Phase-Locked Frequency Contributions to Executive Functioning in Children with and without ASD

Thursday, May 12, 2016: 11:30 AM-1:30 PM
Hall A (Baltimore Convention Center)
T. Clarkson1, A. R. Bhandarkar2 and S. Faja3, (1)Boston Children's Hospital: Harvard Med School, Boston, MA, (2)Laboratories of Cognitive Neuroscience, Boston Children's Hospital: Harvard Med School, Boston, MA, (3)Boston Children's Hospital/Harvard Medical School, Boston, MA

Executive Functioning (EF) is the ability to manage complex or conflicting information in the service of a goal. Children with autism spectrum disorders (ASD) show deficits in EF but little is known about what neural networks contribute to this phenotype. One region implicated in conflict monitoring and working memory is the Anterior Cingulate Cortex (ACC), which is a known theta oscillatory generator (Tsujimoto, et al. 2006). Event-related time-frequency analysis can be used to help determine phase-locked frequency contributions to the neural signal, which help elucidate regional activation based on known oscillatory generators (Roach, & Mathalon, 2008). A developmentally appropriate flanker task was used for measuring phase-locked frequency responses in the N2 component in typically developing (TYP) children compared to children with ASD. 

Objectives:   To determine whether phase-locked frequency band activities during the N2 ERP component predict EF performance in children with and without ASD.

Methods:   19 children with ASD and 29 TYP children between the ages of 7-11 years participated. Additional children with ASD are being recruited. All had an IQ > 85 and there were no group differences on IQ, age or gender. The EF Battery included the Stroop task to measure inhibition of interfering information, the Change task to examine monitoring, the Backwards Digit Span to measure working memory, and the Flanker task as another measure of inhibition. Time-frequency analysis using the Fourier Transform on averaged ERP waveforms was used to examine phase-locked spectral data within the N2 component in the incongruent condition. 

Results:   In the TYP group, higher theta and beta power predicted of worse monitoring, (F(2, 28) = 11.67, p< 0.001) with an R2= .46. Additionally, higher theta and alpha power predicted worse inhibition (F(2, 21) = 3.54, p< 0.049) with an R2= .27 on the Stroop task, and higher theta and beta power predicted worse inhibition on the Flanker task (F(2, 29) = 3.61, p=0.04). Theta power alone predicted worse working memory (F(1,29)= 4.09, p=0.05). In the ASD group, theta and beta power trended towards predicting poor working memory performance (F(2, 18) = 3.23, p= 0.06), R2= .29.

Conclusions:   Overall within the TYP group, increased theta power within the N2 predicted worse EF performance on our tasks that measured monitoring, inhibition, and working memory. This is consistent with previous literature that demonstrated increased ACC activation, which is a theta oscillatory generator, is associated with increased conflict monitoring activity on more difficult tasks.  More involvement of the ACC indexed by theta suggests more effortful neural response, thus worse overall performance. Within the TYP group these findings suggest that phase-locked time-frequency analysis could be a powerful tool for examining specific neural activity and brain networks that are important for EF performance. Specifically, an increase in phase-locked theta power during the N2 is a good indicator of poor EF abilities. Within the ASD group, our initial examination did not show this pattern, only a trend in theta and beta power related to working memory. However data collection is ongoing for children with ASD to increase statistical power.