Dynamic imaging of brain function: toward convergence with neural network simulation

Dynamic neuroimaging techniques allow measurement of neural population responses that reflect integrated activity of the underlying networks. A range of available methods provide spatial resolution and coverage from subcellular to whole head, and the ability to probe both fast and slow processes of neural activation. We have recently imaged intrinsic optical signals that are tightly coupled to the processes of neuronal activation. We observed slow optical responses corresponding to metabolic and/or hemodynamic processes. Other, faster response components closely tracked the dynamics of electro-physiological responses. We have employed fast optical signals to visualize expected spatial patterns of physiological activation of rat somato-sensory "barrel" cortex. Optical signals showed evidence of high frequency structure correlated with synchronous oscillatory activity observed in simultaneous electrical recordings. In order to account for interesting neural dynamic behavior, we are developing simulation tools that allow us to predict experimentally observable responses of neural populations. We will use these capabilities to generate testable hypotheses, and to optimize network models that account for observed dynamic responses.