- Awarded: 2021
- Award Type: Human Cognitive and Behavioral Science Award
- Award #: 875530
Atypical brain activity and connectivity are well demonstrated in older children and adults with autism spectrum disorder (ASD), but it is unknown when these changes first appear. Gamma band atypicalities are particularly relevant, as they are associated with synaptic dysfunction and excitatory/inhibitory imbalances. Magnetoencephalography (MEG) is the optimal non-invasive approach to measure brain oscillations and connectivity, providing direct, real-time measures of brain activity. A recent breakthrough in MEG technology is the use of optically pumped magnetometers (OPMs)1–3. OPM-MEG cap-mounted sensors yield a four-fold increased sensitivity and are movement-tolerant. OPMs are also very sensitive to the gamma band and allow robust single-subject studies.
In this project, Margot Taylor and her collaborators will study high (baby sibs) and low risk children longitudinally and two- to four-year-olds recently diagnosed with ASD. Baby sibs are young children from families who already have a child with ASD; they have a 20 to 30 percent chance of also being diagnosed with the condition. MEG will be recorded using OPMs in these three groups at resting-state and in response to emotional faces and visual spirals. The researchers will follow the baby sibs from 12 months, before diagnosis, to three years, when they do or do not receive an ASD diagnosis, and compare their data with matched, longitudinally studied controls, as well as recently diagnosed children. MEG spectral power analyses for the range of frequencies will be completed and functional connectivity will be compared across the three groups. MEG data and behavioral measures will be analyzed across all participants as continuous variables to determine the relations between the full spectrum of ASD, brain and behavior.
Upon competition of this study, the team will know if gamma and/or connectivity abnormalities are seen (a) prior to diagnosis, (b) at diagnosis and (c) how neural atypicalities and behavior evolve over the first years of life. This will allow stratification of toddlers and young children based on objective brain-behavior relations and be foundational for future knowledge translation and targeted interventions.
- Electroencephalography and eye-tracking measures as scalable biomarker-based predictors of ASD in high-risk infants
- MEG/MRS dose-response study of STX209 in autism spectrum disorder
- Neurobiological correlates of motor impairment in children with 16p11.2 syndrome
- Developing fNIRS as a brain function indicator in at-risk infants