royaume-Uni]
7 Centre for Psychiatry Research [Stockholm]
8 Curtin University [Perth]
9 Donders Institute for Brain, Cognition and Behaviour
10 University Medical Center [Utrecht]
11 UniMe - Università degli Studi di Messina = University of Messina
12 GHFC (UMR_3571 / U-Pasteur_1) - Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions
13 King‘s College London
14 Goethe-University Frankfurt am Main
15 Central Institute of Mental Health [Mannheim]

Abstract Background Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. Methods We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2–32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults ( n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants’ MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%–30% split). Results In the training dataset, we found an interaction between age and group for the reactivity to eye opening ( p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52–0.62, specificity 0.59–0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. Limitations The statistical power to detect weak effects—of the magnitude of those found in the training dataset—in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset’s effects. Conclusions This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

Keywords: Autism spectrum disorder; EEG; Functional connectivity; Power spectrum; Resting state

Domains: Neurons and Cognition [q-bio.NC]

Pilar Garcés, Sarah Baumeister, Luke Mason, Christopher Chatham, Stefan Holiga, et al.. Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis. Molecular Autism, 2022, 13 (1), pp.22. ⟨10.1186/s13229-022-00500-x⟩. ⟨pasteur-04072081⟩