Sex-Modulated Atypical Resting-State Functional Connectivity in Autism: An Independent Component Analysis

Thursday, May 15, 2014
Atrium Ballroom (Marriott Marquis Atlanta)
R. A. Bethlehem1, M. C. Lai1,2, M. V. Lombardo1,3, A. N. Ruigrok1, B. Auyeung1,4, J. Suckling5, E. Bullmore5, M. AIMS Consortium6, S. Baron-Cohen1,7 and B. Chakrabarti1,8, (1)Autism Research Centre, University of Cambridge, Cambridge, United Kingdom, (2)Department of Psychiatry, National Taiwan University College of Medicine, Taipei, Taiwan, (3)Department of Psychology, University of Cyprus, Nicosia, Cyprus, (4)Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom, (5)Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, (6)Institute of Psychiatry, King’s College London; Autism Research Centre, University of Cambridge; Autism Research Group, University of Oxford, Cambridge, United Kingdom, (7)CLASS Clinic, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom, (8)School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
Background: Atypical neural connectivity has been proposed to be a potential hallmark for autism, with hypotheses including decreased fronto-posterior and enhanced parietal-occipital connectivity, reduced long-range and increased short-range connectivity, and temporal binding deficits. However, empirical findings vary substantially depending on the aspects of connectivity examined, the developmental stage of the individual, the spatial and temporal scales, task versus no-task conditions, how motion artefacts are handled, and the specific neural systems of concern. In addition, the role of biological sex in modulating atypical connectivity in autism is not yet clear.

Objectives: (1) To explore the atypical connectivity hypothesis of autism using functional connectivity (FC) analysis on resting-state functional magnetic resonance imaging (fMRI) data, using a non-biased, model-free, data-driven approach: independent component analysis (ICA); (2) To explore if biological sex modulates the characteristics of resting-state FC in autism.

Methods: Resting-state fMRI data (3T, 13 minutes with TR=1302 ms, eyes closed) from 117 individuals in four groups (males with autism N=25, neurotypical males N=33, females with autism N=30, neurotypical females N=29), matched for age, IQ and in-scanner head-motion, was analyzed with ICA using the Group ICA Toolbox (running under Matlab). We investigated 29 components, out of a total of 59 estimated independent components, that showed a high goodness-of-fit with known resting-state networks (for the remaining components, 17 were labelled undetermined and 13 likely reflected aliasing noise signal or artefact). To test group differences in within-component FC, two-way factorial ANCOVAs (factor 1: diagnosis [autism, neurotypical], factor 2: sex [male, female]) were performed for the 29 component maps of interest, with age and average frame-wise displacement as nuisance covariates. Using permutation tests, we further compared group differences in FC between all 46 non-artefactual components.

Results: For within-component FC, main effects of diagnosis and sex were found in both directions, on almost all components that were examined. In brief, we found functional decoupling between the precuneus and the anterior cingulate in the autism group, as well as decreased coupling between the basal ganglia and medial prefrontal cortex. However, diagnosis-by-sex interactions were almost ubiquitously seen in regions other than those showing main effects. For between-component FC, the default mode network components were more functionally connected to other components in the male autism group compared to the male neurotypical group. This difference, however, was not apparent in the female group.

Conclusions: Results revealed evidence for atypical but heterogeneous connectivity in high-functioning adults with autism compared to neurotypical adults. The directionality of differences in within-component FC varied substantially with components. In addition, biological sex significantly modulated the effect of diagnosis in most components. Overconnectivity between the default mode network components and other components was found in autism, but only in males. Overall these indicate a complicated picture of atypical connectivity in autism, which at the same time substantially differed between males and females. More fine-grained descriptions on patterns of atypical connectivity in different subgroups of autism are needed, as opposed to an over-simplified view that general hypo- or hyper-connectivity marks the atypical neurobiology of autism.