1. Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis
- Author
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Garcés, Pilar, Baumeister, Sarah, Mason, Luke, Chatham, Christopher, Holiga, Stefan, Dukart, Juergen, Jones, Emily, Banaschewski, Tobias, Baron-Cohen, Simon, Bölte, Sven, Buitelaar, Jan, Durston, Sarah, Oranje, Bob, Persico, Antonio, Beckmann, Christian, Bougeron, Thomas, Dell’acqua, Flavio, Ecker, Christine, Moessnang, Carolin, Charman, Tony, Tillmann, Julian, Murphy, Declan, Johnson, Mark, Loth, Eva, Brandeis, Daniel, Hipp, Joerg, Ahmad, Jumana, Ambrosino, Sara, Auyeung, Bonnie, Bourgeron, Thomas, Bours, Carsten, Brammer, Michael, Brogna, Claudia, de Bruijn, Yvette, Chakrabarti, Bhismadev, Cornelissen, Ineke, Crawley, Daisy, Dumas, Guillaume, Faulkner, Jessica, Frouin, Vincent, Goyard, David, Ham, Lindsay, Hayward, Hannah, Holt, Rosemary, Kundu, Prantik, Lai, Meng-Chuan, Ardhuy, Xavier Liogier D’, Lombardo, Michael, Lythgoe, David, Mandl, René, Marquand, Andre, Mennes, Maarten, Meyer-Lindenberg, Andreas, Mueller, Nico, Oakley, Bethany, O’dwyer, Laurence, Oldehinkel, Marianne, Pandina, Gahan, Ruggeri, Barbara, Ruigrok, Amber, Sabet, Jessica, Sacco, Roberto, Cáceres, Antonia San José, Simonoff, Emily, Spooren, Will, Toro, Roberto, Tost, Heike, Waldman, Jack, Williams, Steve, Wooldridge, Caroline, Zwiers, Marcel, Leap Group, The Eu-Aims, Garcés, Pilar [0000-0003-4989-0123], Apollo - University of Cambridge Repository, Roche Innovation Center [Basel, Switzerland], Heidelberg University, University Hospital Mannheim | Universitätsmedizin Mannheim, University of London [London], Institute of Neuroscience and Medicine, Brain and Behaviour [Jülich, Germany] (INM-7), Jülich Research Centre, Autism Research Centre [Cambridge, Royaume-Uni], University of Cambridge [UK] (CAM), Centre for Psychiatry Research [Stockholm], Karolinska Institutet [Stockholm], Curtin University [Perth], Planning and Transport Research Centre (PATREC), Donders Institute for Brain, Cognition and Behaviour, Radboud University [Nijmegen], University Medical Center [Utrecht], Università degli Studi di Messina = University of Messina (UniMe), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), King‘s College London, Goethe-University Frankfurt am Main, Central Institute of Mental Health [Mannheim], This work was supported by EU-AIMS (European Autism Interventions), which receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115300, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (grant FP7/2007–2013), from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions and from Autism Speaks. AIMS-2-TRIALS is funded by the Innovative Medicines Initiative 2 Joint Undertaking (IMI 2 JU) under grant agreement no. 777394. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program, EFPIA, Autism Speaks, Autistica, and SFARI. PG was supported by the Roche Postdoctoral Fellowship (RPF) program., European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), European Project: 777394,H2020-JTI-IMI2-2016-10-two-stage,AIMS-2-TRIALS(2018), and University of Zurich
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Adult ,Adolescent ,Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13] ,Autism spectrum disorder ,EEG ,Resting state ,Power spectrum ,Functional connectivity ,610 Medicine & health ,1309 Developmental Biology ,2806 Developmental Neuroscience ,2738 Psychiatry and Mental Health ,Developmental Neuroscience ,130 000 Cognitive Neurology & Memory ,1312 Molecular Biology ,Humans ,ddc:610 ,10064 Neuroscience Center Zurich ,Autistic Disorder ,Child ,Molecular Biology ,Brain Mapping ,Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7] ,Research ,220 Statistical Imaging Neuroscience ,Brain ,Reproducibility of Results ,Electroencephalography ,10058 Department of Child and Adolescent Psychiatry ,Magnetic Resonance Imaging ,Psychiatry and Mental health ,Cross-Sectional Studies ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Developmental Biology - 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., Molecular Autism, 13
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- 2022