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Research ArticleNew Research, Disorders of the Nervous System

Adaptation and Inhibition Control Pathological Synchronization in a Model of Focal Epileptic Seizure

Anatoly Buchin, Cliff C. Kerr, Gilles Huberfeld, Richard Miles and Boris Gutkin
eNeuro 13 September 2018, 5 (5) ENEURO.0019-18.2018; https://doi.org/10.1523/ENEURO.0019-18.2018
Anatoly Buchin
1University of Washington, Department of Physiology and Biophysics (United States, Seattle), 1959 NE Pacific St, 98195
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Cliff C. Kerr
2University of Sydney, School of Physics (Australia, Sydney), Physics Rd, NSW 2006
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Gilles Huberfeld
3Sorbonne Université-UPMC, Pitié-Salpêtrière Hô, Neurophysiology Department (France, Paris), 47-83 Boulevard de l’Hôpital, 75013
4Institut national de la santé et de la recherche médicale Unit 1129 “Infantile Epilepsies and Brain Plasticity”, Paris Descartes University, Sorbonne Paris Cité University group, (France, Paris), 149 rue de Sévres 75015
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Richard Miles
5Brain and Spine Institute, Cortex and Epilepsie Group (France, Paris), 47 Boulevard Hôpital, 75013
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Boris Gutkin
6Paris Sciences & Lettres Research University, Laboratoire des Neurosciences Cognitives, Group for Neural Theory (France, Paris), 29, rue d'Ulm, 75005 France
7National Research University Higher School of Economics, Center for Cognition and Decision Making (Russia, Moscow), 20 Myasnitskaya, 109316
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  • Figure 1.
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    Figure 1.

    Structure of the population model. A, Scheme of interacting neural populations. E, I: excitatory and inhibitory populations; Embedded Image , Embedded Image : excitatory to excitatory and excitatory to inhibitory maximal conductances; Embedded Image , Embedded Image : inhibitory-to-inhibitory and inhibitory-to-excitatory maximal conductance; gAHP: adaptation conductance in the excitatory population; Embedded Image : synaptic noise input to the excitatory population; AHP, afterhyperpolarization current (Buchin and Chizhov, 2010b). B, LFP model: Embedded Image : contribution of a single excitatory cell; N: the number of neurons; Embedded Image : the average membrane potential in the excitatory population. C, D, Sigmoid approximation of potential-to-rate function (Johannesma, 1968) of the excitatory (C) and inhibitory population (D).

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    Figure 2.

    Neural mass model in various excitatory regimes. A, Activity of a neural population in the resting state. B, Seizure state. C, Disinhibited state. LFP is present together with intracellular recording from the pyramidal cell. Each plot contains the model scheme, power spectrum, and time traces provided by the excitatory population Embedded Image as well as experimental LFP. Red traces correspond to the model, blue traces to the experiment, and green traces to the intracellular recordings from the pyramidal cells. Model parameters for (A): Embedded Image = 1.5 mS/cm2; Embedded Image = 1 mS/cm2; Embedded Image = 2 mS/cm2; Embedded Image = 0.2 mS/cm2; Embedded Image = 1.6 mS/cm2; (B): Embedded Image = 1.5 mS/cm2; Embedded Image = 1 mS/cm2; Embedded Image = 0.5 mS/cm2; Embedded Image = 0.2 mS/cm2; Embedded Image = 1.6 mS/cm2; (C): Embedded Image = 1.5 mS/cm2; Embedded Image = 1 mS/cm2; Embedded Image = 0 mS/cm2; Embedded Image = 0.2 mS/cm2; Embedded Image = 1.6 mS/cm2.

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    Figure 3.

    Oscillatory frequencies of the population model. A–D, Oscillatory frequencies of the population model in the absence of the synaptic noise (Embedded Image = 0) as a function of the synaptic conductance, Embedded Image . E, Simultaneous intracellular recording from single pyramidal cell, LFP, and population model during transition from the resting state toward seizure. States marked by dotted lines. The green trace corresponds to the model’s resting state (Fig. 2A, Embedded Image ), red corresponds to early seizure (Fig. 2B, Embedded Image ), yellow corresponds to late seizure (Embedded Image ), and purple corresponds to the disinhibition state (Fig. 2C, Embedded Image ).

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    Figure 4.

    Analysis of the population model. A–D, Bifurcation diagrams for the variations of the maximal synaptic conductances, including recurrent excitation Embedded Image , excitation from excitatory to inhibitory population Embedded Image , inhibition from inhibitory to excitatory population Embedded Image , and the recurrent inhibition in the inhibitory population Embedded Image , respectively. E, F, Bifurcation diagrams for adaptation in the excitatory population Embedded Image and GABA reversal potential Embedded Image from the inhibitory-to-excitatory current, Embedded Image . Diagrams A–D were calculated for Embedded Image = 2 mS/cm2; E, gIE = 0.5 mS/cm2; and F, gIE 1 mS/cm2. The value of Embedded Image characterizes the average membrane potential in the resting state and maximal/minimal values of Embedded Image during the oscillations. Red and green dots correspond to the supercritical and subcritical Andronov–Hopf bifurcations. Solid and dotted lines depict the stable and unstable solutions.

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    Table 1.

    Population model parameters

    Excitatory population
    ParameterValueInterpretation
    Embedded Image1 mF/cm2Membrane capacitance (Buchin and Chizhov, 2010b)
    Embedded Image0.02 mS/cm2Sodium leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image0.044 mS/cm2Potassium leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image0.01 mS/cm2Chloride leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image1.6 mS/cm2AHP-current conductance (Buchin and Chizhov, 2010b)
    Embedded Image1.5 mS/cm2Excitatory-to-excitatory conductance
    Embedded Image1 mS/cm2Excitatory-to-inhibitory conductance
    Embedded Image2; 0.5; 1 mS/cm2Inhibitory-to-excitatory conductance
    Embedded Image0.2 mS/cm2Inhibitory-to-inhibitory conductance
    Embedded Image–65 mVReset membrane potential (Chizhov and Graham, 2007; Buchin and Chizhov, 2010b)
    Embedded Image–55 mVThreshold membrane potential (Chizhov and Graham, 2007; Buchin and Chizhov, 2010b)
    Embedded Image2.84 × 104Sigmoid fit parameter
    Embedded Image0.19 mV-1Sigmoid fit parameter
    Embedded Image1.23 × 104Sigmoid fit parameter
    Embedded Image–10 mVSigmoid fit parameter (threshold)
    Embedded Image3 μA/cm2Input current variance
    Embedded Image5.4 msAMPA current correlation time (Buchin et al., 2016a,b)
    Embedded Image4 mVMembrane potential dispersion
    Embedded Image50 mVSodium reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image–75 mVPotassium reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image–93 mVChloride reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image–75 mVGABA reversal potential (Huberfeld et al., 2007)
    Embedded Image0 mVAMPA reversal potential (Brunel and Wang, 2001)
    Embedded Image–70 mVAHP reversal potential (Brunel and Wang, 2001)
    Embedded Image1 msAHP rise time (Brunel and Wang, 2001)
    Embedded Image320 msAHP decay time (Brunel and Wang, 2001)
    Embedded Image1 msAMPA rise time (Chizhov, 2002)
    Embedded Image5.4 msAMPA decay time (Chizhov, 2002)
    Inhibitory population
    ParameterValueInterpretation
    Embedded Image1 mS/cm2Membrane capacitance (Buchin and Chizhov, 2010b)
    Embedded Image0.02 mS/cm2Sodium leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image0.04 mS/cm2Potassium leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image0.03 mS/cm2Chloride leak conductance (Krishnan and Bazhenov, 2011)
    Embedded Image2 mS/cm2Inhibitory-excitatory synaptic conductance
    Embedded Image0.2 mS/cm2Excitatory-inhibitory synaptic conductance
    Embedded Image–65 mVReset membrane potential
    Embedded Image–55 mVThreshold membrane potential
    Embedded Image2.84 × 104Sigmoid fit parameter
    Embedded Image0.19 mV-1Sigmoid fit parameter
    Embedded Image1.23 × 104Sigmoid fit parameter
    Embedded Image–10 mVSigmoid fit parameter (threshold)
    Embedded Image4 mVMembrane potential dispersion
    Embedded Image50 mVSodium reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image–75 mVPotassium reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image–82 mVChloride reversal potential (Krishnan and Bazhenov, 2011)
    Embedded Image8.3 msGABA-A decay time (Chizhov et al., 2002)
    Embedded Image0.2 msGABA-A rise time (Chizhov, 2002)
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    Table 2.

    Population model variables

    VariableInterpretation
    Embedded Image , mVAverage membrane potential of the excitatorypopulation
    Embedded Image , mVAverage membrane potential of the inhibitory population
    eExcitatory population synaptic gating variable
    iInhibitory population synaptic gating variable
    aExcitatory population adaptation gating variable
    Embedded Image , μA/cm2Random excitatory input
    Embedded Image , HzFiring rate of the excitatory population
    Embedded Image , HzFiring rate of the inhibitory population
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    Table 3.

    Power spectrum analysis

    Model, peak amplitude, HzExperiment, peak amplitude, HzModel, spectrum linear fit, 1/HzExperiment, spectrum linear fit, 1/Hz
    Rest---0.005—-0.002-0.005—-0.002
    Seizure3.01—3.522.95—3.75-0.005—-0.002-0.003—-0.002
    Pre-ictal state1.33—1.431.21—1.79-0.007—-0.003-0.01—-0.008

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Adaptation and Inhibition Control Pathological Synchronization in a Model of Focal Epileptic Seizure
Anatoly Buchin, Cliff C. Kerr, Gilles Huberfeld, Richard Miles, Boris Gutkin
eNeuro 13 September 2018, 5 (5) ENEURO.0019-18.2018; DOI: 10.1523/ENEURO.0019-18.2018

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Adaptation and Inhibition Control Pathological Synchronization in a Model of Focal Epileptic Seizure
Anatoly Buchin, Cliff C. Kerr, Gilles Huberfeld, Richard Miles, Boris Gutkin
eNeuro 13 September 2018, 5 (5) ENEURO.0019-18.2018; DOI: 10.1523/ENEURO.0019-18.2018
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Keywords

  • adaptation
  • AHP current
  • neural mass model
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  • temporal lobe epilepsy

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