Excitation spreads through a neural network via positive feedback connections between the neurons. The amount of positive feedback in the network is determined by the number and strength of these excitatory synaptic connections, as well as the degree to which these connections are masked by pre and postsynaptic inhibition. The proposed research will test the hypothesis that the amount of positive feedback in a neural network is correlated with the probability that the network will initiate a seizure. To test this hypothesis, we have developed two noninvasive methods. The first method quantifies the amount of positive feedback based on the temporal pattern of interictal spikes on the electroencephalogram (EEG). The second method modifies the amount of positive feedback by selective long-term depression (LTD) of the strength of recurrent excitatory synapses. Using a well-characterized rat kainate model of chronic epilepsy, the amount of positive feedback measured from the EEG will be correlated with seizure probability during epileptogenesis. As an additional test of the hypothesis, the amount of positive feedback in the epileptic networks will be decreased by LTD of the recurrent synapses, and the seizure probability will be compared to EEG measures of positive feedback before and after LTD. These experiments may provide two important tools for treating epilepsy. The first is the ability to estimate seizure probability from the pattern of interictal spike activity on the EEG, which would make possible the prospective evaluation of the risk of seizures and the efficacy of anticonvulsant therapy. The second is the induction of long-term decreases in seizure probability by synapse-specific LTD of recurrent excitatory synapses in the epileptic network, which may prove to be a very useful anticonvulsant strategy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS034360-08
Application #
6780878
Study Section
Special Emphasis Panel (ZRG1-MDCN-4 (02))
Program Officer
Fureman, Brandy E
Project Start
1996-12-01
Project End
2005-07-31
Budget Start
2004-08-01
Budget End
2005-07-31
Support Year
8
Fiscal Year
2004
Total Cost
$368,619
Indirect Cost
Name
University of Colorado Denver
Department
Neurology
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045
Staley, Kevin (2015) Molecular mechanisms of epilepsy. Nat Neurosci 18:367-72
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Staley, Kevin J; White, Andrew; Dudek, F Edward (2011) Interictal spikes: harbingers or causes of epilepsy? Neurosci Lett 497:247-50
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Dulla, Chris G; Frenguelli, Bruno G; Staley, Kevin J et al. (2009) Intracellular acidification causes adenosine release during states of hyperexcitability in the hippocampus. J Neurophysiol 102:1984-93
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Swiercz, Waldemar; Cios, Krzysztof; Hellier, Jennifer et al. (2007) Effects of synaptic depression and recovery on synchronous network activity. J Clin Neurophysiol 24:165-74

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