Kevin Bender, Professor

Closed (1) Fitting neuronal models to electrophysiological data.

Applications for Spring 2018 are now closed for this project.

Studying the biophysical properties of neurons, such as the different ion channel distributions and kinetics, can be done by fitting electrophysiological recordings from acute slices to neuronal compartmental models. In this process, a detailed neuron is modeled to a set of electrical circuits which describes it’s biophysical properties. These properties, also called model parameters, can be adjusted. We try to constrain the model’s parameters so it will behave like the neuron we recorded from. This process is done using an optimization algorithm that relies on training the model across thousands of permutations with respect to recorded physical stimulations from an actual neuron. We are investigating novel approaches to perform such an optimization. A further goal of this project is to adapt the optimization so that it can work on models that differ in physiology and research goals.

We are seeking undergraduate students who would like to take part in this project. We prefer EECS/CS students but being one of these majors is not required. Possible tasks include:
1. Using and modifying an optimization algorithms library written in Python language.
2. Running computations on Linux Clusters or GPUs.
3. Mathematical modeling and using Matlab to run analysis on large multi-dimensional datasets.
4. Porting code from Matlab to Python.
5. Applying machine learning algorithms to further increase the efficacy of the optimization algorithm.
6. Adapting and creating models in the NEURON language for neuronal cell modeling.

Day-to-day supervisor for this project: Roy Ben-Shalom, Post-Doc

Qualifications: Required Skills: Knowledge about Python language or any Object-oriented language is required. Knowledge about Matlab is preferred. Some knowledge about neurons or electrical circuit theory will be helpful but aren’t essential. Some knowledge about linear algebra or optimization theory is required. Understanding the dynamics of this project, which might contain relatively intense mathematical structure, is critical. Please keep this in mind.

Weekly Hours: 9-12 hrs

Off-Campus Research Site: Can work remotely or at:
UCSF Mission Bay
675 Nelson Rising Ln, San Francisco, CA 94158

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