Parallel Supercomputing in Cognitive Brain Imaging Other Massive 3-D Dataspaces
Final rept. 1 Mar 1998-28 Feb 1999
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF PSYCHOLOGY
Pagination or Media Count:
This instrumentation grant supported the purchase of a small supercomputer for cognitive brain imaging and other large 3D dataspaces. The machine that was purchased was an SGI Silicon Graphics Origin 2000 parallel supercomputer with 14 CPUs, 7 gigabytes of main memory, 750 gigabytes of disk storage, and 5 terabytes of fast tape storage. In addition, 6 SGI Unix workstations were purchased for graphics display and processing, and 9 NTIntel workstations for local data analysis. The machines are networked in a 100mbit LAN. The area of computing in functional brain imaging and other massive 3-D dataspaces has extraordinary scientific, medical, and commercial potential. The potential application to DoD is the ability to measure brain function during the performance of high workload tasks, such as decision making, communication, and visualization. The measurement of the brain function provides a new way to measure cognitive workload, its limitations, and its efficiencies. These new methods have implications for the selection and training of personnel, and for the design of human computer interfaces. The research develops methods for measuring brain activation in the cortex during the performance of high level cognitive tasks and in dynamic decision making, in order to evaluate the cognitive workload imposed on an operator by various tasks, situations, interfaces, or instruments. The fMRI data are acquired at a high rate one brain slice about 5 mm thick consisting of 64x128 voxels approximately every 200 msec, in tasks taking a total of about 15 minutes each. The data are then subjected to signal processing and statistical modeling techniques, to discover the spatial and temporal patterns of cortical activation in a network of brain areas that underlie higher level cognition.
- Computer Systems