A Shift to Randomness of Brain Oscillations in People with Autism
Abstract
Background Resting-state functional magnetic resonance imaging (fMRI) enables investigation of the intrinsic functional organization of the brain. Fractal parameters such as the Hurst exponent, H, describe the complexity of endogenous low-frequency fMRI time series on a continuum from random (H = .5) to ordered (H = 1). Shifts in fractal scaling of physiological time series have been associated with neurological and cardiac conditions.Methods Resting-state fMRI time series were recorded in 30 male adults with an autism spectrum condition (ASC) and 33 age- and IQ-matched male volunteers. The Hurst exponent was estimated in the wavelet domain and between-group differences were investigated at global and voxel level and in regions known to be involved in autism.Results Complex fractal scaling of fMRI time series was found in both groups but globally there was a significant shift to randomness in the ASC (mean H = .758, SD = .045) compared with neurotypical volunteers (mean H = .788, SD = .047). Between-group differences in H, which was always reduced in the ASC group, were seen in most regions previously reported to be involved in autism, including cortical midline structures, medial temporal structures, lateral temporal and parietal structures, insula, amygdala, basal ganglia, thalamus, and inferior frontal gyrus. Severity of autistic symptoms was negatively correlated with H in retrosplenial and right anterior insular cortex.Conclusions Autism is associated with a small but significant shift to randomness of endogenous brain oscillations. Complexity measures may provide physiological indicators for autism as they have done for other medical conditions.
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Several recent imaging studies on resting-state functional connectivity and DTI confirm disruptive neural activation dynamics in ASD within the vmPFC-VS-amygdala circuitry.
“In fact, several recent imaging studies on resting-state functional connectivity and DTI confirm disruptive neural activation dynamics in ASD within the vmPFC–VS–amygdala circuitry [78-81].”
From Social “wanting” dysfunction in autism: neurobiological underpinnings and treatment implications (2012) · cites this paper as [80]
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A Brainnetome Atlas Based Mild Cognitive Impairment Identification Using Hurst Exponent
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Self-referential and social cognition in a case of autism and agenesis of the corpus callosum
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- Authors
- Lai, M.-C., Lombardo, M. V., Chakrabarti, B., Sadek, S. A., Pasco, G., Wheelwright, S. J., Bullmore, E. T., Baron-Cohen, S., & Suckling, J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Lai, Meng-Chuan
- ORCID
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 68
- Issue
- 12
- Pages
- 1092-1099
- ISSN
- 0006-3223 (ISSN-L)
- OpenAlex
- W2091912373
- Cited by
- 153
- References
- 110
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 2 · 2023: 9 · 2022: 7 · 2021: 8 · 2020: 9 · 2019: 9 · 2018: 8 · 2017: 14 · 2016: 10 · 2015: 8 · 2014: 8 · 2013: 22 · 2012: 18
- FWCI
- 9.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- Cambridge Overseas Trust
- Medical Research Council
- Girton College, University of Cambridge
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- autism spectrum disorder, Hurst exponent, fractal scaling, resting-state fMRI, neural oscillations, wavelet analysis, autism severity, anterior insula, retrosplenial cortex, cortical midline structures
- MeSH terms
- Adult, Autistic Disorder, Brain, Humans, Magnetic Resonance Imaging, Male, Fractals, Nonlinear Dynamics, Brain Waves
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