Our goal is to understand the organizational principles that underlie information processing in neural circuits.

We apply and develop 'functional connectomics' as a platform to discover the relationship between circuit structure and function in the Drosophila and rodent brain.

Our work is focused on a few key questions:

--What rules determine network connectivity? How are these rules enforced during development?

--How do local networks process information and how does this relate to long-range processing?

--What network motifs are conserved and what differentiates brains and brain regions?

--What are the fundamental constraints on network behavior?

We primarily use large-scale EM and in vivo multi-photon calcium imaging to examine the structure and function of neurons and networks. Serial section EM provides us with detailed anatomical information about neurons and their connections. We can identify excitatory and inhibitory neurons and synapses, discover connectivity motifs, and analyze the organization of synaptic connections. The other key component of our approach is physiology – either optical imaging of activity sensors or electrophysiology. Ideally, the same cells are subjected to in vivo physiological recording and connectivity analysis. In this way we can infer how patterns of connectivity shape neuronal computations.

Additionally, we use genetic tools for labeling and manipulation; and modeling to explore the implications of our data and generate testable theories. Finally, we are devising approaches that will allow us to use behavior to bridge our understanding of circuit structure and network computation. By working across these modes of inquiry we aim to uncover the fundamental building blocks of functional networks.