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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

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Published on: September 12, 2011

Resting-State Functional Connectivity of the Amygdala in Autism: A Preregistered Large-Scale Study.

Dorit Kliemann¹, Paola Galdi¹, Avery L Van De Water¹

¹Department of Psychological and Brain Sciences (Kliemann, Van De Water, Egger), Department of Psychiatry (Kliemann), and Iowa Neuroscience Institute (Kliemann, Van De Water), University of Iowa, Iowa City; Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena (Kliemann, Adolphs); School of Informatics, University of Edinburgh, Edinburgh (Galdi); McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Mass. (Jarecka, Ghosh); Division of Biology and Biological Engineering and Chen Neuroscience Institute, California Institute of Technology, Pasadena (Adolphs); Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston (Ghosh).

The American Journal of Psychiatry

|August 29, 2024

Summary

This study found no reliable evidence for atypical amygdala functional connectivity in autism spectrum disorder (ASD), challenging leading neurobiological hypotheses. Results highlight the impact of analytical choices on autism brain imaging research.

Keywords:

Autism Spectrum Disorder Cognitive Neuroscience Functional Connectivity Neurodevelopmental Disorders Neuroimaging

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Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

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Published on: July 31, 2016

Area of Science:

Neuroscience
Neuroimaging
Autism Research

Background:

Leading hypotheses suggest underconnectivity, atypical amygdala function, and higher variability in autism spectrum disorder (ASD).
Previous research faced limitations including small sample sizes and analytic flexibility, hindering generalizability.
This study addresses these limitations to rigorously test hypotheses regarding amygdala functional connectivity in ASD.

Purpose of the Study:

To test three leading neurobiological hypotheses of ASD applied to amygdala functional connectivity.
To investigate functional connectivity (FC) magnitude, pattern similarity, and interindividual variability.
To address limitations of prior work by using a large, preregistered dataset and robust analytical methods.

Main Methods:

Analysis of resting-state functional MRI data from the Autism Brain Imaging Data Exchange (ABIDE) dataset (N=212 with ASD).
Examination of functional connectivity from two amygdala subdivisions across various anatomical scales.
Application of a Bayesian approach for hypothesis evaluation, considering preprocessing pipelines and anatomical specificity.

Main Results:

Inconsistent evidence for atypical amygdala FC magnitude in ASD.
Strong evidence supporting a typical multivariate pattern of amygdala functional connectivity in ASD.
No consistent evidence for increased interindividual variability in amygdala functional connectivity within the ASD group.

Conclusions:

Preregistered analyses found no reliable evidence for atypical amygdala functional connectivity in autism, contrary to leading hypotheses.
Findings underscore the critical influence of analytical choices (e.g., preprocessing, anatomical specificity) on neuroimaging results in ASD.
Future research should explore diverse hypotheses, employ multiple analytical pipelines, collect deeper individual data, and enhance participant diversity for robust findings.