%0 Journal Article
%T Parsing evoked and induced gamma response differences in Autism: A visual evoked potential study.
%A Dickinson A
%A Ryan D
%A McNaughton G
%A Levin A
%A Naples A
%A Borland H
%A Bernier R
%A Chawarska K
%A Dawson G
%A Dziura J
%A Faja S
%A Kleinhans N
%A Sugar C
%A Senturk D
%A Shic F
%A Webb SJ
%A McPartland JC
%A Jeste S
%A  
%J Clin Neurophysiol
%V 165
%N 0
%D 2024 Jun 8
%M 38959536
%F 4.861
%R 10.1016/j.clinph.2024.05.015
%X <B>OBJECTIVE: </B>Electroencephalography (EEG) measures of visual evoked potentials (VEPs) provide a targeted approach for investigating neural circuit dynamics. This study separately analyses phase-locked (evoked) and non-phase-locked (induced) gamma responses within the VEP to comprehensively investigate circuit differences in autism.<BR><B>METHODS: </B>We analyzed VEP data from 237 autistic and 114 typically developing (TD) children aged 6-11, collected through the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Evoked and induced gamma (30-90 Hz) responses were separately quantified using a wavelet-based time-frequency analysis, and group differences were evaluated using a permutation-based clustering procedure.<BR><B>RESULTS: </B>Autistic children exhibited reduced evoked gamma power but increased induced gamma power compared to TD peers. Group differences in induced responses showed the most prominent effect size and remained statistically significant after excluding outliers.<BR><B>CONCLUSIONS: </B>Our study corroborates recent research indicating diminished evoked gamma responses in children with autism. Additionally, we observed a pronounced increase in induced power. Building upon existing ABC-CT findings, these results highlight the potential to detect variations in gamma-related neural activity, despite the absence of significant group differences in time-domain VEP components.<BR><B>CONCLUSIONS: </B>The contrasting patterns of decreased evoked and increased induced gamma activity in autistic children suggest that a combination of different EEG metrics may provide a clearer characterization of autism-related circuitry than individual markers alone.