Overt social interaction and resting state in young adult males with autism: core and contextual neural features

Abstract

Conversation is an important and ubiquitous social behavior. Individuals with Autism Spectrum Disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (N=19) without intellectual disability and age-and IQ-matched typically developing controls (N=20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: Conversation, which had high social demand, and Repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven inter-regional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants' social impairments.These results were then compared with previously-acquired resting-state data (56 Autism, 62Control participants). While some inter-regional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during Task and decrease during Rest. In contrast, striato-and thalamocortical relationships with socially engaged brain regions are increased in both Task and Rest, and may be core to the condition of autism. IN AUTISM 3 SOCIAL INTERACTION & REST

Altered functional connectivity during speech perception in congenital amusia

“…The magnitude of transient head motion was calculated from the six motion parameters obtained during image realignment and aggregated as a single variable using AFNI's @1dDiffMag to calculate a Motion Index (Berman et al, 2016;Gotts et al, 2012;Jasmin et al, 2019c). This measure is similar to average Frame Displacement over a scan (Power et al, AMUSIA AND LANGUAGE PROCESSING 2012) and is in units of mm per repetition time.…”

“…Beta series analysis requires initial seed voxels, vertices, or regions to be identified, whose trial-to-trial changes in activity are then compared to those of the rest of the brain. Rather than choose a priori seeds derived from the literature, which used mainly musical tasks or resting state, we used a data-driven approach to search for the largest group and condition differences in functional connectivity (Berman et al, 2016;Cole et al, 2010;Gotts et al, 2012;Jasmin et al, 2019c;Meoded et al, 2015;Song et al, 2015;Steel et al, 2016;Stoddard et al, 2016;Watsky et al, 2018). To do this, we first calculated the "whole-brain connectedness" (similar to 'centrality' in graph theory) of each cortical vertex (a procedure available in AFNI as the 3dTCorrMap function).…”

“…The reason for this choice was so that voxels in cortex and subcortex would contribute equally to our measure of global (whole-brain) connectivity. First, average gray-matter beta value was calculated for each trial by intersecting each image in the beta series with a whole-brain gray matter mask (which excluded white matter and ventricles) and calculating the average beta value within the mask (Gotts et al, 2012;Jasmin et al, 2019c). Next, this gray matter average was correlated with each cortical surface vertex's beta series, separately for each subject and condition, to obtain whole-brain connectedness maps.…”

“…An analogy is in Analysis of Variance, where a significant omnibus test indicates a difference exists, but follow-up testing is required to determine where in the model differences exist (Gotts et al, 2012). Thus, to locate the regions driving this pattern, we undertook a second step: follow-up seed-to-wholebrain testing (Cole et al, 2010;Gotts et al, 2012;Jasmin et al, 2019c). Each seed region was examined with respect to its connectivity pattern with every cortical vertex and subcortical structure.…”

Altered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?

“…In the current review, we first provide an overview of the main theoretical perspectives on connectivity in ASD, and we then review the relevant evidence from resting-state functional connectivity fMRI. We focus the subsequent discussion of causality around two recent studies from our lab that have attempted to manipulate the patterns of functional connectivity, one by neurofeedback (Ramot et al, 2017) and one by altering the task state (Jasmin et al, 2018).…”