Autism Speaks, Science, Grants Program

Click on researcher name for biography information.

Gillian Hayes, Ph.D.
University of California, Irvine
$83,563 over 2 years

Technology Support for Interactive and Collaborative Visual Schedules

Visual schedules can improve the ability for individuals with autism to understand, structure, and predict activities. They are often used as part of behavioral and educational interventions to support children and adults with autism spectrum disorder. These schedules, if properly augmented, can also provide avenues for better communication, real-time problem solving and schedule manipulation, and reporting about this information. Dr. Hayes aims to produce affordable and effective solutions for computer-based interactive, collaborative, ubiquitous, and intelligent visual schedule systems. Dr. Hayes' lab will develop interactive, sensing, and communications technologies that can be used both in schools and homes and that can support the user in dealing with the unexpected events in daily real-world life. They will leverage existing classroom and home practices, as well as technologies previously shown to support collaboration and interaction in special education and autism-specific classrooms, including technologies previously co-developed by Dr. Hayes with the help of prior Innovative Technology for Autism Initiative support.

What this means for people with autism: This project seeks to improve the day-to-day lives of people with autism by providing a mechanism for planning and conducting activities, as well as systematically tracking progress. First, this will make it easier for support networks (parents, teachers and specialists) to collaborate on education and treatment goals for a child with autism, as well as track the child's progress. Second, and perhaps most significantly, the products developed by this team should lead to increased autonomy by providing supports for navigating daily tasks successfully.

Thomas Keating, Ph.D.
Eugene Research Institute
$99,851 over 2 years

Self-Management of Daily Living Skills: Development of Cognitively Accessible Software for Individuals with Autism

This project will develop and field test a self-management software application that can be used by late-adolescents and adults with autism to monitor and manage their daily activities while at the same time interacting with caregivers in more self-determined and competent ways. The project will focus specifically on a multimedia application for enhancing self-management in the domains of personal care and household task management that will run on small, portable computers. Year 1 will focus on specification of software requirements, interface testing, and development guided by end user input from 5 individuals with autism and their family members. Year 2 will include continued prototype development and alpha testing of basic application functionality and interface controls, followed by a study in which both usability and changes in self-management competence will be examined. Project outputs will include a prototype self-management software application and technical reports which will be submitted for publication in major journals focused on autism and submitted for presentation at appropriate professional and family/consumer-oriented conferences.

What this means for people with autism: This project seeks to improve the daily lives of individuals with autism by providing a mechanism for planning and conducting activities, as well as providing remote feedback of key event completion to caregivers. The products developed by this team should lead to increased autonomy by providing supports for navigating daily tasks successfully and providing important data to those assisting them in planning daily routines.

Patrice (Tamar) Weiss, Ph.D.
University of Haifa
$92,290 over 2 years

Enhancing social communication for children with HFA

Children with High Functioning Autism (HFA) have the basic verbal ability for creating a story, but often lack the social understanding that is needed for such a task. Moreover, these children often prefer to play alone since they have difficulty in developing appropriate peer relationships and in interacting socially or emotionally with their peers. However, many of these children enjoy using technological devices such as computers since they provide direct and immediate feedback. Based on Dr. Weiss' previous research, partially funded by an Innovative Technology for Autism bridge grant, they hypothesize that running a game on a large “table-top” computer with a touch-screen interface (a computer with a display that is the size and orientation of a small table that allows both users to simultaneously interact with it by touch) that requires children to work together, will retain the advantages of working with a computer, yet facilitate an important dimension, namely communication and interaction with others. The main goal of the proposed study is to examine the effectiveness of a short-term intervention using an “enforced collaboration” paradigm to facilitate social-interactive skills among children with HFA compared to a group that has not received this intervention. The second goal is to examine whether can apply their newly acquired ability to collaborate in other tasks. The third goal is to examine the effectiveness of the Story Table intervention on children's ability to narrate a story after treatment. Finally, if successful, Dr. Weiss' lab will look at ways to bring these activities to less expensive computing platforms.

What this means for people with autism: This project targets the skills necessary for children with HFA to have natural social interactions, as well as participate in social environments that could lead to developmental and educational improvement. If successful as an intervention, this project would not only assist in the social development of children with HFA, but also help to reduce their social isolation.

Brian Roark, Ph.D.
Oregon Health and Science University
$100,000 over 2 years

Automated Measurement of Dialogue Structure in Autism

This project seeks to bring the power of machine-based sensing and computation to improve the study of speech patterns in individuals with autism. By combining technologies stemming from natural language processing methods and prosodic analysis methods, they expect to find aspects of speech that could be used as clinical markers. Current manual methods for measuring narrative coherence are not only difficult to obtain and extremely time consuming but it is unclear whether the human coder can even detect the statistical degree of semantic similarity as the machine can. This research will analyze recordings being collected from two narrative recall tests that have the potential to uncover a wider range of speech differences between ASD and others. The hope is that this will clinically define children with ASD relative to typically developing children and differentiate ASD from other groups who also have communication impairments, i.e., children with developmental language delay (DLD), as well as differentiate speech characteristics or markers that might better discriminate subtypes within the ASD umbrella (e.g., HFA vs. Asperger's). They expect that speech and language technologies will not only make critical diagnostic speech features easier to document but also may actually uncover distinguishing speech features in autism and autistic subtypes that have previously gone undetected.

What this means for people with autism: Potentially significant outcomes include improving the understanding of autism in a way that could lead to better diagnosis, and the refinement of speech analysis technologies that could not only improve the diagnosis of autism, but also make seeking that diagnosis faster and cheaper.