Annually, the Vanderbilt Kennedy Center (VKC) allocates small grants to teams comprising VKC faculty, their trainees, Vanderbilt Data Science Institute (VDSI) faculty, and their trainees. These grants, known as the IDD-READS (Intellectual and Developmental Disability REsearch And Data Science) Awards, serve as an internal funding mechanism aimed at supporting research in intellectual and developmental disabilities. The focus is on leveraging innovative data science tools and fostering collaboration between VKC and VDSI.
Awarded projects engage in novel, multidisciplinary research that demonstrates a strong potential for securing external grant support. Encouragement is particularly extended to applications suggesting research that establishes connections between biomedical variables (such as neuroscience or genetics) and behavioral, educational, or policy components (e.g., learning, behavior problems).
“The IDD-READS awards present an exciting opportunity to unite the dedicated VKC community of researchers, committed to enhancing the lives of individuals with intellectual and developmental disabilities, with the impressive and expanding community of data scientists associated with the VDSI,” said Jeffrey Neul, M.D., Ph.D., Annette Schaffer Eskind Chair and VKC director. “Using data science methods to address complex issues in IDD research opens up new avenues for advancing our comprehension of these disorders and discovering approaches to make a meaningful impact.”
2024-25 IDD-Reads Grant Awards Recipients
(* indicates VKC membership)
Uncovering Multisensory Mental Embeddings in Neurotypical and Neurodivergent Populations with Generate Stimulus Sets
Principal Investigators (PIs): David Tovar, M.D., Ph.D., and Mark Wallace, Ph.D.*
Mark Wallace, Ph.D.
David Tovar, M.D.
This project delves into sensory processing in autism, focusing on how the brain integrates sensory information into cohesive mental concepts. Autistic individuals often perceive sensory stimuli differently, either as overly intense or not intense enough. Using advanced AI, the initiative aims to create multisensory stimuli that replicate these unique sensory experiences, combining visual and auditory elements to foster holistic sensory perception and mental concepts.
At the heart of the project is the evaluation of how these stimuli are integrated into a cohesive mental concept, using a computational model. The project will also compare the model’s results with actual brain activity, utilizing various neural datasets to examine between the AI-generated sensory combinations and neural responses in the brain.
The ultimate goal is to compare sensory processing between neurotypical and neurodiverse individuals. This comparison aims to identify distinct patterns in how each group organizes and interprets sensory information, enhancing our understanding of autism and potentially leading to more effective support strategies.
Developing a Tool for Data-Driven Evaluation and Clinical Interventions for Children with Cerebral Palsy
Elizabeth Martin, M.D.
Access to high-quality data for evidence-based clinical treatment options can be limited for health care providers serving individuals with rare or unique conditions. Cerebral palsy (CP) is the most common cause of childhood disability, but the underlying causes of this diagnosis are numerous and extremely variable, affecting the type of developmental disabilities that may present in each child as well as what clinical interventions are appropriate to optimize each child’s function.
The goal of this project is to develop and test a new data tool that a multidisciplinary team of physicians can use to search and analyze information to show exactly how other children with specific types of cerebral palsy responded to treatment. This will allow clinicians to give families a better idea of what they could expect from different treatment options when they are in a clinic visit and allow data-driven decision making in the clinic.
Application of Novel Time-Varying Heart Rate Variability to Quantify Autonomic Synchrony in Social Dyads of Youth With and Without Autism Spectrum Disorder
Rachael Muscatello, Ph.D.
PI: Rachael Muscatello, Ph.D.*
Autonomic nervous system control of the heart has recently been proposed as a possible biological marker of autism spectrum disorder (ASD). A key component of an ASD diagnosis is difficulties with social interactions, and it is believed that several brain regions help to control both the heart and aspects of social behavior. Thus, research has focused heavily on the link between the heart and the brain in ASD. Very little attention has been paid to the concept of interpersonal synchrony, which is defined as the time-matching of behavior, emotion, or internal experiences in two or more individuals.
Social experiences are reciprocal, to-and-fro interactions; therefore, it is likely that measurement of heart activity in two interacting individuals will provide further insights into the ways in which biology influences social communication and behavior in ASD. The challenge is that such research requires use of short periods of time to identify synchronous or asynchronous biology. Although our team has had success using short periods for heart rate, examining the variability of heart rate, which may be more informative, is more challenging.
This study will use a novel data-calculation method to quantify short-term heart rate variability and determine the relationship/synchrony in variability between two interacting youth. This will be the first study to use second-by-second variability analysis and synchrony in youth with ASD. Expectations are that the study will yield effective methods for precise examination of real-time biological synchrony that may be used to better understand the role of nervous system control of the heart and its implications for social behavior in youth with and without ASD.
To learn more about IDD-READS grant opportunities, click here.
