Project Summary The firing of action potentials in the principal neurons (collectively, MTCs) of the olfactory bulb (OB) is modulated by the intrinsic dynamics of OB circuitry. These dynamics, arising from an interplay between the subthreshold dynamics of MTCs and the synaptic dynamics of the OB external plexiform layer, generate coordinated local field potential oscillations at gamma frequencies (roughly 40-80 Hz in vivo; 20-55 Hz in vitro) and phase-constrain the timing of MTC action potentials with respect to these oscillations. While these dynamics are known to be important for olfactory performance, it remains unclear which aspects of this dynamical regulation of spike timing are important for odor encoding and OB function. In part, this has been due to the limited capacity to control the intensity and timecourse of odor delivery on fine spatial and temporal scales, along with the limited capacity of electrical stimulation in slice explants to deliver stimuli with odor-like spatiotemporal properties. This project proposes to deliver “odor-like” stimuli to OB slices using spatiotemporally patterned optogenetic stimulation, and to record MTC ensemble responses (spikes and local field potentials) using a 120-channel planar microelectrode array. This strategy enables precise control of both the afferent stimulus and the neuromodulatory state of the circuit. By varying the spatiotemporal properties of these afferent stimuli in accordance with explicit models of “odor quality”, “concentration”, and “sniffing”, their effects on the regulation of spike timing among coordinated ensembles of activated MTCs can be determined. This system provides a remarkable opportunity to elucidate the underlying metrics and mechanisms of sensory encoding in the olfactory system. The project PI is experienced in cellular and molecular neuroscience, but is new to systems neuroscience, optogenetics, electrophysiology, and the analysis of neuronal ensemble activity. His PhD research will incorporate each of these techniques, including the design and vetting of data analysis workflows for these complex datasets. Cornell University and his research mentor are providing all necessary research resources and opportunities for technical training and intellectual engagement.