@article{ISI:000237000300050,
 abstract = {The dependence of the rate of kindling on network properties, such as
the number of neurons, number of stored memories, and the number of
neurons used to store each memory, is studied through computer
simulations of an appropriate neural network model for kindling of focal
epilepsy. Simulations are performed for models of both chemical and
electrical kindling. Larger and more complex networks are found to take
longer time to kindle, as observed in experiments. The nature of the
dependence of the kindling rate on network properties is somewhat
different between the two types of kindling. A simple analysis of the
process of chemical kindling is presented, which provides a
semi-quantitative explanation of the behavior observed in our
simulations. This analysis also shows that our main conclusions about
the dependence of the kindling rate on the size and complexity of the
network are independent of some of the assumptions made in our modeling.
(c) 2005 Elsevier B.V. All rights reserved.},
 author = {Biswal, B and Niranjan, BR and Ullal, G and Dasgupta, C},
 doi = {10.1016/j.physa.2005.08.075},
 eissn = {1873-2119},
 issn = {0378-4371},
 journal = {PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS},
 month = {MAY 15},
 orcid-numbers = {Dasgupta, Chandan/0000-0002-0302-1881
Biswal, Bibhu/0000-0002-4821-760X},
 pages = {565-580},
 times-cited = {1},
 title = {Computational modeling of the dependence of kindling rate on network
properties},
 unique-id = {ISI:000237000300050},
 volume = {364},
 year = {2006}
}