Autism Spectrum Disorder (ASD) is hallmarked by social-emotional reciprocity deficits. Social-emotional responding requires the clear recognition of social cues as well as the internal monitoring of emotional salience. Insular cortex is central to the salience network, and plays a key role in approach-avoidance emotional valuation. Consistent right anterior insular hypoactivity and variable volumetric differences of insular cortical volumes were shown previously. The current study analyzed anterior and posterior insular volume/asymmetry changes in ASD across age. Age was used as an additional grouping variable as previous studies indicated differential regional volume in ASD individuals before and after puberty onset. In the current sample, pre-teen ASD expressed left lateralized anterior insula, while adolescent ASD had right lateralization. Typically developing (TD) individuals expressed the opposite lateralization of anterior insula in both age-groups (right greater than left anterior insular volume among pre-teen TD and left greater than right anterior insular volume among adolescent TD). Social-emotional calibrated severity scores from the ADOS were positively correlated with leftward anterior insular asymmetry and negatively correlated with proportional right anterior insular volumes in ASD. Insular cortex has a lateralized role in autonomic nervous system regulation (parasympathetic control in the left, sympathetic control in the right). Atypical insular asymmetry in ASD may contribute to the development of networks with a diminished salience signal to human faces and voices, and may lead to more learned passive avoidant responses to such stimuli at younger ages, leading to more distressed responses in adolescence. Data here supports the use of early behavioral intervention to increase awareness of and reward for social-emotional cues.

Insular Cortex, while being one of the most highly integrative regions of the brain, continues to be one the least understood. Previous studies have found cytoarchitectural subregions within insular cortex, each with unique patterns of connectivity with other brain regions. Taken together, along with more recent functional analyses, evidence suggests that each insular subregion performs a unique functional role. Using a simple geometric bisecting algorithm (i.e., the Cohen Bisect), these subregions can accurately be sized and located. However, this method has only been used in a discontinued brain imaging application known as BrainImageJava (BIJ). In order to continue research on the function and makeup of insular cortical subregions, a new Cohen Bisect plugin was created for the Multi-Image Analysis GUI (Mango). Manual insular regions-of-interest (ROIs) were created among a sample of Fragile X Syndrome, Developmental Delay and Typically Developing children. Using this open-sourced plugin, anterior and posterior insular gray-matter volumes were reliably measured and showed no degradation between the original total volume and the post-bisect totals. Additional previously analyzed insular ROIs were converted from BIJ to Mango, and the new Cohen Bisect plugin was used reliably to confirm previous statistical results. The new Cohen Bisect Plugin for Mango incorporates an established methodology into a novel tool for researchers to approximate insular functional subregions using structural MRI.

Insular Cortex, a multimodal region with connectivity throughout the brain, has a role in numerous clinical disorders. Manual morphometry is the ideal means to measure volume of insular cortex, in order to capture subtle inter-subject variability, but is very time consuming. Automated image processing is far more efficient, but is susceptible to losing some of the anatomical variation across subjects. The goal of this study was to combine the accuracy of manual morphometry with the efficiency of an automated algorithm for obtaining measurements of human insular cortex using Advanced Normalization Tools (ANTs). Similar to the previously published protocol for hippocampus, landmarks were placed on insular cortex using MANGO, and ANTs was used to generate automated ROIs. Manual ROIs were used with the automated ROIs to create a correction algorithm that would improve the reliability over the fully automated ROIs. This segmentation adapter overlaps the automated ROI and the manual ROI and corrects the automated tracing (semi-automated). Manual ROIs were used from a previously analyzed sample in Fragile X Syndrome. Intra-class correlation coefficients (ICC) were used to test reliability. Results showed low reliability between manual tracings and ANTs automated tracings indicating that the automated approach alone is not enough. ICC between manual left and semi-automated left measurements was .784, and .864 between manual right and semi-automated right measurements. The semi-automated ROIs were found to be more accurate than just the automated ROIs, indicating this novel ANTs protocol may be a reliable tool for analyzing insular morphometry in larger subject samples.