Research

The heart of our approach to research is to triangulate on our questions of interest using concerted electrophysiological, behavioral, and computational methods. That is, our electrophysiological studies are designed to help us understand the circuitry enabling natural behaviors, and our theoretical modeling strives to understand how such physiological systems can underlie both simple behavioral capabilities as well as complex behavior in natural contexts. This also underlies our interest in designing neuromorphic algorithms for artificial systems.

Why do we focus on the olfactory system? Perhaps the main reason is because the olfactory system is a microcosm of the most interesting questions in neuroscience. The olfactory bulb, in particular, is a morphologically isolated telencephalic cortical structure. It receives direct input from primary sensory neurons, such that sensory input can be studied at a reduced, mechanistic, physical level comparable to studying the retina or the cochlear nucleus. It transforms this sensory input across a single principal synapse (with lots of interneurons contributing to this transformation), and exports this transformed sensory information to several other regions of the brain. However, the olfactory bulb also receives rich top-down neuromodulatory inputs, and is affected by complex physiological state variables (such as stress and hunger) and contextual information (via the anterior olfactory nucleus), in ways comparable to much “higher” centers in other sensory systems. That is, the construction of meaningful odor representations occurs within a much more compact neural network than, for example, in the visual system, where the construction of meaningful visual images requires a great deal more computation across multiple regions of the brain. Essentially, we can study and interrelate neuronal biophysics and meaningful, quasi-cognitive representations within the same, reasonably well-described, experimentally tractable neuronal network.

[box]Lewis Thomas, in his essay On Smell, wrote: “I should think we might fairly gauge the future of biological science, centuries ahead, by estimating the time it will take to reach a complete, comprehensive understanding of odor. It may not seem a profound enough problem to dominate all the life sciences, but it contains, piece by piece, all the mysteries.”[/box]

Ascending and contextual control of functional circuitry

This is one of the core projects and interests of the lab: how do ascending inputs from the rest of the brain affect the operations of early olfactory circuitry? In particular: How do neuromodulatory chemicals, released into the olfactory system, alter the functional circuitry of the system? How does contextual […]

Network dynamics in the olfactory system

We study the emergent dynamics and encoding properties of olfactory bulb circuitry using live tissue slices laid down upon 60- and 120-channel planar multielectrode arrays (MEAs), and also through the analysis of in vivo data from olfactory bulb and piriform cortex. Briefly, olfactory bulb circuitry is intrinsically resonant, and imposes […]

Gene expression profiles induced by odor learning

Understanding learning and memory is one of the great challenges of neuroscience, and olfactory learning and memory is only a small corner of a field dominated by work in hippocampus, amygdala, cerebellum, and prefrontal cortex. What we seek to contribute to this larger field is a rich and effective way […]

Computational modeling of neurons and networks

Computational modeling of neural circuits is increasingly essential to systems neuroscience, as the ability of researchers to construct sound working hypotheses on an ad hoc basis is becoming increasingly challenging as the complexity and diversity of datasets increase. Models serve as proofs of concept, tests of sufficiency, and as quantitative […]

Neuromorphic algorithms

A key translational goal in the lab is to extract “algorithms” from the biological networks we study, study them computationally, and ultimately embed them into neuromorphic hardware. The overall goal of this neuromorphic computing strategy is to enable us to build artificial systems with capabilities approaching those of their biological […]

Tool development

We build many of our own software tools for simulation and analysis — sometimes from scratch, but also by integrating and adapting tools and approaches designed by others and released under open source licenses. We also build some of our own electronics hardware for customized behavioral testing. Software tools, designs, […]