Post published on Twitter/X on 19 Nov 2022 07:51

Abstract

Abstract Background It is well-established that individuals with autism show atypical functional brain connectivity. However, the role this plays in behavior, especially in naturalistic social settings, has remained unclear. Some atypical patterns may reflect core deficits, while others may instead compensate for deficits and promote adaptive behavior. Distinguishing these possibilities requires measuring the ‘typicality’ of spontaneous behavior and determining which connectivity patterns correlate with it. Methods Thirty-nine male participants (19 autism, 20 typically-developed) engaged in 115 spontaneous conversations with an experimenter during fMRI scanning (Jasmin, et al., 2019, Brain). A classifier algorithm was trained to distinguish participants by diagnosis based on 81 semantic, affective and linguistic dimensions derived from their use of language. The algorithm’s certainty that a participant was in either the autism or typical group was used as a measure of task performance and compared with functional connectivity levels. Results The algorithm accurately classified participants (74%, P =.002), and its scores correlated with clinician-observed autism signs (ADOS) (r s =.56, P =.03). In support of a compensatory role, greater functional connectivity, most prominently between left-hemisphere social communication regions and right inferior frontal cortex, correlated with more typical language behaviour, only for the autism group (r s =.56, P =.01). Conclusion We report a simple and highly generalizable method for quantifying behavioral performance and neural compensation during complex spontaneous social behavior, without the need for an a priori benchmark. The findings suggest that functional connectivity increases in autism during communication reflect a neural compensation strategy.