TY - JOUR
T1 - Epilepsy in small-world networks
AU - Netoff, Theoden I.
AU - Clewley, Robert
AU - Arno, Scott
AU - Keck, Tara
AU - White, John A.
PY - 2004/9/15
Y1 - 2004/9/15
N2 - 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.
AB - 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.
KW - Computational modeling
KW - Epilepsy
KW - Interictal burst
KW - Networks
KW - Seizures
KW - Small-world networks
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U2 - 10.1523/JNEUROSCI.1509-04.2004
DO - 10.1523/JNEUROSCI.1509-04.2004
M3 - Article
C2 - 15371508
AN - SCOPUS:4644317180
SN - 0270-6474
VL - 24
SP - 8075
EP - 8083
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 37
ER -