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Imaging research requires approaches that record neural signals across relatively large swaths of cortical and/or subcortical tissue to unravel large-scale computational principles of brain function. Technological advances now allow brain imaging to be undertaken at different spatial scales, spanning from the resolution of a single cell (tens of micrometers) to populations of interconnected neurons (millimeters).

At the cellular level, research on two-photon Calcium imaging at UMD, supported by one of the ten inaugural NIH BRAIN awards aimed at seeding large scale interdisciplinary brain research, investigates mechanisms of auditory processing and plasticity in primary auditory cortex. Novel cell level imaging technologies, including light sheet technologies developed by collaborators from the NIH to rapidly image small model organisms and breakthrough non-invasive imaging technologies developed by NIST, will be housed and will be broadly accessible in the new Imaging Development Core facility housed in the Physical Sciences Complex.

A major effort of population level imaging research at UMD focuses on research with humans at the Maryland Neuroimaging Center (MNC), and employs both magnetoencephalography (MEG) and magnetic resonance imaging (MRI) techniques. Whereas MEG allows the investigation of the human brain with excellent temporal resolution (millisecond level) while functional MRI offers excellent spatial resolutions (millimeter scale).

MRI research at UMD includes developmental work with children, language acquisition and expertise, cognition and emotion interactions, memory, and social neuroscience. Whereas the research is often conducted from a basic science standpoint, it is highly translational. For example, research on language addresses learning to read and dyslexia; research on the social brain is directly tied to autism; research on emotion is related to anxiety and depression. Research at the MNC thus intersects with multiple BBI themes, including Mental Health, Learning/Plasticity, and Sensation, Perception, and Communication.

Both MEG and MRI research employ large, multi-participant datasets that involve complex analytical processing pipelines. Joining the strengths of imaging research and both Big Data and Complex Systems that exist on campus would transform the landscape of imaging research at UMD. Research studying hundreds of participants, imaged with several modalities, much like in the Human Connectome Project, previously not viable at the MNC, would become possible and propel UMD to the forefront of human imaging centers.

Integration of imaging research with techniques from Virtual/Augmented Reality would allow the study of hitherto unexplored mental processes. These would include, for example, studies of virtual (but realistic) social interactions that have largely prevented the study of these functions in the highly non naturalistic and constrained environments of MEG and MRI.