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S087-2

Increasing Signal Variability During Development and Its Relevance to Autism
Spectrum Disorders

Tetsuya Takahashi

Research Center for Child Mental Development, Kanazawa University, Japan

Background/Objective: During development, the human brain demonstrates a phenomenal growth
of neural connections. One core neurobiological mechanism of autism spectrum disorders (ASD)
involves aberrant neural connectivity during development. The recent advent of nonlinear analytic
methods, which have served for the quantitative description of the brain signal complexity, has
provided new insights into neural connectivity.

Method: We examined magnetoencephalography (MEG) signal complexity using multiscale entropy,
an estimate of time-series signal complexity associated with long-range temporal correlation, in 80
typically developed children (32-94 m) and 52 children with ASD (38-92 m).

Result: In typically developed children, MEG signal complexity was significantly increased with
age across coarser time scales predominantly in posterior brain regions, whereas no significant age
related changes were found in children with ASD. Additionally, typically developed children
demonstrated significant left-sided lateralization across finer temporal scales in temporal region,
which was lacking in children with ASD.

Conclusion: Our findings suggest that the increase in MEG complexity along with aging may be a
reflective of typical neural development. Furthermore, multiscale entropy analysis applying to MEG
may provide useful information in understanding the neurophysiological mechanisms and diagnosis
in ASD.