Area:
Computational Neuroscience
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High-probability grants
According to our matching algorithm, William Lytton is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
1993 — 1997 |
Lytton, William W |
R29Activity Code Description: Undocumented code - click on the grant title for more information. |
Thalamocortical Neuron Dynamics and Absence Epilepsy @ University of Wisconsin Madison
Understanding absence epilepsy will require understanding thalamic oscillations. The long term goal of this research is to use computer models to integrate known details of intrinsic neuronal properties and synaptic inputs to explain the genesis of the physiological and pathological slow rhythms of the thalamus. Intrinsic cell dynamics and synaptic connectivity interact in complex ways. Models of individual brain areas can provide a framework for integrating new physiological and pharmacological observations. A complement to animal models of epilepsy, computer models have the flexibility to extensively explore complex neuronal interactions that may suggest new pharmacological approaches. Slow oscillations in the thalamus, in both the 3 Hz range of absence epilepsy and slow-wave sleep in the 10 Hz range of sleep spindles, appear to involve low-threshold calcium spikes due to the T-type calcium channel (T channel). Ethosuximide, an anticonvulsant used for absence epilepsy, alters the kinetics of this channel. Computer modeling will be used 1) to determine the effects of passive properties and dendritic ion channels on the integrative properties of the neurons, 2) to relate neuronal firing patterns to the density and kinetics of ion channels, 3) to evaluate how physiological and pharmacological modulation of ion channels might alter the intrinsic oscillations of thalamocortical neurons, 4) to explore how repetitive intracellular stimulation or repetitive cortical synaptic input would affect oscillatory patterns, 5) to evaluate the contribution of intrinsic versus network properties in synchronizing slow oscillations in networks of simplified model neurons.
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