OBJECTIVES: Autism is a severe neurodevelopmental disorder with a high rate of epilepsy and subclinical epileptiform activity. High physical connectivity on a microcolumnar level leading to epileptiform activity and low functional informational connectivity are assumed in autism. The aim of this study was to investigate nonlinear EEG brain dynamics in terms of synchronization in a group of children with autism spectrum disorders compared to a control group. We expected a lower degree of synchronization in autistic subjects. METHODS: The autistic group consisted of 27 patients with autism spectrum disorders diagnosed according to ICD-10. The mean age of the sample was 7.1 (SD 3.6) years, 14 of them were mentally retarded. Normal EEG was found in 9 patients, epileptiform EEG in 18 autistic patients. Four patients had a history of epileptic seizures, fully compensated in long term. The control group consisted of 20 children (mean age of 8.4, SD 2.3 years) with normal intelligence, without an epileptic history, investigated within the frame of the research program for cochlear implantation. They had normal neurological examination and suffered from perceptive deafness. Normal EEG was found in 17 of the control subjects, epileptiform EEG was in 3 control subjects. We analyzed night sleep EEG recordings from 10 channels (F3, F4, F7, F8, C3, C4, T3, T4, P3 and P4) with the inclusion of sleep stages NREM 2, 3 and 4 in the subsequent analyses. Coarse-grained entropy information rates between neighbouring electrodes were computed, expressing the synchronization between 11 selected electrode couples. RESULTS: Synchronization was significantly lower in the autistic group in all three examined NREM stages even when age and intelligence were taken into account as covariates. CONCLUSIONS: The results of the study confirmed the validity of the underconnectivity model in autism.
OBJECTIVES:Autism is a severe neurodevelopmental disorder with a high rate of epilepsy and subclinical epileptiform activity. High physical connectivity on a microcolumnar level leading to epileptiform activity and low functional informational connectivity are assumed in autism. The aim of this study was to investigate nonlinear EEG brain dynamics in terms of synchronization in a group of children with autism spectrum disorders compared to a control group. We expected a lower degree of synchronization in autistic subjects. METHODS: The autistic group consisted of 27 patients with autism spectrum disorders diagnosed according to ICD-10. The mean age of the sample was 7.1 (SD 3.6) years, 14 of them were mentally retarded. Normal EEG was found in 9 patients, epileptiform EEG in 18 autisticpatients. Four patients had a history of epilepticseizures, fully compensated in long term. The control group consisted of 20 children (mean age of 8.4, SD 2.3 years) with normal intelligence, without an epileptic history, investigated within the frame of the research program for cochlear implantation. They had normal neurological examination and suffered from perceptive deafness. Normal EEG was found in 17 of the control subjects, epileptiform EEG was in 3 control subjects. We analyzed night sleep EEG recordings from 10 channels (F3, F4, F7, F8, C3, C4, T3, T4, P3 and P4) with the inclusion of sleep stages NREM 2, 3 and 4 in the subsequent analyses. Coarse-grained entropy information rates between neighbouring electrodes were computed, expressing the synchronization between 11 selected electrode couples. RESULTS: Synchronization was significantly lower in the autistic group in all three examined NREM stages even when age and intelligence were taken into account as covariates. CONCLUSIONS: The results of the study confirmed the validity of the underconnectivity model in autism.