Results of quantitative EEG analysis are associated with autism spectrum disorder and development abnormalities in infants with tuberous sclerosis complex

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064203%3A_____%2F21%3A10427628" target="_blank" >RIV/00064203:_____/21:10427628 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11130/21:10427628

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=.INfxLwjDH" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=.INfxLwjDH</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.bspc.2021.102658" target="_blank" >10.1016/j.bspc.2021.102658</a>

Result language

angličtina

Original language name

Results of quantitative EEG analysis are associated with autism spectrum disorder and development abnormalities in infants with tuberous sclerosis complex

Original language description

Objective: The aim of this study is the investigation of early-life EEG background abnormalities or &quot;dysmature&quot; traits in infants with tuberous sclerosis complex (TSC) and their capacity to predict autism spectrum disorder or neurodevelopmental outcome. Methods: EEG data were prospectively collected from TSC patients during the EPISTOP trial (NCT02098759). Subjects were younger than 4 months, and ASD risk and neurodevelopmental outcome were assessed at the age of 2 years. The EEG at the first visit was analyzed by means of Multiscale Entropy (MSE), multifractality (MFA), amplitude integrated EEG features and topological indices of the EEG network. These features were associated with both ASD and abnormal Bayley outcome of the infants using linear discriminant analysis. Results: The classification of the ASD patients shows that MFA and MSE had the best discrimination performances, with an area under the ROC curve AUC (MFA) = 0.74 and AUC(MSE) = 0.79 respectively, and kappa scores of Kappa(MFA) = 0.48 and Kappa(MSE) = 0.26. Concerning both abnormal Bayley outcome and ASD, the developmental abnormalities detection shows that entropy and fractal features outperform the other subsets of attributes and the multiclass analysis shows that those features can also discriminate patients with ASD from patients with only developmental abnormalities (Kappa(MFA) = 0.41 and Kappa(MSE) = 0.36). Conclusion: Quantitative EEG analysis shows that a dysmature EEG, i.e. a signal with higher fractal regularity and lower entropy, is associated with autism spectrum disorder or abnormal Bayley outcome at 2 years of age.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30103 - Neurosciences (including psychophysiology)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Biomedical Signal Processing and Control

ISSN

1746-8094

e-ISSN

—

Volume of the periodical

68

Issue of the periodical within the volume

July

Country of publishing house

GB - UNITED KINGDOM

Number of pages

12

Pages from-to

102658

UT code for WoS article

000670367800009

EID of the result in the Scopus database

2-s2.0-85105339277