Testing the Bottom-Up vs Top-Down Imbalance Hypothesis of ASD

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ABSTRACT / PROJECT SUMMARY Functional connectivity in the brains of individuals with autism spectrum disorders (ASD) has emerged as an important marker of neural abnormalities associated with the disorder. However, despite hundreds of studies on the topic, the specific nature of functional connectivity abnormalities that characterize the disorder remains unresolved and no unifying framework has emerged to describe it. Constructing a consistent model of the functional connectivity abnormalities that underlie ASD is absolutely essential for advancing our understanding of the neural etiology of the disorder. While the commonly accepted model is one where long- range functional connectivity is decreased in ASD while local functional connectivity is increased, many studies have shown increased or normal long-range functional connectivity in ASD and the evidence supporting the hypothesis that local functional connectivity is increased remains scant and indirect. To date, the vast majority of studies of functional connectivity in ASD have been carried out using fMRI, a technique that relies on the hemodynamic response and thus has a temporal resolution of <1Hz. It is well known, however, that functional connectivity is usually mediated by much faster frequency bands, commonly divided into five fundamental frequency bands: delta (1-2 Hz), theta (3-7 Hz), alpha (8-12 Hz), beta (13-30 Hz), and gamma (31-80 Hz). There is also recent evidence that these frequency bands mediate functional connectivity with preferred directionality. Based on our own preliminary data and current studies, we propose to test the hypothesis that ASD is characterized by increased long-range bottom-up (feedforward) functional connectivity, alongside decreased long-range top-down (feedback ) functional connectivity, and that the gamma and beta frequency bands, respectively, mediate these functional connectivity abnormalities. Here, we propose to test our hypothesis by obtaining MEG (magnetoencephalography) data from two spatial attention paradigms, visual and auditory, optimized for assessing bottom-up versus top-down functional connectivity, in 50 TD and 60 ASD individuals, ages 14-17. Specifically, we propose the following aims: (1) Test the hypothesis that bottom-up functional connectivity is abnormally increased in ASD in the auditory and visual domains, and this is manifested primarily in the gamma frequency band. (2) Test the hypothesis that top- down functional connectivity is abnormally reduced in ASD in the auditory and visual domains, and this is manifested primarily in the beta frequency band. (3) Test the hypothesis that neurophysiological functional connectivity measures derived using MEG will be predictive of ASD severity, diagnosis, and behavioral features, using robust correlations, canonical correlations, and machine learning techniques. We expect that the results of this study will lead to a substantially more detailed, comprehensive, and mechanistically motivated framework for the wide range of functional connectivity abnormalities observed in ASD.