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Faculty Areas of Interest

Computational neuroscience

Computational neuroscience uses mathematics to understand the computational function of neural systems. It includes the study of neural components as computational elements; the building of mathematical models to describe neural systems and behavior; the exploration of theoretical principles that underlie biological function and the development of mathematical tools for the analysis of experimental data.


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Marc Binder

Input-Output Functions of Motoneurons

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Elizabeth Buffalo

Neural Mechanisms of Learning and Memory

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Daniel Cook

Physiological knowledge representation for multiscale biosimulation: Key to the virtual human

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Adrienne Fairhall

Neural information processing systems

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Eberhard Fetz

Cortical control of movement; neural modeling

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Sharona Gordon

Molecular basis of sensory transduction

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Greg Horwitz

Neural Basis of Color Perception

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Steve Perlmutter

Neural Control of Limb Movements

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Fred Rieke

Signal transduction in the visual system

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Eric Shea-Brown

Dynamics and computation in neural circuits

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William Zagotta

Molecular mechanisms of ion channel function