We are constantly bombarded by the sights, sounds, and smells of the world around us. Many decisions we make are based on the specifics of these sensory stimuli. For example, the visual appeal of beautiful scenery may keep us climbing up a tough hiking trail, but traffic noise from a nearby highway may be loud enough for us to decide it's not worth the effort. In a more mundane situation, we may choose whether or not to eat a particular fruit based on its color, smell, and feel, with past experience and our state of hunger guiding how we weight the different factors.
A fundamental goal of systems neuroscience is to understand how the brain represents and processes such information to select an appropriate course of action. Our research focuses on this issue, as well as on the question of how neural circuits integrate information from different modalities. We would like to uncover links between such computations and adaptive decision-making. We believe that exploring such issues requires studying the activity of large populations of neurons in a behaving organism. Furthermore, validating any potential answers will require manipulating neural circuits in precise and well-controlled ways. A suitable model system to use is the fruit fly, Drosophila melanogaster, which has long been the organism of choice for behavioral genetics and comes with tools to fluorescently label, manipulate, and record the activity of genetically targeted neurons.
For the past few years we have been using both two-photon imaging and electrophysiology (sometimes simultaneously) to record from brain neurons in the intact adult fruit fly during active tethered behavior. For optical imaging, we use genetically encoded sensors (of, for example, calcium), including new indicators developed by Loren Looger's lab and the GENIE Project Team at Janelia. The advantage of such sensors is that the same genetically identified neurons can be targeted for imaging in fly after fly. With the combination of electrophysiological and optical methods to record from identified neural populations during walking and flight behavior, and with a variety of computational techniques, we are exploring the sensorimotor processing that underlies simple behaviors.
One of the first insights we gained from recording in the visual system during behavior was that even neurons early in the sensory pathway modify their tuning properties based on the motor state of the fly. That is, sensory coding has to be thought of as a dynamic, adaptive process that is modified depending on an animal’s behavioral situation.
Going forward, our lab is interested in two broad areas of research:
- Identification of neurons and circuits in the fly brain involved in multisensory integration: This effort involves using genetic, electrophysiological, and imaging techniques to establish functional connectivity and to map circuits of interest. Our particular obsession is an area of the insect brain, called the central complex, that is considered to be important for sensorimotor processing.
- Neural representation of sensory and motor information during behavior: We are using existing electrophysiological and optical methods, as well as some in development, to study sensorimotor computations in single neurons and ensembles of neurons during sensory-guided orientation in a virtual environment. Computational analysis and modeling are key components of this effort.
We collaborate with many other labs at Janelia. To combine high-throughput physiological recordings with fly behavior, we work with other groups at Janelia Farm, including Michael Reiser's lab, Gwyneth Card’s lab, the Instrumentation Design and Fabrication Group, the Applied Physics and Instrumentation Group, and the Scientific Computing Group. Much of the appeal of the fruit fly as a model organism lies in the many molecular tools being developed for it: expertise in this field is abundant at Janelia, and we benefit greatly from research in the labs of Gerry Rubin, Julie Simpson, and Alla Karpova, among others.
Establishing causal links between multimodal computations of neuronal ensembles and the fly's decision-making behavior is a long-term goal for our lab. Along the way, we hope to discover some general principles about sensory representations, motor control, neural computation, and the functional organization of small circuits in the fly brain.