19940
Prefrontal Neurofeedback Training Approaches in Children with Autism Based on the Relative Power of EEG Rhythms Analysis

Saturday, May 16, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
Y. WANG1,2, E. M. Sokhadze2, L. L. Sears3, A. EI-Baz4, A. Tasman2 and M. F. Casanova2, (1)State Key Laboratory of Cognitive Neuroscience and Learning,Beijing Normal University, BEIJING, China, (2)Psychiatry and Behavioral Sciences, University of Louisville, Louisville, KY, (3)Department of Pediatrics, University of Louisville, Louisville, KY, (4)Department of Bioengineering, University of Louisville, Louisville, KY
Background:  

Electroencephalographic biofeedback training (so called brainwave neurofeedback) is a treatment potentially useful for improvement of self-regulation skills in autism spectrum disorder (ASD). We proposed that prefrontal neurofeedback training will be accompanied by changes in relative power of EEG bands and ratios of individual bands (e.g. theta/beta ratio). By using the custom-made MATLAB application based on wavelet transformation, we were able to detect changes in the relative power and band ratios during the neurofeedback course.

Objectives:

The goal of the study was to detect the correlations between prefrontal neurofeedback training and the changes in relative power of EEG bands and the individual band ratios. And further to find an effective approaches for prefrontal neurofeedback training.

Methods:  

The protocol used a training procedure, which according to specifications, represents wide band EEG amplitude suppression with simultaneous up-regulation of 40Hz centered gamma activity. In the first pilot study on 8 children and adolescents with ASD (~17.4 yrs) we used 12 sessions long course of prefrontal 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. Quantitative EEG analysis (qEEG) 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, beta, and gamma) and their ratios within and between sessions.

Results:

Using our custom-made MATLAB application, we were able to detect changes in the relative power and band ratios during the neurofeedback, specifically linear decrease of theta/beta ratio (from 9.54±3.57 to 7.81±1.46 mean decrease being -1.72±3.40) and increase of 40 Hz centered gamma (from 73.1±4.85 to 75.39±5.27) over 18 sessions of neurofeedback in 18 children with ASD. The pilot study that used only 12 sessions showed significant qEEG changes sessions but did show only trend of progress across the 12 sessions. Also, 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), while Hyperactivity scores also showed decrease (from 16.65±13.78 to 13.29±11.97)

Conclusions:

Our experiments showed advantages of 18 sessions long weekly prefrontal neurofeedback training course in children with autism. Neurofeedback effects in the autism group were expressed in increased relative power of gamma band, decreased Theta/beta and Theta/low beta ratios. 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.