Implications for Global and Local Visual Processing in Individuals with Learning Disabilities

Visual processing in humans is done by integrating and updating multiple streams of global and local sensory input. When this is not done smoothly, it becomes difficult to see the “big picture”, which has been found to have implications on emotion recognition, social skills, and conversation skills in individuals with Autism Spectrum Disorder (ASD) and other learning disabilities. Previous research in this field has aimed to direct ASD patients toward normative processing of the global features by developing and evaluating a filter which is intended to decrease local interference, or the prioritization of local details. This work attempts to utilize the filter to, not only shift eye gaze toward normative fixation areas or “hotspots”, but also to maintain focus on those areas. To operationalize these measures, location and duration of participants’ fixations were recorded during a free viewing task. An algorithm was then implemented that would isolate these areas and calculate whether a participant’s fixation was within those bounds. Statistical analysis revealed that, overall, participants did not have a significantly higher likelihood of hitting a hotspot in a filtered image as opposed to a raw one. In addition, participants\u27 hit duration was not significantly different when viewing a filtered image as opposed to a raw one. However, there were some clinically significant findings among individual participants that warrant further investigation. Building on this work, we plan to conduct research that will help to understand how the spatial frequency in raw and filtered images affects the ability of the filter to redirect global processing. These findings will eventually be used to improve the image filter and conduct further research in this field

Spatial Frequency Implications for Global and Local Processing in Autistic Children

Visual processing in humans is done by integrating and updating multiple streams of global and local sensory input. Interaction between these two systems can be disrupted in individuals with ASD and other learning disabilities. When this integration is not done smoothly, it becomes difficult to see the “big picture”, which has been found to have implications on emotion recognition, social skills, and conversation skills. An example of this phenomenon is local interference, which is when local details are prioritized over the global features. Previous research in this field has aimed to decrease local interference by developing and evaluating a filter to help direct ASD patients towards normative processing of the global features in images. Within this process, this research focuses on whether an image’s spatial frequency was affected by the filter and how spatial frequency impacted the filter’s functionality. Spatial frequency can be defined as a measure of the periodic distribution of light versus dark in image. In this work, we isolated “hot spots”, which are areas in the image where the eye gaze of normative individuals fixated. Using the OpenCV package in Python, I implemented an algorithm to detect hotspots and draw a contour around each one. I then drew rectangles around the contours in each image and calculated the spatial frequency within each rectangle. Statistical analysis will reveal whether the spatial frequency of hot spots had an impact on the differences in normative and ASD fixations. We plan to use these findings to improve the image filter and conduct further research in this field

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 featured images in 11 autistic children. Participants saw counterbalanced images way 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–however in opposite ways (however versus high levels of luminance). 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 of and semantic representation in images of natural scenes