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EEG Mu Rhythm in Typical and Atypical Development
Published on: April 9, 2014
Aberrant brain oscillatory coupling from the primary motor cortex in children with autism spectrum disorders
Kyung-Min An1, Takashi Ikeda1, Chiaki Hasegawa2
1Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan; Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa, Japan.
Abstract:
Autism spectrum disorder (ASD) often involves dysfunction in general motor control and motor coordination, in addition to core symptoms. However, the neural mechanisms underlying motor dysfunction in ASD are poorly understood. To elucidate this issue, we focused on brain oscillations and their coupling in the primary motor cortex (M1). We recorded magnetoencephalography in 18 children with ASD, aged 5 to 7 years, and 19 age- and IQ-matched typically-developing children while they pressed a button during a video-game-like motor task. The motor-related gamma (70 to 90 Hz) and pre-movement beta oscillations (15 to 25 Hz) were analyzed in the primary motor cortex using an inverse method. To determine the coupling between beta and gamma oscillations, we applied phase-amplitude coupling to calculate the statistical dependence between the amplitude of fast oscillations and the phase of slow oscillations. We observed a motor-related gamma increase and a pre-movement beta decrease in both groups. The ASD group exhibited a reduced motor-related gamma increase and enhanced pre-movement beta decrease in the ipsilateral primary motor cortex. We found phase-amplitude coupling, in which high-gamma activity was modulated by the beta rhythm in the primary motor cortex. Phase-amplitude coupling in the ipsilateral primary motor cortex was reduced in the ASD group compared with the control group. Using oscillatory changes and their couplings, linear discriminant analysis classified the ASD and control groups with high accuracy (area under the receiver operating characteristic curve: 97.1%). The current findings revealed alterations in oscillations and oscillatory coupling, reflecting the dysregulation of motor gating mechanisms in ASD. These results may be helpful for elucidating the neural mechanisms underlying motor dysfunction in ASD, suggesting the possibility of developing a biomarker for ASD diagnosis.

