2008 Poster Sessions : Combining Structural and Functional Neuroimaging Data for Characterizing Organizational Development of Brain Systems

Student Name : Kaustubh Supekar
Advisor : Mark D. Musen
Research Areas: Artificial Intelligence
Understanding the development process of brain systems is critical for gaining insight into how mature brain functions work and for investigating neurodisorders such as autism and ADHD where this development process is disrupted.Neuroimaging techniques such as diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) are valuable tools for in-vivo measurement of the structure and function of the human brain. Recent technological advances in the application of these techniques have provided researchers with a unique opportunity to use neuroimaging data to study brain systems in-vivo. We have developed a novel method that characterizes the functional interactions between brain regions within specific systems as a function of age and structural connectivity between these regions. fMRI and DTI data acquired from healthy children (ages 8 to 10) and adults (ages 19 to 21) was used to compute functional interactions/connections and structural connectivity between brain regions, respectively. We hypothesized selective pruning and strengthening of functional connections with age. In particular, we expected reduction in short-range connections with age and simultaneous addition/strengthening of long-range connections.

In this poster, I will present the results of this study.

Kaustubh Supekar is currently a PhD Candidate in the department of Biomedical Informatics at Stanford University. He holds a BS and MS degree in Computer Science. He has held research positions at the Mid America Heart Institute and Children's Mercy Hospital. He was a research analyst at the Mayo Clinic before moving to Stanford University in 2004.

Kaustubh's research focuses on developing computational models based on multi-modal imaging data for early diagnosis and treatment of complex brain disorders. His ongoing PhD dissertation research work is on developing imaging-based biomarkers for early-stage detection and diagnosis of Alzheimer's disease – a complex brain disorder that effects more than 25 million people worldwide. For his dissertation work, recently, he received the 2007 Kathryn Grupe Award for Excellence in Research on Alzheimer's disease from the Alzheimer's Association of Northern California & Northern Nevada. He was also honored with the 2007 Student Award from the Organization of Human Brain Mapping.

Kaustubh has received fellowship in Biomedical Informatics from the European Engineering and Physical Sciences Research Council and Chancellor's Non-resident award from University of Missouri. His work has been featured and published in numerous international conferences and journals.