Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2013, Article ID 182145, 10 pages
Research Article

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

1Department of Pediatrics, The University of Chicago, Chicago, IL 60637, USA
2Computation Institute, The University of Chicago and Argonne National Laboratories, Argonne, IL 60439, USA
3Mathematics and Computer Science Division, Argonne National Laboratories, IL 60439, USA
4Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
5Committee on Computational Neuroscience, The University of Chicago, Chicago, IL 60637, USA

Received 22 August 2013; Accepted 3 November 2013

Academic Editor: Qingshan Liu

Copyright © 2013 Lorenzo L. Pesce et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.