Dr. Christian Fink (Department of Physics and Astronomy, Neuroscience Program)

Epilepsy affects roughly 1% of the world's population [1], with approximately 10% of these people being effectively treated by surgical removal of an epileptic focus [2]. This approach is a method of last resort when anti-epileptic drugs are ineffective, since removing a portion of a patient’s brain may have undesirable side effects. In this project we will theoretically investigate the feasibility of preventing seizure propagation by severing a few individual connections from an epileptic focus, rather than removing the focus in its entirety.

We will explore this idea by running simulations of epileptic seizures using a recently developed theoretical model of seizure dynamics [3], as well as the connectivity map of the macaque brain [4]. The question we seek to answer is: how can we identify which neural connection(s) should be removed in order to best inhibit seizure propagation? We will use tools from dynamical systems theory and network theory to formulate quantitative measures to answer this question.

This project will therefore involve developing a computational model of the macaque brain in order to model the propagation of epileptic seizures. After learning about fundamental techniques in computational neuroscience, students will write code in Python to run these large-scale simulations. Overall, the project is appropriate for any student with experience in differential equations and computer programming, and who has an interest in computational neuroscience.

REFERENCES

[1] Thurman et. al. “Standards for epidemiologic students and surveillance of epilepsy,” Epilepsia, 2011.

[2] Surgery for Epilepsy, NIH Consensus Statement, 1990 Mar 19- 21; 8(2):1-20.

[3] Jirsa et. al. “On the nature of seizure dynamics,” BRAIN, 2014.

[4] Modha and Singh. “Network architecture of the long-distance pathways in the macaque brain,” PNAS, 2010.