The vast complexity of the brain makes it one of the most interesting and difficult topics in science today. Many hypotheses about the brain can only be tested by constructing a physiological model of comparable complexity. This, in turn, relies on experiments that yield detailed information about the substrate of the brain—intrinsic cell properties, circuit connectivity, and synapse properties. These two aspects of neuroscience—modelling and experimentation—form a feedback loop that moves us iteratively toward better models: experimental output drives new models, and model output guides the design of new experiments. I am interested in the use and development high-throughput methods to characterize synapse properties such as connectivity, strength, kinetics and short term plasticity, with emphasis on generating the data we need to constrain circuit models. Ultimately, collecting this data will require a combination of techniques including parallel patch-clamp recordings, photostimulation mapping, tracer injections, and a variety of genetic tools.

Expertise

• Systems neuroscience


• Patch electrophysiology and optophysiology


• Physiological circuit modelling

Research Programs

• Structured Science


• Research Science -- Cell Types