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@ARTICLE{Garcs:910711,
author = {Garcés, Pilar and Baumeister, Sarah and Mason, Luke and
Chatham, Christopher H. and Holiga, Stefan and Dukart,
Jürgen and Jones, Emily J. H. and Banaschewski, Tobias and
Baron-Cohen, Simon and Bölte, Sven and Buitelaar, Jan K.
and Durston, Sarah and Oranje, Bob and Persico, Antonio M.
and Beckmann, Christian F. and Bougeron, Thomas and
Dell’Acqua, Flavio and Ecker, Christine and Moessnang,
Carolin and Charman, Tony and Tillmann, Julian and Murphy,
Declan G. M. and Johnson, Mark and Loth, Eva and Brandeis,
Daniel and Hipp, Joerg F. and Ahmad, Jumana and Ambrosino,
Sara and Auyeung, Bonnie and Banaschewski, Tobias and
Baron-Cohen, Simon and Baumeister, Sarah and Beckmann,
Christian F. and Bölte, Sven and Bourgeron, Thomas and
Bours, Carsten and Brammer, Michael and Brandeis, Daniel and
Brogna, Claudia and de Bruijn, Yvette and Buitelaar, Jan K.
and Chakrabarti, Bhismadev and Charman, Tony and
Cornelissen, Ineke and Crawley, Daisy and Dell’Acqua,
Flavio and Dumas, Guillaume and Durston, Sarah and Ecker,
Christine and Faulkner, Jessica and Frouin, Vincent and
Garcés, Pilar and Goyard, David and Ham, Lindsay and
Hayward, Hannah and Hipp, Joerg and Holt, Rosemary and
Johnson, Mark H. and Jones, Emily J. H. and Kundu, Prantik
and Lai, Meng-Chuan and ardhuy, Xavier Liogier D’ and
Lombardo, Michael V. and Loth, Eva and Lythgoe, David J. and
Mandl, René and Marquand, Andre and Mason, Luke and Mennes,
Maarten and Meyer-Lindenberg, Andreas and Moessnang, Carolin
and Mueller, Nico and Murphy, Declan G. M. and Oakley,
Bethany and O’Dwyer, Laurence and Oldehinkel, Marianne and
Oranje, Bob and Pandina, Gahan and Persico, Antonio M. and
Ruggeri, Barbara and Ruigrok, Amber and Sabet, Jessica and
Sacco, Roberto and Cáceres, Antonia San José and Simonoff,
Emily and Spooren, Will and Tillmann, Julian and Toro,
Roberto and Tost, Heike and Waldman, Jack and Williams,
Steve C. R. and Wooldridge, Caroline and Zwiers, Marcel P.},
title = {{R}esting state {EEG} power spectrum and functional
connectivity in autism: a cross-sectional analysis},
journal = {Molecular autism},
volume = {13},
number = {1},
issn = {2040-2392},
address = {London},
publisher = {BioMed Central},
reportid = {FZJ-2022-04082},
pages = {22},
year = {2022},
abstract = {BackgroundUnderstanding 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.MethodsWe 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).ResultsIn 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.LimitationsThe
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.ConclusionsThis 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.},
cin = {INM-7},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5251 - Multilevel Brain Organization and Variability
(POF4-525)},
pid = {G:(DE-HGF)POF4-5251},
typ = {PUB:(DE-HGF)16},
pubmed = {35585637},
UT = {WOS:000797539700002},
doi = {10.1186/s13229-022-00500-x},
url = {https://juser.fz-juelich.de/record/910711},
}