23857
Prefrontal Neurofeedback Training in Children with Autism

Saturday, May 13, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
E. M. Sokhadze1, M. F. Casanova2, D. P. Kelly3, Y. WANG4 and A. Tasman1, (1)University of Louisville, Louisville, KY, (2)University of South Carolina School of Medicine, Greenville, SC, (3)Pediatrics, Greenville Health System, Greenville, SC, (4)Allied Health School, Beijing Language and Culture University, Beijing, China
Background:  Electroencephalographic (EEG) biofeedback training (i.e., neurofeedback) is a treatment potentially useful for improvement of self-regulation skills in autism spectrum disorder (ASD). There are several techniques proposed to target symptoms of ASD using neurofeedback, with most differences being in the type of training (e.g., power of EEG bands, theta/beta ratio, coherence), topography (Cz or Pz), guidance by quantitative EEG (qEEG) and number of neurofeedback sessions (e.g., 20 vs. 30, etc.).

Objectives:  We proposed that prefrontal neurofeedback training will be accompanied by changes in relative power of EEG bands (e.g., 40 Hz centered gamma band) and ratios of individuals bands (e.g., theta/beta ratio) and will be more effective with higher number of training sessions (e.g., 12 vs 18 sessions). Outcomes measures along with EEG included as well behavioral ratings by parents/caregivers

Methods:  In the first pilot study on 8 children and adolescents with ASD (~17.4 yrs) we used 12 session long course of neurofeedback from AFz site, while in the second study on 18 children (~13.2 yrs) we administered 18 sessions of 25 min long prefrontal neurofeedback training. The protocol used a training procedure, which according to specifications, represents wide band EEG amplitude suppression with simultaneous upregulation of 40 Hz centered gamma activity. Custom-made Matlab program developed for the analysis of EEG data using wavelet analysis was useful to detect changes in EEG profiles during neurofeedback sessions. Quantitative EEG analysis at the training site was completed for each session of neurofeedback using a custom-made MATLAB application to determine the relative power of the individual bands (delta, theta, alpha, low beta, high beta, and gamma) and their ratios (theta/low beta, theta/high beta, etc.) within and between sessions. In both studies we analyzed Aberrant Behavior Checklist (ABC) ratings by caregivers (pre- and post-treatment).

Results: The pilot study that used only 12 sessions showed significant qEEG changes sessions but did show only trend of progress across the 12 sessions even though changes of individual EEG bands and their ratios were significant. The 18 session course of neurofeedback showed more significant improvements both in behavioral and qEEG measures. There was found a significant reduction in Lethargy subscale of the ABC. The rating scores showed reduction ( from 10.18 ± 6.07 to 7.53± 5.82, t(17)=3.29, p=0.005), while Hyperactivity scores also showed decrease (from 16.65 ±13.78 to 13.29 ± 11.97, t(17)=2.56, p=0.021).

Conclusions: Our experiments showed advantages of 18 session long weekly prefrontal neurofeedback course in children with autism. More future research is needed to assess qEEG changes at other topographies using brain mapping and using other outcome measures including behavioral evaluations to judge about clinical utility of prefrontal neurofeedback in children with ASD.