node_title | node_title
Understand the input-output relationships in neural circuits
node_body | node_body
To understand a neural circuit, we need to know the information it receives, the transformation it applies to its inputs, and the information it outputs to the rest of the brain. We use a data-rich approach to elucidate circuit computations by systematically characterizing the representational properties of large numbers of boutons and neurons in the input and output layers of a neural circuit. Currently, we focus our efforts on the mouse primary visual cortex, where the tuning properties of inputs and outputs at depth can be characterized accurately only after the optical aberrations are corrected.
Summaries of our recent projects can be found here and here.