A Computational Facility for Neuroimaging Research

Duke University, Durham NC

Investigators

Abstract

[unreadable] DESCRIPTION (provided by applicant): Neuroimaging research using magnetic resonance imaging, magnetic resonance spectroscopy, magnetic resonance microscopy, and dense array electrical recording involves the acquisition of very large data structures that then must be transformed through a series of compute-intensive post-processing tasks into meaningful information. This project is jointly submitted by NIH-supported investigators at Duke University and the University of North Carolina who primarily use neuroimaging methods. The investigators are representative of four interdisciplinary centers that support neuroimaging research at these institutions: (1) The Duke-UNC Brain Imaging and Analysis Center (jointly funded by both universities), (2) the Center for In- Vivo Microscopy (a NIH National Research Resource Center), (3) the Center for Advanced Magnetic Resonance Development, and (4) the Center for Cognitive Neuroscience. The directors of these centers and their collaborating scientists have found that the sheer volume of data resulting from improved acquisition methods and improved hardware has made it increasingly difficult to fully analyze data in a timely manner. Some important computational processes are unfeasible, such as the creation of 3D chemical shift images. Other routine processes such as 3D spatial normalization of a time series of image volumes require many hours of processing on our single processor workstations. We are requesting funds to purchase a high performance multiprocessor computer to facilitate these and other processing requirements. [unreadable] [unreadable] Our proposal trades heavily upon the recent installation at Duke University of an IBM Storage Area Network (SAN) with capacious multi-terabyte storage capacity for the use of its high technology centers. The proposed multiprocessor system would be connected directly to this SAN via a fiber channel adapter. Thus, the benefits of the SAN to our group of investigators would be fully realized by the proposed computational resource. Our proposal also benefits from the close collaboration that already exists among the included centers in scientific endeavors, in the development of analytical software, and in the management of large research instruments.