Note: Most Internet Explorer 8 users encounter issues playing the presentation videos. Please update your browser or use a different one if available.

Resting State Quantitative EEG Differences At 3 Years of Age by Risk Status and Diagnostic Outcome for Autism Spectrum Disorders

Friday, 3 May 2013: 14:00-18:00
Banquet Hall (Kursaal Centre)
A. R. Levin1, V. Vogel-Farley2, H. Tager-Flusberg3 and C. A. Nelson4, (1)Neurology, Boston Children's Hospital, Boston, MA, (2)Children's Hospital Boston, Boston, MA, (3)Boston University, Boston, MA, (4)Boston Children's Hospital, Boston, MA
Background: Identification of early and predictive biomarkers for autism spectrum disorders (ASD) is of key importance, as it allows diagnosis and thus treatment to begin as early as possible, potentially resulting in improved outcomes.  EEG is one promising biomarker, as an often cited hypothesis is that autism is associated with alterations in the makeup of neural networks, with long-range underconnectivity and local overconnectivity (Geschwind & Levitt 2007), and one can infer brain-based connectivity using patterns of electrical activity.  Several studies (e.g. Murias et al. 2007) have previously demonstrated altered quantitative EEG  patterns in older children and adults with ASD compared to controls.  In younger children, prior studies have demonstrated altered quantitative EEG patterns (Tierney et al. 2012; Bosl et al. 2011) and altered white matter fiber tract organization (Wolff et al. 2012) in children at high risk for ASD (HRA) by virtue of having a sibling with ASD, which increases the risk of developing ASD nearly 20-fold (Ozonoff et al. 2011), compared to siblings of typically developing children (low risk controls, LRC).  Because neural networks change with age, further evaluation of the developmental trajectory of EEG findings in very young children at risk for ASD, and those who ultimately receive a diagnosis, is necessary in order to determine an EEG-based predictive biomarker for ASD.

Objectives: As part of a longitudinal study tracking the development of HRA and LRC children, we evaluated resting-state EEG in 3 year olds at high and low risk for ASD, and who do and do not meet diagnostic criteria for ASD, to evaluate for differences in quantitative EEG findings between these groups.  

Methods: EEG was collected from children at 36 months of age with a 128 HydroCel Sensor Net System (EGI, Inc, Eugene OR) while they were were seated on their mother’s lap, watching a lab assistant blowing bubbles.  The diagnosis of ASD was based on an ADOS by a certified examiner at 36 months of age, and confirmed by clinical impression. 

Results: Preliminary analyses demonstrate that HRA children who were diagnosed with ASD at 36 months have a right frontal asymmetry in absolute high alpha power (9-13 Hz), meaning there is higher high alpha power on the right compared to the left; typically developing (TD) children from both the HRA and LRC groups have a left frontal asymmetry in this frequency band.  Consistent with these differences in asymmetry, recent studies in our lab have suggested that HRA children show an initial left frontal asymmetry at 6 months that shifts rightward by 18 months, while LRC children show right frontal asymmetry that shifts leftward over the same age range.  Additionally, preliminary analyses have demonstrated that many of the spectral differences between the HRA and LRC groups seen in younger children have disappeared by age 3.

Conclusions: These findings suggest that altered quantitative EEG findings have the potential to become a biomarker for autism risk.  However, between-group differences appear to change significantly over time, highlighting the importance of evaluating specific findings over the course of development.

See more of: Neurophysiology 2
See more of: Neurophysiology
See more of: Brain Structure & Function
| More