Abnormal Maturation of Alpha Peak Frequency in Children with Autism Spectrum Disorder May be Explained By Abnormal White Matter Maturation

Poster Presentation
Saturday, May 4, 2019: 11:30 AM-1:30 PM
Room: 710 (Palais des congres de Montreal)
M. DiPiero, J. I. Berman, M. Ku, L. Blaskey, E. S. Kuschner, M. Kim, H. L. Green, T. P. Roberts and J. C. Edgar, Children's Hospital of Philadelphia, Philadelphia, PA
Background: Characterization of abnormal neural oscillatory processes in children with autism spectrum disorder (ASD) is considered a promising route to understanding brain dysfunction in ASD. Our laboratory reported abnormal maturation of resting-state alpha activity in children with ASD, with higher peak alpha frequency (PAF) in young children with ASD than age-matched typically-developing children (TDC). A study by Valdés-Hernández et al. established a relationship between PAF and diffusion magnetic resonance (DMR) fractional anisotropy (FA) in adults. The present study investigated relationships between PAF and DMR measures in TDC and ASD to better understand the structural features that contribute to normal/abnormal alpha rhythms in children

Objectives: To determine if PAF and diffusion associations are observed in TDC and children with ASD.

Methods: Eyes-closed resting-state MEG data were obtained from 73 male TDC (M=11.9±2.97years) and 107 male children with ASD (M=11.7±2.72 years). Groups did not differ on age(p>0.05). A 15 regional source model was used to project MEG surface data into source space. A Fast Fourier Transform was applied to 3.41 second epochs of continuous data at each regional source. PAF was identified (8-12 Hz) from regional sources’ average power spectra, with the PAF value obtained from the source showing the largest amplitude alpha activity. DMR with b=1000s/mm2 and 30 gradient directions was collected. Artifacts in the data were corrected using FSL’s eddy. FA and radial diffusivity (RD) were measured in white matter subserving PAF regional source (midline parietal regions) to characterize local white matter maturation.

Results: Given known associations between age and both PAF/white matter integrity, a regression model with age, diffusion, and group was used to predict PAF. For both FA and RD, significant group-x-age-x-diffusion interactions(ps<0.01) indicated a different pattern of association for TDC and ASD. Simple effect analyses showed that whereas TDC age and diffusion metrics explained unique variance in PAF, neither age nor diffusion metrics predicted variance in PAF in ASD. In the TDC group, regression analyses with age entered 1st and FA 2nd showed that age explained 24% of variance(p=0.001) and FA explained 4% of variance(p<0.05) in PAF. Reversing the order of entry, FA explained 14% of variance(p=0.001) and age explained 14% of variance(p=0.001) in PAF. In the ASD group, age and FA together explained a non-significant 2% of PAF variance(p>0.05). A similar pattern of findings was observed for PAF and RD.

Conclusions: This is the first study to show associations between white matter structure and PAF in children, indicating white-matter maturation determines, in part, the dynamics of resting-state alpha. DMR measures of white-matter fiber density and myelination were directly proportional to occipital-thalamo-cortical alpha frequency. Myelination and white matter maturation support the rapid conduction velocities necessary to drive faster alpha rhythms. This relationship was not observed in ASD, indicating disruption of a basic developmental mechanism underlying resting-state-processes in ASD. To the extent that resting-state alpha rhythms are supported by thalamo-cortical circuitry, present findings support the hypothesis of a thalamic contribution to abnormal cortical activity in ASD.