Brain responses to biological motion predict treatment outcome in young children with autism

Abstract

Autism spectrum disorders (ASDs) are common yet complex neurodevelopmental disorders, characterized by social, communication and behavioral deficits. Behavioral interventions have shown favorable results-however, the promise of precision medicine in ASD is hampered by a lack of sensitive, objective neurobiological markers (neurobiomarkers) to identify subgroups of young children likely to respond to specific treatments. Such neurobiomarkers are essential because early childhood provides a sensitive window of opportunity for intervention, while unsuccessful intervention is costly to children, families and society. In young children with ASD, we show that functional magnetic resonance imaging-based stratification neurobiomarkers accurately predict responses to an evidence-based behavioral treatment-pivotal response treatment. Neural predictors were identified in the pretreatment levels of activity in response to biological vs scrambled motion in the neural circuits that support social information processing (superior temporal sulcus, fusiform gyrus, amygdala, inferior parietal cortex and superior parietal lobule) and social motivation/reward (orbitofrontal cortex, insula, putamen, pallidum and ventral striatum). The predictive value of our findings for individual children with ASD was supported by a multivariate pattern analysis with cross validation. Predicting who will respond to a particular treatment for ASD, we believe the current findings mark the very first evidence of prediction/stratification biomarkers in young children with ASD. The implications of the findings are far reaching and should greatly accelerate progress toward more precise and effective treatments for core deficits in ASD.

Figure 1

Treatment effectiveness quantified as the change in SRS total raw score. Left: the black lines indicate each child's change in core autism symptom severity from pretreatment to posttreatment; the red line is the group mean. Right: the mean and the 95% confidence interval (CI) of Δ, the change score (that is, post minus pre). SRS, Social Responsiveness Scale.

Figure 2

Prediction of treatment effectiveness using univariate general linear model (GLM). Four distinct brain regions, in which greater pretreatment BOLD activation (% signal change) in the contrast of biological vs scrambled motion was associated with greater treatment effectiveness. Scatterplot illustrating pretreatment BOLD activation and actual change in severity (that is, post minus pre), with a horizontal reference line at y=0 indicating no change from pretreatment to posttreatment (that is, post=pre). BOLD, blood oxygen level dependent; FFG, fusiform gyrus; OFC, orbital frontal cortex; pSTS, posterior superior temporal sulcus; R, right; SPL, superior parietal lobule; TP, temporal pole.

Figure 3

Predictive accuracy of the univariate neuropredictive clusters, as estimated by MVPA with cross validation. Top: weight map showing the relative weights derived from the multivariate modeling of pretreatment response to biological motion that contributed to the prediction of change in severity (that is, post minus pre) at representative slices (MNI152 mm space). Bottom: scatterplot illustrating actual and predicted treatment effectiveness, with a horizontal reference line at y=0 indicating no change from pretreatment to posttreatment (that is, post=pre). Cross validation was based on a leave-one-subject-out framework. MNI, Montreal Neurological Institute; MVPA, multivariate pattern analysis; R, right.