4.7 Review

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

Journal

NEUROPSYCHOPHARMACOLOGY
Volume 40, Issue 1, Pages 171-189

Publisher

SPRINGERNATURE
DOI: 10.1038/npp.2014.172

Keywords

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Funding

  1. Autism Centers of Excellence [2P50 HD055784 NIH- NICHD, 1R01 HD073983-01 NIH/NICHD]
  2. Staglin Center for Cognitive Neurosciences
  3. Ahmanson-Lovelace Brain Mapping Center
  4. Medical Scientist Training Program [T32 GM008042]
  5. Neurobehavioral Genetics Training Program [5T32 MH073526-08 NIH]
  6. National Research Service Award [F31 MH093999-01A1]
  7. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [P50HD055784] Funding Source: NIH RePORTER
  8. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM008042] Funding Source: NIH RePORTER
  9. NATIONAL INSTITUTE OF MENTAL HEALTH [F31MH093999, T32MH073526] Funding Source: NIH RePORTER

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Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data.

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