Cable Theory

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Gaute T Einevoll - One of the best experts on this subject based on the ideXlab platform.

  • power laws from linear neuronal Cable Theory power spectral densities of the soma potential soma membrane current and single neuron contribution to the eeg
    PLOS Computational Biology, 2014
    Co-Authors: Klas H Pettersen, Henrik Linden, Tom Tetzlaff, Gaute T Einevoll
    Abstract:

    Power laws, that is, power spectral densities (PSDs) exhibiting behavior for large frequencies f, have been observed both in microscopic (neural membrane potentials and currents) and macroscopic (electroencephalography; EEG) recordings. While complex network behavior has been suggested to be at the root of this phenomenon, we here demonstrate a possible origin of such power laws in the biophysical properties of single neurons described by the standard Cable equation. Taking advantage of the analytical tractability of the so called ball and stick neuron model, we derive general expressions for the PSD transfer functions for a set of measures of neuronal activity: the soma membrane current, the current-dipole moment (corresponding to the single-neuron EEG contribution), and the soma membrane potential. These PSD transfer functions relate the PSDs of the respective measurements to the PSDs of the noisy input currents. With homogeneously distributed input currents across the neuronal membrane we find that all PSD transfer functions express asymptotic high-frequency power laws with power-law exponents analytically identified as for the soma membrane current, for the current-dipole moment, and for the soma membrane potential. Comparison with available data suggests that the apparent power laws observed in the high-frequency end of the PSD spectra may stem from uncorrelated current sources which are homogeneously distributed across the neural membranes and themselves exhibit pink () noise distributions. While the PSD noise spectra at low frequencies may be dominated by synaptic noise, our findings suggest that the high-frequency power laws may originate in noise from intrinsic ion channels. The significance of this finding goes beyond neuroscience as it demonstrates how power laws with a wide range of values for the power-law exponent α may arise from a simple, linear partial differential equation.

Ricardo M Leao - One of the best experts on this subject based on the ideXlab platform.

  • a negative slope conductance of the persistent sodium current prolongs subthreshold depolarizations
    Biophysical Journal, 2017
    Co-Authors: Cesar C Ceballos, Antonio C Roque, Ricardo M Leao
    Abstract:

    Neuronal subthreshold voltage-dependent currents determine membrane properties such as the input resistance (Rin) and the membrane time constant (τm) in the subthreshold range. In contrast with classical Cable Theory predictions, the persistent sodium current (INaP), a non-inactivating mode of the voltage-dependent sodium current, paradoxically increases Rin and τm when activated. Furthermore, this current amplifies and prolongs synaptic currents in the subthreshold range. Here, using a computational neuronal model, we showed that the creation of a region of negative slope conductance by INaP activation is responsible for these effects and the ability of the negative slope conductance to amplify and prolong Rin and τm relies on the fast activation of INaP. Using dynamic clamp in hippocampal CA1 pyramidal neurons in brain slices, we showed that the effects of INaP on Rin and τm can be recovered by applying an artificial INaP after blocking endogenous INaP with tetrodotoxin. Furthermore, we showed that injection of a pure negative conductance is enough to reproduce the effects of INaP on Rin and τm and is also able to prolong artificial excitatory post synaptic currents. Since both the negative slope conductance and the almost instantaneous activation are critical for producing these effects, the INaP is an ideal current for boosting the amplitude and duration of excitatory post synaptic currents near the action potential threshold.

  • the role of negative conductances in neuronal subthreshold properties and synaptic integration
    Biophysical Reviews, 2017
    Co-Authors: Cesar C Ceballos, Antonio C Roque, Ricardo M Leao
    Abstract:

    Based on passive Cable Theory, an increase in membrane conductance produces a decrease in the membrane time constant and input resistance. Unlike the classical leak currents, voltage-dependent currents have a nonlinear behavior which can create regions of negative conductance, despite the increase in membrane conductance (permeability). This negative conductance opposes the effects of the passive membrane conductance on the membrane input resistance and time constant, increasing their values and thereby substantially affecting the amplitude and time course of postsynaptic potentials at the voltage range of the negative conductance. This paradoxical effect has been described for three types of voltage-dependent inward currents: persistent sodium currents, L- and T-type calcium currents and ligand-gated glutamatergic N-methyl-D-aspartate currents. In this review, we describe the impact of the creation of a negative conductance region by these currents on neuronal membrane properties and synaptic integration. We also discuss recent contributions of the quasi-active Cable approximation, an extension of the passive Cable Theory that includes voltage-dependent currents, and its effects on neuronal subthreshold properties.

Klas H Pettersen - One of the best experts on this subject based on the ideXlab platform.

  • power laws from linear neuronal Cable Theory power spectral densities of the soma potential soma membrane current and single neuron contribution to the eeg
    PLOS Computational Biology, 2014
    Co-Authors: Klas H Pettersen, Henrik Linden, Tom Tetzlaff, Gaute T Einevoll
    Abstract:

    Power laws, that is, power spectral densities (PSDs) exhibiting behavior for large frequencies f, have been observed both in microscopic (neural membrane potentials and currents) and macroscopic (electroencephalography; EEG) recordings. While complex network behavior has been suggested to be at the root of this phenomenon, we here demonstrate a possible origin of such power laws in the biophysical properties of single neurons described by the standard Cable equation. Taking advantage of the analytical tractability of the so called ball and stick neuron model, we derive general expressions for the PSD transfer functions for a set of measures of neuronal activity: the soma membrane current, the current-dipole moment (corresponding to the single-neuron EEG contribution), and the soma membrane potential. These PSD transfer functions relate the PSDs of the respective measurements to the PSDs of the noisy input currents. With homogeneously distributed input currents across the neuronal membrane we find that all PSD transfer functions express asymptotic high-frequency power laws with power-law exponents analytically identified as for the soma membrane current, for the current-dipole moment, and for the soma membrane potential. Comparison with available data suggests that the apparent power laws observed in the high-frequency end of the PSD spectra may stem from uncorrelated current sources which are homogeneously distributed across the neural membranes and themselves exhibit pink () noise distributions. While the PSD noise spectra at low frequencies may be dominated by synaptic noise, our findings suggest that the high-frequency power laws may originate in noise from intrinsic ion channels. The significance of this finding goes beyond neuroscience as it demonstrates how power laws with a wide range of values for the power-law exponent α may arise from a simple, linear partial differential equation.

Antoine Jérusalem - One of the best experts on this subject based on the ideXlab platform.

  • Neurite, a finite difference large scale parallel program for the simulation of electrical signal propagation in neurites under mechanical loading.
    PLOS ONE, 2015
    Co-Authors: Julián Andrés García-grajales, Gabriel Rucabado, Antonio García-dopico, José-maría Peña, Antoine Jérusalem
    Abstract:

    With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite—explicit and implicit—were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

Cesar C Ceballos - One of the best experts on this subject based on the ideXlab platform.

  • a negative slope conductance of the persistent sodium current prolongs subthreshold depolarizations
    Biophysical Journal, 2017
    Co-Authors: Cesar C Ceballos, Antonio C Roque, Ricardo M Leao
    Abstract:

    Neuronal subthreshold voltage-dependent currents determine membrane properties such as the input resistance (Rin) and the membrane time constant (τm) in the subthreshold range. In contrast with classical Cable Theory predictions, the persistent sodium current (INaP), a non-inactivating mode of the voltage-dependent sodium current, paradoxically increases Rin and τm when activated. Furthermore, this current amplifies and prolongs synaptic currents in the subthreshold range. Here, using a computational neuronal model, we showed that the creation of a region of negative slope conductance by INaP activation is responsible for these effects and the ability of the negative slope conductance to amplify and prolong Rin and τm relies on the fast activation of INaP. Using dynamic clamp in hippocampal CA1 pyramidal neurons in brain slices, we showed that the effects of INaP on Rin and τm can be recovered by applying an artificial INaP after blocking endogenous INaP with tetrodotoxin. Furthermore, we showed that injection of a pure negative conductance is enough to reproduce the effects of INaP on Rin and τm and is also able to prolong artificial excitatory post synaptic currents. Since both the negative slope conductance and the almost instantaneous activation are critical for producing these effects, the INaP is an ideal current for boosting the amplitude and duration of excitatory post synaptic currents near the action potential threshold.

  • the role of negative conductances in neuronal subthreshold properties and synaptic integration
    Biophysical Reviews, 2017
    Co-Authors: Cesar C Ceballos, Antonio C Roque, Ricardo M Leao
    Abstract:

    Based on passive Cable Theory, an increase in membrane conductance produces a decrease in the membrane time constant and input resistance. Unlike the classical leak currents, voltage-dependent currents have a nonlinear behavior which can create regions of negative conductance, despite the increase in membrane conductance (permeability). This negative conductance opposes the effects of the passive membrane conductance on the membrane input resistance and time constant, increasing their values and thereby substantially affecting the amplitude and time course of postsynaptic potentials at the voltage range of the negative conductance. This paradoxical effect has been described for three types of voltage-dependent inward currents: persistent sodium currents, L- and T-type calcium currents and ligand-gated glutamatergic N-methyl-D-aspartate currents. In this review, we describe the impact of the creation of a negative conductance region by these currents on neuronal membrane properties and synaptic integration. We also discuss recent contributions of the quasi-active Cable approximation, an extension of the passive Cable Theory that includes voltage-dependent currents, and its effects on neuronal subthreshold properties.