Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards.

ABSTRACT:

Objectives

Autism spectrum disorders (ASD) are diagnosed based on early-manifesting clinical symptoms, including markedly impaired social communication. We assessed the viability of resting-state functional MRI (rs-fMRI) connectivity measures as diagnostic biomarkers for ASD and investigated which connectivity features are predictive of a diagnosis.

Methods

Rs-fMRI scans from 59 high functioning males with ASD and 59 age- and IQ-matched typically developing (TD) males were used to build a series of machine learning classifiers. Classification features were obtained using 3 sets of brain regions. Another set of classifiers was built from participants' scores on behavioral metrics. An additional age and IQ-matched cohort of 178 individuals (89 ASD; 89 TD) from the Autism Brain

SUBMITTER: Plitt M 

PROVIDER: S-EPMC4309950 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature