Impact of methodological variables on functional connectivity findings in autism spectrum disorders

Authors

  • Aarti Nair,

    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, California
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  • Christopher L. Keown,

    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Department of Cognitive Science, University of California, San Diego, California
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  • Michael Datko,

    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Department of Cognitive Science, University of California, San Diego, California
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  • Patricia Shih,

    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Neuroscience Department, Brown University, Providence, Rhode Island
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  • Brandon Keehn,

    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Laboratories of Cognitive Neuroscience, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
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  • Ralph-Axel Müller

    Corresponding author
    1. Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California
    2. Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, California
    • Correspondence to: Ralph-Axel Müller, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120. E-mail: rmueller@mail.sdsu.edu

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  • Aarti Nair and Christopher L. Keown. contributed equally to this work.

Abstract

Growing evidence suggests that Autism Spectrum Disorder (ASD) involves abnormalities of multiple functional networks. Neuroimaging studies of ASD have therefore increasingly focused on connectivity. Many functional connectivity (fcMRI) studies have reported network underconnectivity in children and adults with ASD. However, there are notable inconsistencies, with some studies reporting overconnectivity. A previous literature survey suggested that a few methodological factors play a crucial role in differential fcMRI outcomes. Using three ASD data sets (two task-related, one resting state) from 54 ASD and 51 typically developing (TD) participants (ages 9–18 years), we examined the impact of four methodological factors: type of pipeline (co-activation vs. intrinsic analysis, related to temporal filtering and removal of task-related effects), seed selection, field of view (whole brain vs. limited ROIs), and dataset. Significant effects were found for type of pipeline, field of view, and dataset. Notably, for each dataset results ranging from robust underconnectivity to robust overconnectivity were detected, depending on the type of pipeline, with intrinsic fcMRI analyses (low bandpass filter and task regressor) predominantly yielding overconnectivity in ASD, but co-activation analyses (no low bandpass filter or task removal) mostly generating underconnectivity findings. These results suggest that methodological variables have dramatic impact on group differences reported in fcMRI studies. Improved awareness of their implications appears indispensible in fcMRI studies when inferences about “underconnectivity” or “overconnectivity” in ASD are made. In the absence of a gold standard for functional connectivity, the combination of different methodological approaches promises a more comprehensive understanding of connectivity in ASD. Hum Brain Mapp 35:4035–4048, 2014. © 2014 Wiley Periodicals,Inc.

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