Functional Connectivity Scanning in Minimally-Verbal Children with ASD

Background:  Functional connectivity analysis is a powerful tool for examining neural phenotypes in ASD. However, there are multiple challenges to successful scanning of less verbal individuals and there is very little published research regarding functional scanning in this population. Recent advances in fMRI protocols and data analysis techniques, combined with specially-developed behavioral protocols, have allowed us to obtain adequate functional connectivity data for about ¾ of children and adolescents we have scanned.

Objectives:  To obtain valid functional connectivity data from minimally verbal children diagnosed with ASD.

Methods:  After initial phone screening regarding suitability for scanning, we recruited 12 children ages 8-16 who qualified based on current functional language level for either Module 1 or 2 on the ADOS-2. There were three key elements to successful imaging and interpretation. 1) A rich behavioral management program that included a) iPad-based video modeling practiced at home and in the imaging facility; b) as much time as needed in a mock partial scanner using a 3D printed head coil; c) as much time as needed over several sessions in the actual MRI scan room; d) true noise-cancelling headphones to reduce background sensitivities; e) parent and research assistant in the scan room to provide reassurance at all times; f) a short (8 minute) movie created especially for maintaining interest and calm for vulnerable samples. 2) implementation of multiband sequences that allow for rapid collection of high resolution functional data, counteracting unwanted physiological artifacts and allowing for discarding of epochs contaminated by movement and other artifacts. This allowed us to scan for as long as possible (a maximum of 2 x 8 minute sessions) while keeping and interpolating data from shorter periods of successful data acquisition. 3) Analytic techniques including standard ICA methods and a novel Bayesian fcMRI analysis method for estimating individual functional networks using a hierarchical Markov random field tool.

Results:  Preliminary results indicated successful data acquisition from more than 75% of participants. Data indicates markedly elevated internetwork synchrony relative to controls, similar to that seen in a previously-reported low-functioning Down Syndrome cohort. Increased short-range connectivity seems to be specifically abnormal for the low-functioning cohort versus previous higher-functioning autism samples and is negatively correlated with IQ. We hypothesize that ongoing analyses will show that connectivity between fusiform face area and language areas (Broca Area, Wernicke Area, lateral premotor cortex) with default mode network hubs will respectively predict social and language prognosis, respectively.

Conclusions:  Methods for successful scanning of lower-functioning, minimally-verbal individuals have the potential to substantially increase our understanding of the whole spectrum of autism, including both structural and functional scanning and the capacity to identify cross-sectional and longitudinal functional connectivity MRI biomarkers for language function, restrictive and repetitive behaviors, and social impairment. We will continue to share ongoing improvements to behavioral protocols and imaging/analysis methods in pursuit of this important goal.