Neuroimaging in neurodevelopmental disorders: focus on resting-state fMRI analysis of intrinsic functional brain connectivity

Abstract

Purpose of review: Resting-state fMRI assessment of instrinsic functional brain connectivity (rs-fcMRI) in autism spectrum disorders (ASD) allows assessment of participants with a wide range of functioning levels, and collection of multisite databases that facilitate large-scale analysis. These heterogeneous multisite data present both promise and methodological challenge. Herein, we provide an overview of recent (1 October 2016-1 November 2017) empirical research on ASD rs-fcMRI, focusing on work that helps clarify how best to leverage the power of these data.

Recent findings: Recent research indicates that larger samples, careful atlas selection, and attention to eye status of participants will improve the sensitivity and power of resting-state fMRI analyses conducted using multisite data. Use of bandpass filters that extend into a slightly higher frequency range than typical defaults may prevent loss of disease-relevant information. Connectivity-based parcellation as an approach to region of interest analyses may allow for improved understanding of functional connectivity disruptions in ASD. Treatment approaches using rs-fcMRI to determine target engagement, predict treatment, or facilitate neurofeedback demonstrate promise.

Summary: Rs-fcMRI data have great promise for biomarker identification and treatment development in ASD; however, ongoing methodological development and evaluation is crucial for progress.