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Mol Autism. 2019 Jun 24;10:27. doi: 10.1186/s13229-019-0273-5. eCollection 2019.

Generalizability and reproducibility of functional connectivity in autism.

Author information

1
1Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108 USA.
2
2Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT 84112 USA.
3
3Department of Pediatrics, University of Utah, Salt Lake City, UT 84108 USA.
4
4Waisman Center, University of Wisconsin-Madison, Madison, WI 53705 USA.
5
5Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112 USA.
6
6Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719 USA.
7
7Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT 84604 USA.
8
8Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705 USA.
9
9McLean Hospital and Department of Psychiatry, Harvard University, Cambridge, MA 02478 USA.
10
10Department of Neurology, University of Utah, Salt Lake City, UT 84132 USA.

Abstract

Background:

Autism is hypothesized to represent a disorder of brain connectivity, yet patterns of atypical functional connectivity show marked heterogeneity across individuals.

Methods:

We used a large multi-site dataset comprised of a heterogeneous population of individuals with autism and typically developing individuals to compare a number of resting-state functional connectivity features of autism. These features were also tested in a single site sample that utilized a high-temporal resolution, long-duration resting-state acquisition technique.

Results:

No one method of analysis provided reproducible results across research sites, combined samples, and the high-resolution dataset. Distinct categories of functional connectivity features that differed in autism such as homotopic, default network, salience network, long-range connections, and corticostriatal connectivity, did not align with differences in clinical and behavioral traits in individuals with autism. One method, lag-based functional connectivity, was not correlated to other methods in describing patterns of resting-state functional connectivity and their relationship to autism traits.

Conclusion:

Overall, functional connectivity features predictive of autism demonstrated limited generalizability across sites, with consistent results only for large samples. Different types of functional connectivity features do not consistently predict different symptoms of autism. Rather, specific features that predict autism symptoms are distributed across feature types.

KEYWORDS:

Autism spectrum conditions; Functional connectivity MRI; Replicability; Reproducibility; Resting-state; fMRI

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