Manipulating image luminance to improve eye gaze and verbal behavior in autistic children

Autism has been characterized by a tendency to attend to the local visual details over surveying an image to understand the gist—a phenomenon called local interference. This sensory processing trait has been found to negatively impact social communication. Although much work has been conducted to understand these traits, little to no work has been conducted to intervene to provide support for local interference. Additionally, recent understanding of autism now introduces the core role of sensory processing and its impact on social communication. However, no interventions to the end of our knowledge have been explored to leverage this relationship. This work builds on the connection between visual attention and semantic representation in autistic children. In this work, we ask the following research questions: RQ1: Does manipulating image characteristics of luminance and spatial frequency increase likelihood of fixations in hot spots (Areas of Interest) for autistic children? RQ2: Does manipulating low-level image characteristics of luminance and spatial frequency increase the likelihood of global verbal responses for autistic children? We sought to manipulate visual attention as measured by eye gaze fixations and semantic representation of verbal response to the question “What is this picture about?”. We explore digital strategies to offload low-level sensory processing of global features via digital filtering. In this work, we designed a global filter to reduce image characteristics found to be distracting for autistic people and compared baseline images to filtered images in 11 autistic children. Participants saw counterbalanced images over 2 sessions. Eye gaze in areas of interest and verbal responses were collected and analyzed. We found that luminance in non-salient areas impacted both eye gaze and verbal responding—in opposite ways. Additionally, the interaction of luminance and spatial frequency in areas of interest is also significant. This is the first empirical study in designing an assistive technology aimed to augment global processing that occurs at a sensory-processing and social-communication level. Contributions of this work include empirical findings regarding the quantification of local interference in images of natural scenes for autistic children in real-world settings; digital methods to offload global visual processing to make this information more accessible via insight on the role of luminance and spatial frequency in visual perception and semantic representation in images of natural scenes.

LouAnne Boyd, Vincent Berardi, Deanna Hughes, Franceli Cibrian, Jazette Johnson, Viseth Sean, Eliza DelPizzo-Cheng, Brandon Mackin, Ayra Tusneem, Riya Mody, Sara Jones, Karen Lotich