A number of recent studies suggest that cognitive processes rely on spatial and temporal patterns of activity in extended neural networks. Optical imaging techniques can provide information on a microscopic level about the individual and collective behavior of cells involved in these processes. We propose to develop an advanced image probe and digital acquisition system designed for high performance functional neural imaging using intrinsic light scattering signals. The first goal of the project is to improve the image probe design for high sensitivity to small and rapid changes in light scattering. Two methods of reflectance mode illumination will be explored for fluorescence and polarized light measurements. The system will incorporate an electronically tunable filter to illuminate tissue with specific wavelengths for spectroscopic measurements, and an intensified detector for dynamic fluorescence measurements. The second goal is to implement hardware and software improvements to the data acquisition system. Application performance requirements and the need to integrate of a number of data modalities require that we develop custom data acquisition hardware; the proposed system will control CCD camera circuitry, and capture, process and archive 2000 frames per second, with 256 channels of concurrent electrophysiological data. We will integrate this hardware into inexpensive, multiple processor. Pentium computer systems, designed for distributing tasks across multiple processors. The third goal for the project is to apply the device to investigate the nature and origin of light scattering changes associated with neural activation. Our preliminary studies in the hippocampus and medulla have demonstrated several different optical changes associated with neural activation, including fast light scattering changes concurrent with neural swelling and electrical transmission, and slower changes in light absorbance associated with hemodynamic coupling to metabolic demand. We will examine the spectral nature of the optical signals, characterize the timing of at least four components that we have identified, and employ physical and physiological manipulations to identify and characterize underlying mechanisms.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Diagnostic Imaging Study Section (DMG)
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Grabb, Margaret C
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Washington State University
Veterinary Sciences
Schools of Veterinary Medicine
United States
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Krueger, James M; Huang, Yanhua H; Rector, David M et al. (2013) Sleep: a synchrony of cell activity-driven small network states. Eur J Neurosci 38:2199-209
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