Vivek Jayaraman is interested in understanding how sensory and motor information is represented, integrated, and transformed by ensembles of neurons in the brain to enable appropriate actions. His lab uses a combination of experimental and computational techniques to explore sensorimotor processing in the central brain of Drosophila. Their goal is to establish causal links between computation in such circuits and the insect's behavioral decisions.
Visual Learning in Head-Fixed Drosophila
Many animals display the ability to flexibly adjust their behavior on the basis of past experience. A fundamental question in systems neuroscience is how sensory information is adaptively associated with actions. My lab is tackling this broad question in the genetic model organism Drosophila melanogaster. In recent years, we have developed techniques to monitor the activity of genetically identified neural populations using two-photon calcium imaging and electrophysiology in tethered, behaving flies in a virtual reality arena (Seelig et al., Nature Methods, 2010). We are now developing various behavioral paradigms that will allow us to explore adaptive sensorimotor integration under such conditions. Flies have been shown to perform several complex behaviors, including visual pattern learning (Liu et al., Nature, 2006) and place learning (Ofstad et al., Nature, 2011). This project will involve working with postdocs in the lab to train tethered flies to associate visual stimuli with rewards and punishments in a "closed-loop" virtual reality arena. The goals are to understand what aspects of the behavioral conditions and task best predict robust learning performance and to analyze data to identify features of the stimuli and actions that are being learned by trained flies. Depending on how successfully the flies learn the task, students may have additional opportunities to use optogenetics to explore neural substrates involved in this behavior.
This project would be best suited to someone interested in and, ideally, with some experience in designing, performing, and analyzing quantitative behavior experiments. Experience working with flies is not essential but would be a bonus. Being comfortable with MATLAB and instrumentation (i.e., mechanical, electrical, optical) would also be pluses.
Identifying Network Motifs Inside the Drosophila Central Brain
Drosophila's small brain is powerful enough to allow it to perform many interesting behaviors. My lab is trying to identify neural algorithms used by its brain to perform adaptive visual behaviors, such as visual pattern learning and place learning. We would like to know how a particular brain region, called the central complex, which is implicated in many of these behaviors, dynamically integrates visual and motor information to allow the fly to select actions. We would like to map out the functional structure of the central complex network. We use genetic tools developed here at Janelia and elsewhere that provide us with cell-type–specific access to different neuron types in the region, and we perform experiments that test for functional connectivity between neurons by combining optogenetics and two-photon imaging. The project will use these techniques in isolated brains to help us identify and map interesting and important neural pathways within this brain region.
The ideal candidate for this project would be someone with "good hands" and previous experience with imaging. Experience with electrophysiology would be a major plus, as would working with flies and performing insect dissections.