Abstract
BackgroundWhile autism and attention-deficit/hyperactivity disorder (ADHD) are considered distinct conditions from a diagnostic perspective, clinically they share some phenotypic features and have high comorbidity. Regardless, most studies have focused on only one condition, with considerable heterogeneity in their results. Taking a dual-condition approach might help elucidate shared and distinct neural characteristics.MethodGraph theory was used to analyse topological properties of structural covariance networks across both conditions and relative to a neurotypical (NT; n = 87) group using data from the ABIDE (autism; n = 62) and ADHD-200 datasets (ADHD; n = 69). Regional cortical thickness was used to construct the structural covariance networks. This was analysed in a theoretical framework examining potential differences in long and short-range connectivity, with a specific focus on relation between central graph measures and cortical thickness.ResultsWe found convergence between autism and ADHD, where both conditions show an overall decrease in CT covariance with increased Euclidean distance between centroids compared with a NT population. The 2 conditions also show divergence. Namely, there is less modular overlap between the 2 conditions than there is between each condition and the NT group. The ADHD group also showed reduced cortical thickness and lower degree in hub regions than the autism group. Lastly, the ADHD group also showed reduced wiring costs compared with the autism groups.ConclusionsOur results indicate a need for taking an integrated approach when considering highly comorbid conditions such as autism and ADHD. Furthermore, autism and ADHD both showed alterations in the relation between inter-regional covariance and centroid distance, where both groups show a steeper decline in covariance as a function of distance. The 2 groups also diverge on modular organization, cortical thickness of hub regions and wiring cost of the covariance network. Thus, on some network features the groups are distinct, yet on others there is convergence.
Highlights
Autism spectrum conditions are characterized by deficits in social communication alongside unusually restricted interests and repetitive behaviors, difficulties adjusting to unexpected change, and sensory hypersensitivity (American Psychiatric Association 2013)
We found convergence between autism and attention-deficit/hyperactivity disorder (ADHD), where both conditions show an overall decrease in CT
The ADHD group showed reduced wiring costs compared with the autism groups
Summary
Autism spectrum conditions ( autism) are characterized by deficits in social communication alongside unusually restricted interests and repetitive behaviors, difficulties adjusting to unexpected change, and sensory hypersensitivity (American Psychiatric Association 2013). There is a tendency for autism to be associated with excess local or short-range connectivity, relating to enhanced local processing. This is thought to be accompanied by decreased global or long-range connectivity, relating to impaired integration as manifested in “weak central coherence.”. Zielinski et al (2012) reported a connectivity reduction in salience network and posterior regions of the default mode network (DMN), whereas frontal DMN regions were overconnected This notion of network dependent alterations was recently confirmed by a large structural covariance study in the ABIDE dataset (Long et al 2016). Taking a dual-condition approach might help elucidate shared and distinct neural characteristics
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