Neuroscience Guest Lectures

Professor David Glahn’s research focuses on elucidating the neurobiological roots of major mental illnesses through the integration of cognitive neuropsychological, functional and structural neuroimaging, and behavioral and molecular genetic approaches.  The ultimate goal is to identify the genes involved in affective and psychotic illnesses as well as those that influence non-pathological brain structure and function.  Gene localization could contribute significantly to our understanding of the underlying biology of complex mental illness, which would in turn improve future treatments and open potential for prevention strategies.

Progress in elucidating the pathophysiology of mental illnesses is predicated on causal gene identification. However, no genome-wide significant loci have yet been localized for most mental illnesses except for a few linked to schizophrenia and bipolar disorder that explain only a fraction of the genetic variance predisposing these illnesses.

Quantitative endophenotypes, traits that index genetic liability for an illness rather than diagnoses alone, provides a complementary strategy for identifying risk genes that has been successfully applied to identify disease-risk genes for heart disease, obesity, and diabetes. Quantitative endophenotypes established in family-based studies of clinical samples typically vary within the normal population, thus providing the opportunity to localize genes influencing these traits in unselected pedigrees.

Dr Glahn presents recent work in applying neurocognitive, neuroimage and transcriptional endophenotypes in search of risk genes for affective and psychotic illnesses as part of the “Genetics of Brain Structure and Function” study.

Dr Kennedy has extensive expertise in the development of image analysis techniques and was a co-founder of the Center for Morphometric Analysis (CMA) at the Massachusetts General Hospital. Throughout his career, he has participated in the advent of novel technologies such as MRI-based morphometric analysis (1989), functional MRI (1991) and diffusion tensor pathway analysis (1998). He has long-standing experience with development of neuroinformatics resources (Internet Brain Volumetric Database, Internet Brain Segmentation Repository, Internet Analysis Tools Registry) and participated as co-PI in the morphometry Biomedical Informatics Research Network (mBIRN). Dr Kennedy is the community liaison for the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) and a founding editor of the Neuroinformatics journal that debuted in 2003.

The overarching goal is to improve the reproducibility of neuroimaging science and extend the impact of research funding through the implementation of a Findable, Accessible, Interoperable and Reusable (FAIR) technology stack that supports a comprehensive set of data management, analysis, and utilization frameworks for both basic research and clinical activities. ReproNim encompasses three technology development efforts and a training mission:

1) Resource Discovery: development of new search and discovery tools to create a sophisticated, comprehensive and dynamic search environment for working with distributed neuroimaging data, tools, workflows and execution environments.

2) Data Modelling & Interoperability: To provide end-users a set of commonly used, reproducible workflows with integrated results and provenance tracking that are easy to use.

3) Reusable Execution Environments: To enable reproducible computation through full automation and tracking of computing environments.

4) Training: To provide the brain imaging community with online training materials based on ReproNim concepts and software developed.

Together, these technologies support a vision of a neuroimaging research landscape where the generation of knowledge is accomplished in a FAIR fashion (in terms of data, analysis and computation) coupled with the ability to reuse and extend these studies by others in the community.