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Andreas V. M. Herz - One of the best experts on this subject based on the ideXlab platform.

  • Section: Cell physiology Dynamics of rat entorhinal cortex layer II/III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    2020
    Co-Authors: Andreas V. M. Herz, G Kreck, Uwe Heinemann, Irina Erchova
    Abstract:

    Abstract Neurons generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neuron and its electrical resonance properties. Using intracellular sharp micro-electrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC-layer-II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5-15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC-layer-III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

  • dynamics of rat entorhinal cortex layer ii and iii cells characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    The Journal of Physiology, 2004
    Co-Authors: Irina Erchova, G Kreck, Uwe Heinemann, Andreas V. M. Herz
    Abstract:

    Neurones generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neurone and its electrical resonance properties. Using intracellular sharp microelectrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC layer II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5–15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC layer III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

Irina Erchova - One of the best experts on this subject based on the ideXlab platform.

  • Section: Cell physiology Dynamics of rat entorhinal cortex layer II/III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    2020
    Co-Authors: Andreas V. M. Herz, G Kreck, Uwe Heinemann, Irina Erchova
    Abstract:

    Abstract Neurons generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neuron and its electrical resonance properties. Using intracellular sharp micro-electrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC-layer-II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5-15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC-layer-III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

  • dynamics of rat entorhinal cortex layer ii and iii cells characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    The Journal of Physiology, 2004
    Co-Authors: Irina Erchova, G Kreck, Uwe Heinemann, Andreas V. M. Herz
    Abstract:

    Neurones generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neurone and its electrical resonance properties. Using intracellular sharp microelectrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC layer II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5–15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC layer III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

Gian Paolo Beretta - One of the best experts on this subject based on the ideXlab platform.

  • NONLINEAR DYNAMICAL EQUATION FOR IRREVERSIBLE, STEEPEST-ENTROPY-ASCENT RELAXATION TO STABLE EQUILIBRIUM
    2015
    Co-Authors: Gian Paolo Beretta
    Abstract:

    Abstract. We discuss the structure and main features of the nonlinear evolution equation proposed by this author as the fundamental dynamical law within the framework of Quantum Thermodynamics. The nonlinear equation generates a dynam-ical group providing a unique Deterministic Description of irreversible, conservative relaxation towards equilibrium from any non-equilibrium state, and satisfies a very restrictive stability requirement equivalent to Hatsopoulos-Keenan statement of the second law of thermodynamics. Here, we emphasize its mathematical structure and its applicability also within other contexts

  • Nonlinear quantum evolution equations to model irreversible adiabatic relaxation with maximal entropy production and other nonunitary processes
    2013
    Co-Authors: Gian Paolo Beretta
    Abstract:

    We first discuss the geometrical construction and the main mathematical features of the maximum-entropy-production/steepest-entropyascent nonlinear evolution equation proposed long ago by this author in the framework of a fully quantum theory of irreversibility and thermodynamics for a single isolated or adiabatic particle, qubit, or qudit, and recently rediscovered by other authors. The nonlinear equation generates a dynamical group, not just a semigroup, providing a Deterministic Description of irreversible conservative relaxation towards equilibrium from any non-equilibrium density operator. It satisfies a very restrictive stability requirement equivalent to the Hatsopoulos-Keenan statement of the second law of thermodynamics. We then examine the form of the evolution equation we proposed to describe multipartite isolated or adiabatic systems. This hinges on novel nonlinear projections defining local operators that we interpret as “local perceptions ” of the overall system’s energy and entropy. Each component particle contributes an independent local tendency along the direction of steepest increase of the locally perceived entropy at constant locally perceived energy. It conserves both the locallyperceived energies and the overall energy, and meets strong separability and non-signaling conditions, even though the local evolutions are not independent of existing correlations. We finally show how the geometrical construction can readily lead to other thermodynamically relevant models, such as of the nonunitary isoentropic evolution needed for full extraction of a system’s adiabatic availability

  • nonlinear quantum evolution equations to model irreversible adiabatic relaxation with maximal entropy production and other nonunitary processes
    Reports on Mathematical Physics, 2009
    Co-Authors: Gian Paolo Beretta
    Abstract:

    We first discuss the geometrical construction and the main mathematical features of the maximum-entropy production/steepest-entropy-ascent nonlinear evolution equation proposed long time ago by this author in the framework of a fully quantum theory of irreversibility and ther­ modynamics for a single isolated or adiabatic particle, qubit, or qudit, and recently rediscovered by other authors. The nonlinear equation generates a dynamical group, not just a semigroup, providing a Deterministic Description of irreversible conservative relaxation towards equilibrium from any nonequilibrium density operator. It satisfies a very restrictive stability requirement equivalent to the Hatsopoulos-Keenan statement of the second law of thermodynamics. We then examine the form of the evolution equation we proposed to describe multipartite isolated or adiabatic systems. This hinges on novel nonlinear projections defining local operators that we interpret as "local perceptions" of the overall system's energy and entropy. Each component particle contributes an independent local tendency along the direction of steepest increase of the locally perceived entropy at constant locally perceived energy. It conserves both the locally perceived energies and the overall energy, and meets strong separability and nonsignaling con­ ditions, even though the local evolutions are not independent of existing correlations. We finally show how the geometrical construction can readily lead to other thermodynamically relevant models, such as of the nonunitary isoentropic evolution needed for full extraction of a system's adiabatic availability.

  • nonlinear dynamical equation for irreversible steepest entropy ascent relaxation to stable equilibrium
    arXiv: Quantum Physics, 2007
    Co-Authors: Gian Paolo Beretta
    Abstract:

    We discuss the structure and main features of the nonlinear evolution equation proposed by this author as the fundamental dynamical law within the framework of Quantum Thermodynamics. The nonlinear equation generates a dynamical group providing a unique Deterministic Description of irreversible, conservative relaxation towards equilibrium from any non-equilibrium state, and satisfies a very restrictive stability requirement equivalent to Hatsopoulos-Keenan statement of the second law of thermodynamics. Here, we emphasize its mathematical structure and its applicability also within other contexts, such as Classical and Quantum Statistical Mechanics, and Information Theory.

G Kreck - One of the best experts on this subject based on the ideXlab platform.

  • Section: Cell physiology Dynamics of rat entorhinal cortex layer II/III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    2020
    Co-Authors: Andreas V. M. Herz, G Kreck, Uwe Heinemann, Irina Erchova
    Abstract:

    Abstract Neurons generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neuron and its electrical resonance properties. Using intracellular sharp micro-electrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC-layer-II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5-15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC-layer-III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

  • dynamics of rat entorhinal cortex layer ii and iii cells characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    The Journal of Physiology, 2004
    Co-Authors: Irina Erchova, G Kreck, Uwe Heinemann, Andreas V. M. Herz
    Abstract:

    Neurones generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neurone and its electrical resonance properties. Using intracellular sharp microelectrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC layer II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5–15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC layer III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

Uwe Heinemann - One of the best experts on this subject based on the ideXlab platform.

  • Section: Cell physiology Dynamics of rat entorhinal cortex layer II/III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    2020
    Co-Authors: Andreas V. M. Herz, G Kreck, Uwe Heinemann, Irina Erchova
    Abstract:

    Abstract Neurons generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neuron and its electrical resonance properties. Using intracellular sharp micro-electrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC-layer-II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5-15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC-layer-III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.

  • dynamics of rat entorhinal cortex layer ii and iii cells characteristics of membrane potential resonance at rest predict oscillation properties near threshold
    The Journal of Physiology, 2004
    Co-Authors: Irina Erchova, G Kreck, Uwe Heinemann, Andreas V. M. Herz
    Abstract:

    Neurones generate intrinsic subthreshold membrane potential oscillations (MPOs) under various physiological and behavioural conditions. These oscillations influence neural responses and coding properties on many levels. On the single-cell level, MPOs modulate the temporal precision of action potentials; they also have a pronounced impact on large-scale cortical activity. Recent studies have described a close association between the MPOs of a given neurone and its electrical resonance properties. Using intracellular sharp microelectrode recordings we examine both dynamical characteristics in layers II and III of the entorhinal cortex (EC). Our data from EC layer II stellate cells show strong membrane potential resonances and oscillations, both in the range of 5–15 Hz. At the resonance maximum, the membrane impedance can be more than twice as large as the input resistance. In EC layer III cells, MPOs could not be elicited, and frequency-resolved impedances decay monotonically with increasing frequency or has only a small peak followed by a subsequent decay. To quantify and compare the resonance and oscillation properties, we use a simple mathematical model that includes stochastic components to capture channel noise. Based on this model we demonstrate that electrical resonance is closely related though not equivalent to the occurrence of sag-potentials and MPOs. MPO frequencies can be predicted from the membrane impedance curve for stellate cells. The model also explains the broad-band nature of the observed MPOs. This underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a Deterministic Description of MPOs. In addition, our results show that the two identified cell classes in the superficial EC layers, which are known to target different areas in the hippocampus, also have different preferred frequency ranges and dynamic characteristics. Intrinsic cell properties may thus play a major role for the frequency-dependent information flow in the hippocampal formation.