Supervisor: Mark Humphries
School of Psychology

Description:

The wiring between neurons, the connectome, defines their activity. So in order to understand the activity of neurons we record from, we want to know the wiring between them. But current technology does not allow the simultaneous recording and tracing of the connections between neurons. To solve this problem, this project will develop computational techniques to accurately infer wiring between neurons from the next generation of imaging techniques that directly record neuron voltages. The project will combine development of algorithms, simulations of neural circuits as test-beds, and analysis of real imaging data from neural populations.

Requirements:

• Matlab and/or Python programming experience. A strong quantitative background in e.g. physics, mathematics, computer science or engineering

Reading:

• Bruno, A., Frost, W. F., & Humphries, M. D. (2015) Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program. Neuron, 86, 304-318.
• Timme, M & Casadiego, J.(2014) Revealing networks from dynamics: an introduction. Journal of Physics A: Mathematical and Theoretical, 47, 343001

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