The Human Cognitive and Behavioral Science RFA prioritizes research that produces foundational knowledge about the neurobehavioral differences associated with ASD. These projects are expected to inform or relate to the development and refinement of tools needed for translational efforts, such as biomarkers and outcome measures. Special emphasis is placed on objective, quantitative measures that may be used in conjunction with standardized clinical measures and genomic information to better characterize phenotypic and neurobiological variability within and across individuals with ASD.
Three tracks are offered within this RFA solicitation: Explorer, Expansion and Collaboration. The Explorer track is appropriate for early-stage projects in which establishing feasibility and proof-of-concept are the most relevant outcomes of the grant period. The Expansion track is appropriate for more mature projects with evidence of feasibility and preliminary validity, for which goals such as scalability, generalizability and/or more comprehensive measure validation are now the most relevant translational outcomes. The Collaboration track is appropriate for multi-lab, cross-institutional collaborative projects. Collaborative proposals should be built around transdisciplinary teams tackling a critical issue in the neurobehavioral differences of autism, with clear translational implications. Collaborations among different institutions are strongly encouraged. SFARI will consider funding a limited number of Collaboration proposals. As such, the proposal must provide a strong rationale for how synergies across multiple disciplines will be leveraged.
The Foundation encourages studies that capitalize on approaches that are informed by recent advances in computer vision, machine learning and speech processing, as well as psychophysics and non-invasive neuroscience techniques (e.g., EEG and MRI). SFARI has a strong interest in developmentally focused studies in areas that include, but are not limited to, communicative, social and ritualistic/stereotyped behavior, as well as sensory and motor function. SFARI also recognizes the importance of domains of function, such as attention, learning and memory, and sleep, in influencing core ASD diagnostic domains. While applications may propose laboratory-based measures, the Foundation is especially interested in real-world, scalable and quantitative measures of behavior (e.g., wearable devices and other methods of digital phenotyping).
The Foundation also encourages proposals that not only quantify specific phenotypes but also may contribute to the development of scalable innovative technologies for improving interventions and supports in humans. Successful applications would include a clear rationale for how the digital technology could be deployed to increase, maintain, or improve quantifiable functional outcomes in individuals with autism; for example, machine learning approaches that could amplify measurable gains from intensive behavioral interventions would be of interest.