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Oxygen and seizure dynamics: II. Computational modeling.

ABSTRACT: Electrophysiological recordings show intense neuronal firing during epileptic seizures leading to enhanced energy consumption. However, the relationship between oxygen metabolism and seizure patterns has not been well studied. Recent studies have developed fast and quantitative techniques to measure oxygen microdomain concentration during seizure events. In this article, we develop a biophysical model that accounts for these experimental observations. The model is an extension of the Hodgkin-Huxley formalism and includes the neuronal microenvironment dynamics of sodium, potassium, and oxygen concentrations. Our model accounts for metabolic energy consumption during and following seizure events. We can further account for the experimental observation that hypoxia can induce seizures, with seizures occurring only within a narrow range of tissue oxygen pressure. We also reproduce the interplay between excitatory and inhibitory neurons seen in experiments, accounting for the different oxygen levels observed during seizures in excitatory vs. inhibitory cell layers. Our findings offer a more comprehensive understanding of the complex interrelationship among seizures, ion dynamics, and energy metabolism.

SUBMITTER: Wei Y

PROVIDER: S-EPMC4064403 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Oxygen and seizure dynamics: II. Computational modeling.

Wei Yina Y Ullah Ghanim G Ingram Justin J Schiff Steven J SJ

Journal of neurophysiology 20140326 2

Electrophysiological recordings show intense neuronal firing during epileptic seizures leading to enhanced energy consumption. However, the relationship between oxygen metabolism and seizure patterns has not been well studied. Recent studies have developed fast and quantitative techniques to measure oxygen microdomain concentration during seizure events. In this article, we develop a biophysical model that accounts for these experimental observations. The model is an extension of the Hodgkin-Hux ...[more]

PMID: 24671540

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Project description:Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion that slow variations of global excitability, due to exogenous fluctuations from extracellular environment, and gap junction communication push the system into paroxysmal regimes. We discuss potential mechanisms underlying such machinery and the relevance of our approach, supporting previous detailed modeling studies and reflecting on the limitations of our methodology.

Project description:Reactive oxygen species (ROS) function as critical mediators in a broad range of cellular signaling processes. The mitochondrial electron transport chain is one of the major contributors to ROS formation in most cells. Increasing evidence indicates that the respiratory Complex II (CII) can be the predominant ROS generator under certain conditions. A computational, mechanistic model of electron transfer and ROS formation in CII was developed in the present study to facilitate quantitative analysis of mitochondrial ROS production. The model was calibrated by fitting the computer simulated results to experimental data obtained on submitochondrial particles (SMP) prepared from bovine and rat heart mitochondria upon inhibition of the ubiquinone (Q)-binding site by atpenin A5 (AA5) and Complex III by myxothiazol, respectively. The model predicts that only reduced flavin adenine dinucleotide (FADH2) in the unoccupied dicarboxylate state and flavin semiquinone radical (FADH•) feature the experimentally observed bell-shaped dependence of the rate of ROS production on the succinate concentration upon inhibition of respiratory Complex III (CIII) or Q-binding site of CII, i.e., suppression of succinate-Q reductase (SQR) activity. The other redox centers of CII such as Fe-S clusters and Q-binding site have a hyperbolic dependence of ROS formation on the succinate concentration with very small maximal rate under any condition and cannot be considered as substantial ROS generators in CII. Computer simulation results show that CII disintegration (which results in dissociation of the hydrophilic SDHA/SDHB subunits from the inner membrane to the mitochondrial matrix) causes crucial changes in the kinetics of ROS production by CII that are qualitatively and quantitatively close to changes in the kinetics of ROS production by assembled CII upon inhibition of CIII or Q-binding site of CII. Thus, the main conclusions from the present computational modeling study are the following: (i) the impairment of the SQR activity of CII resulting from inhibition of CIII or Q-binding site of CII and (ii) CII disintegration causes a transition in the succinate-dependence of ROS production from a small-amplitude sigmoid (hyperbolic) shape, determined by Q-binding site or [3Fe-4S] cluster to a high-amplitude bell-shaped kinetics with a shift to small subsaturated concentrations of succinate, determined by the flavin site.

Dataset Information

Oxygen and seizure dynamics: II. Computational modeling.

Publications

Oxygen and seizure dynamics: II. Computational modeling.

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