Some of our recent work focuses on the early visual system, especially the retina, which we treat as a prototypical brain area. With this example in mind, we have studied the underlying factors driving four characteristic aspects of circuit organization in the brain: (a) The diversity of cell types, and the division of scarce resources between these types, (b) The conserved patterns of structural and functional layout of circuitry, (c) functional adaptation to changing conditions, (d) computation and communication by networks.  We propose that these structural and functional aspects of the organization of the early visual system can be understood as adaptations to efficiently process the information in natural scenes, subject to the metabolic, spatial, temporal and noise constraints inherent in biological computation. 

Ongoing experimental work in our lab uses a multi-electrode array to study adaptation of the retinal network to changes in stimulus statistics. 

Ongoing theoretical work explores: (1) perception of visual texture and natural scene statistics, (2) the circuits underlying visual perception of shape, (3) location coding and goal-directed navigation using populations of place cells in hippocampus and grid cells in entorhinal cortex, (4) the organization of the olfactory system.


The Retina.

(Ramon y Cajal, 1917)

Many of the most interesting functions and behaviors realized by the brain emerge from the collective activity of very large numbers of neurons of many functional types interacting in complex networks. The long-term goal of our lab is to establish the principles underlying the structural and functional organization of such circuits in the brain.  We hope to understand how large-scale behaviors can emerge from the interaction of many individual elements, what the constraints on neural circuit architecture are, and in what ways network functions can be impaired or improved by changes to the architecture.

Some of the theoretical effort in our lab applies techniques developed in neuroscience for data analysis, and for understanding and predicting network function, to analogous problems in the study of cell-signaling and regulatory networks.

Further details and publications are available at our lab website.