Autistic Traits in Neurotypical Adults: Correlates of Graph Theoretical Functional Network Topology and White Matter Anisotropy Patterns

Abstract

Attempts to explicate the neural abnormalities behind autism spectrum disorders frequently revealed impaired brain connectivity, yet our knowledge is limited about the alterations linked with autistic traits in the non-clinical population. In our study, we aimed at exploring the neural correlates of dimensional autistic traits using a dual approach of diffusion tensor imaging (DTI) and graph theoretical analysis of resting state functional MRI data. Subjects were sampled from a public neuroimaging dataset of healthy volunteers. Inclusion criteria were adult age (age: 18–65), availability of DTI and resting state functional acquisitions and psychological evaluation including the Social Responsiveness Scale (SRS) and Autistic Spectrum Screening Questionnaire (ASSQ). The final subject cohort consisted of 127 neurotypicals. Global brain network structure was described by graph theoretical parameters: global and average local efficiency. Regional topology was characterized by degree and efficiency. We provided measurements for diffusion anisotropy. The association between autistic traits and the neuroimaging findings was studied using a general linear model analysis, controlling for the effects of age, gender and IQ profile. Significant negative correlation was found between the degree and efficiency of the right posterior cingulate cortex and autistic traits, measured by the combination of ASSQ and SRS scores. Autistic phenotype was associated with the decrease of whole-brain local efficiency. Reduction of diffusion anisotropy was found bilaterally in the temporal fusiform and parahippocampal gyri. Numerous models describe the autistic brain connectome to be dominated by reduced long-range connections and excessive short-range fibers. Our finding of decreased efficiency supports this hypothesis although the only prominent effect was seen in the posterior limbic lobe, which is known to act as a connector hub. The neural correlates of the autistic trait in neurotypicals showed only limited similarities to the reported findings in clinical populations with low functioning autism.

Alterations in resting state connectivity along the autism trait continuum: a twin study

“…They are in line with earlier results of population-based studies on adolescents and adults, indicating that RS connectivity correlates with both autistic traits [49][50][51][52] and ASD symptom severity scores in clinical samples. 14,53,54 However, our results extend the latter findings as they show the relationship within twin pairs, where most genetic and environmental confounders are controlled for.…”

‘Subtypes’ in the Presentation of Autistic Traits in the General Adult Population

“…This has included studies examining visual search (e.g., Grinter et al 2009a, b), visual illusion susceptibility (Walter et al 2009), biological motion processing (van Boxtel and Lu 2013), multisensory integration (Palmer et al 2013;Donohue et al 2012), social attention (Freeth et al 2013a;Nummenmaa et al 2012), gaze responses (Bayliss and Tipper 2005;Chen and Yoon 2011) and neurophysiological characteristics (Jakab et al 2013;Puzzo et al 2010;Nummenmaa et al 2012;Sutherland and Crewther 2010). These studies most commonly use the autism-spectrum quotient (AQ), an inventory measure designed for use with adult community samples as either a screening or research tool (Baron-Cohen et al 2001).…”

Psychopathic traits are differentially associated with efficiency of neural communication

“…The more edges that information needs to pass through (i.e., the longer the average path length from one node to another node), the less efficient the network (Smit et al, ; Stam & Reijneveld, ; Stam et al, ; Tewarie et al, ). In general, less efficient networks tend to be associated with impairments in higher‐order cognitive processes (e.g., decision making, social reasoning; Jakab et al, ; Minati et al, ). By contrast, networks with more direct edges between neural nodes are more efficient (requiring less time or energy to transfer information between nodes), particularly when those direct edges are connecting functionally related nodes (i.e., nodes that commonly communicate or coactivate).…”

“…Additionally, the present study examines multiple resting-state EEG wavebands: alpha (8-12 Hz) and gamma (30-45 Hz). First, the alpha frequency bands are examined because low-frequency bands, such as alpha, are reliably implicated in long-range neural communication between spatially disparate brain regions (i.e., integration of information across disparate brain regions; Canolty et al, 2006;Doesburg, Vinette, Cheung, & Pang, 2012;Fell & Axmacher, 2011;Tewarie et al, 2014;von Stein & Sarnthein, 2000;Vourkas et al, 2014), which is vital for higher-order processes (Sepulcre et al, 2010); efficient alpha communication is linked with specific processes shown to be deficient in individuals high on psychopathic traits (e.g., decision making and affective theory of mind; Jakab et al, 2013;Minati et al, 2012); alpha activity is implicated in the functioning of the default mode network (Broyd et al, 2009;Chen, Feng, Zhao, Yin, & Wang, 2008), which appears to be dysfunctional in individuals with psychopathic traits (Glenn et al, 2009;Motzkin et al, 2011;Philippi et al, 2015); and abnormal alpha activity is associated with aggressive and antisocial individuals (Kamarajan et al, 2006;Lindberg et al, 2005;Rybak, Crayton, Young, Herba, & Konopka, 2006). Second, the gamma frequency band is examined because it is implicated in shortrange neural communication (von Stein & Sarnthein, 2000) vital to lower-order processes (Sepulcre et al, 2010), and recent evidence shows that individuals high on psychopathic traits display aberrant neural responses to more basic, lowerorder sensory processes (Tillem et al, 2016).…”