bioRxivNeuroscience
Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling
Abstract
Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.\n\nHighlightsO_LISensory and perceptual aberrations are becoming a core feature of the ASD symptom prolife.\nC_LIO_LIBrain oscillations and functional connectivity are consistently affected in ASD.\nC_LIO_LIRelationships (coupling) between high and low frequencies are also deficient.\nC_LIO_LINovel framework proposes the ASD brain is marked by local dysregulation and reduced top-down connectivity\nC_LIO_LIThe ASD brains ability to predict stimuli and events in the environment may be affected\nC_LIO_LIThis may underlie perceptual sensitives and cascade into social processing deficits in ASD\nC_LI
- organism: human
- assay: electronic health records
- assay: imaging
- research focus: benchmarking
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
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