Atypical Visual Saliency in Autism Spectrum Disorder Quantified through Model-Based Eye Tracking

Abstract

Summary The social difficulties that are a hallmark of autism spectrum disorder (ASD) are thought to arise, at least in part, from atypical attention towards stimuli and their features. To investigate this hypothesis comprehensively, we characterized 700 complex natural scene images with a novel 3-layered saliency model that incorporated pixel-level (e.g., contrast), object-level (e.g., shape), and semantic-level attributes (e.g., faces) on 5551 annotated objects. Compared to matched controls, people with ASD had a stronger image center bias regardless of object distribution, reduced saliency for faces and for locations indicated by social gaze, yet a general increase in pixel-level saliency at the expense of semantic-level saliency. These results were further corroborated by direct analysis of fixation characteristics and investigation of feature interactions. Our results for the first time quantify atypical visual attention in ASD across multiple levels and categories of objects.

Infant viewing of social scenes is under genetic control and is atypical in autism

“…Variation in stimulus image properties can be seen in the histograms themselves (parts c-h and m-r) as well as in the statistical comparisons of video image property profiles (parts i-j and s-t, compared by two-sample Kolmogorov-Smirnov tests). These data underscore the notion that “eyes” are a semantic content category rather than a singular stimulus image property 28 , a notion consistent with research distinguishing stimulus-driven or “bottom-up” 43–47 processes in visual saliency from those that are goal-directed or “top-down” 26,27,48–51 .…”

“…Specifically, we analyzed the lightness and color (color opponency in red-green and blue-yellow following the CIE 1976 model 42 ), contrast (RMS, root-mean-squared contrast), orientation gradients (sum of local maxima of image intensity gradient), and amount of motion (sum of change in image intensity) present within all eye regions in all videos 28,43 . Image property profiles for representative videos are plotted in Extended Data Figure 7.…”

“…Greater-than-zero concordance when each twin watched different videos or different content categories would evidence goal-directed action, less dependent on the exact stimulus (flexibly seeking social information as a form of active niche-picking 7 ). For each test, we measured levels of eye-looking and quantified physical image properties of all eyes stimuli 28 (Extended Data Figure 7). …”

Disentangling signal and noise in autism spectrum disorder

“…However, in line with the current view, this atypical salience estimation is not limited to faces or other social stimuli. Wang et al (2015) recently demonstrated that saccade hot spots (across various natural images), were more determined by lowlevel salience (e.g., contrast) in ASD than semantic-level salience as was the case for typically developing individuals.…”

An Algorithm for Automatically Detecting Dyslexia on the Fly

“…Therefore, atypical eye movements are although a secondary consequence of dyslexia, eye tracking is an effective means for assessment of the processing demands that dyslexic readers experience while reading which creates a sound basis for developing predictive and automated models useful for screening [53]. Similarly, eye tracking during free viewing of natural images and videos have been implemented to differentiate subjects with Parkinson's disease, schizophrenia and autism spectrum disorders from control subjects [56], [57].…”