QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

HOME  |   SEARCH  |   ARCHIVE  |   SUBSCRIBE  |   CONTACT  |   HELP

The Journal of Neuroscience, September 15, 2004, 24(37):8075-8083; doi:10.1523/JNEUROSCI.1509-04.2004

This Article Full Text Full Text (PDF) Submit an eLetter Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (31) Citing Articles via Google Scholar Google Scholar Articles by Netoff, T. I. Articles by White, J. A. Search for Related Content PubMed PubMed Citation Articles by Netoff, T. I. Articles by White, J. A.

 Previous Article  |  Next Article 

Neurobiology of Disease
Epilepsy in Small-World Networks

Theoden I. Netoff,^1,3 Robert Clewley,^2,3 Scott Arno,^1,3 Tara Keck,^1,3 and John A. White^1,3

¹Department of Biomedical Engineering, ²Department of Mathematics and ³Center for BioDynamics and Center for Memory and Brain, Boston University, Boston, Massachusetts 02215

In hippocampal slice models of epilepsy, two behaviors are seen: short bursts of electrical activity lasting 100 msec and seizure-like electrical activity lasting seconds. The bursts originate from the CA3 region, where there is a high degree of recurrent excitatory connections. Seizures originate from the CA1, where there are fewer recurrent connections. In attempting to explain this behavior, we simulated model networks of excitatory neurons using several types of model neurons. The model neurons were connected in a ring containing predominantly local connections and some long-distance random connections, resulting in a small-world network connectivity pattern. By changing parameters such as the synaptic strengths, number of synapses per neuron, proportion of local versus long-distance connections, we induced "normal," "seizing," and "bursting" behaviors. Based on these simulations, we made a simple mathematical description of these networks under well-defined assumptions. This mathematical description explains how specific changes in the topology or synaptic strength in the model cause transitions from normal to seizing and then to bursting. These behaviors appear to be general properties of excitatory networks.

Key words: epilepsy; networks; small-world networks; seizures; computational modeling; interictal burst

---

Received Dec 18, 2003; revised July 29, 2004; accepted July 30, 2004.

This article has been cited by other articles:

				A. J. Trevelyan, T. Baldeweg, W. van Drongelen, R. Yuste, and M. Whittington The Source of Afterdischarge Activity in Neocortical Tonic Clonic Epilepsy J. Neurosci., December 5, 2007; 27(49): 13513 - 13519. [Abstract] [Full Text] [PDF]

				J. Dyhrfjeld-Johnsen, V. Santhakumar, R. J. Morgan, R. Huerta, L. Tsimring, and I. Soltesz Topological Determinants of Epileptogenesis in Large-Scale Structural and Functional Models of the Dentate Gyrus Derived From Experimental Data J Neurophysiol, February 1, 2007; 97(2): 1566 - 1587. [Abstract] [Full Text] [PDF]

				J. Shao, T.-H. Tsao, and R. Butera Bursting without slow kinetics: a role for a small world? Neural Comput., September 1, 2006; 18(9): 2029 - 2035. [Abstract] [Full Text] [PDF]

				C. Foldy, J. Dyhrfjeld-Johnsen, and I. Soltesz Structure of cortical microcircuit theory J. Physiol., January 1, 2005; 562(1): 47 - 54. [Abstract] [Full Text] [PDF]

Home  |   Search  |   Archive  |   Subscribe  |   Contact  |   Help