Literature DB >> 9114229

Dynamic interactions determine partial thalamic quiescence in a computer network model of spike-and-wave seizures.

W W Lytton1, D Contreras, A Destexhe, M Steriade.   

Abstract

In vivo intracellular recording from cat thalamus and cortex was performed during spontaneous spike-wave seizures characterized by synchronously firing cortical neurons correlated with the electroencephalogram. During these seizures, thalamic reticular (RE) neurons discharged with long spike bursts riding on a depolarization, whereas thalamocortical (TC) neurons were either entrained into the seizures (40%) or were quiescent (60%). During quiescence, TC neurons showed phasic inhibitory postsynaptic potentials (IPSPs) that coincided with paroxysmal depolarizing shifts in the simultaneously recorded cortical neuron. Computer simulations of a reciprocally connected TC-RE pair showed two major modes of TC-RE interaction. In one mode, a mutual oscillation involved direct TC neuron excitation of the RE neuron leading to a burst that fed back an IPSP into the TC neuron, producing a low-threshold spike. In the other, quiescent mode, the TC neuron was subject to stronger coalescing IPSPs. Simulated cortical stimulation could trigger a transition between the two modes. This transition could go in either direction and was dependent on the precise timing of the input. The transition did not always follow the stimulation immediately. A larger, multicolumnar simulation was set up to assess the role of the TC-RE pair in the context of extensive divergence and convergence. The amount of TC neuron spiking generally correlated with the strength of total inhibitory input, but large variations in the amount of spiking could be seen. Evidence for mutual oscillation could be demonstrated by comparing TC neuron firing with that in reciprocally connected RE neurons. An additional mechanism for TC neuron quiescence was assessed with the use of a cooperative model of gamma-aminobutyric acid-B (GABA(B))-mediated responses. With this model, RE neurons receiving repeated strong excitatory input produced TC neuron quiescence due to burst-duration-associated augmentation of GABA(B) current. We predict the existence of spatial inhomogeneity in apparently generalized spike-wave seizures, involving a center-surround pattern. In the center, intense cortical and RE neuron activity would be associated with TC neuron quiescence. In the surround, less intense hyperpolarization of TC neurons would allow low-threshold spikes to occur. This surround, an "epileptic penumbra," would be the forefront of the expanding epileptic wave during the process of initial seizure generalization. Therapeutically, we would then predict that agents that reduce TC neuron activity would have a greater effect on seizure onset than on ongoing spike-wave seizures or other thalamic oscillations.

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Year:  1997        PMID: 9114229     DOI: 10.1152/jn.1997.77.4.1679

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  12 in total

1.  The GABAergic reticular nucleus: a preferential target of corticothalamic projections.

Authors:  M Steriade
Journal:  Proc Natl Acad Sci U S A       Date:  2001-03-20       Impact factor: 11.205

2.  Feedback inhibition and throughput properties of an integrate-and-fire-or-burst network model of retinogeniculate transmission.

Authors:  Marco A Huertas; Jeffrey R Groff; Gregory D Smith
Journal:  J Comput Neurosci       Date:  2005-10       Impact factor: 1.621

3.  Seizure-like afterdischarges simulated in a model neuron.

Authors:  H Kager; W J Wadman; G G Somjen
Journal:  J Comput Neurosci       Date:  2007-04       Impact factor: 1.621

4.  Spike-and-wave oscillations based on the properties of GABAB receptors.

Authors:  A Destexhe
Journal:  J Neurosci       Date:  1998-11-01       Impact factor: 6.167

5.  Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON.

Authors:  William W Lytton; Alexandra H Seidenstein; Salvador Dura-Bernal; Robert A McDougal; Felix Schürmann; Michael L Hines
Journal:  Neural Comput       Date:  2016-08-24       Impact factor: 2.026

6.  Neural field model of seizure-like activity in isolated cortex.

Authors:  X Zhao; P A Robinson
Journal:  J Comput Neurosci       Date:  2017-04-07       Impact factor: 1.621

7.  Generalized seizures in a neural field model with bursting dynamics.

Authors:  X Zhao; P A Robinson
Journal:  J Comput Neurosci       Date:  2015-08-19       Impact factor: 1.621

8.  Influence of norepinephrine on somatosensory neuronal responses in the rat thalamus: a combined modeling and in vivo multi-channel, multi-neuron recording study.

Authors:  Karen A Moxon; David M Devilbiss; John K Chapin; Barry D Waterhouse
Journal:  Brain Res       Date:  2007-02-08       Impact factor: 3.252

9.  Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach.

Authors:  Ardalan Aarabi; Bin He
Journal:  Clin Neurophysiol       Date:  2013-11-28       Impact factor: 3.708

Review 10.  Interactions between membrane conductances underlying thalamocortical slow-wave oscillations.

Authors:  A Destexhe; T J Sejnowski
Journal:  Physiol Rev       Date:  2003-10       Impact factor: 37.312

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