The Experts below are selected from a list of 211896 Experts worldwide ranked by ideXlab platform

Katie Sykes - One of the best experts on this subject based on the ideXlab platform.

  • nations like unto yourselves an inquiry into the status of a General Principle of international law on animal welfare
    Social Science Research Network, 2013
    Co-Authors: Katie Sykes
    Abstract:

    This article proposes that there is a General Principle of international law concerning the humane treatment of animals. Preoccupation with “animal rights” has been associated with Western cultural imperialism masquerading as a universal ethic. The issue of animal welfare is thus an instructive example of what Jutta Brunnee and Stephen Toope have identified as the key challenge for international law of “construct[ing] normative institutions while admitting and upholding the diversity of peoples in international society.” The article applies the framework of interactive international law that is set out in Brunnee and Toope’s recent book Legitimacy and Legality in International Law, while raising questions about the weight that their analysis accords to practice and their willingness to conclude that widely recognized Principles to which states fail to adhere in practice lack legal force. The article also examines how laws prohibiting cruelty to animals have emerged precisely from an interactive cultural exchange between East and West, in particular between England and India. It concludes that Brunnee and Toope’s framework, although it does not deal at any length with General Principles of law (a source of international law in which practice plays a relatively minor role), is a useful tool for understanding how a culturally contested Principle fits into international law, and ultimately supports the view that there is a General Principle of international law concerning animal welfare.

  • nations like unto yourselves an inquiry into the status of a General Principle of international law on animal welfare
    Canadian Yearbook of international Law Annuaire canadien de droit international, 2012
    Co-Authors: Katie Sykes
    Abstract:

    This article proposes that there is a General principIe of international law concerning the humane treatment of animals. Preoccupation with "animal rights" has been associated with Western cultural imperialism masquerading as a universal ethic. Animal welfare is thus an instructive case study of what Jutta Brunnee and Stephen Toope have identified as the key challenge for international law, that of "construct[ing] normative institutions while admitting and upholding the diversity of peoples in international society." This article applies the framework of interactional international law set out in Brunnee and Toope's recent book Legitimacy and Legality in International Law, while raising questions about the weight that their analysis accords to practice and their willingness to conclude that widely recognized Principles to which states fail to adhere in practice lack legal force. The article also examines how laws prohibiting cruelty to animals have emerged precisely from an interactive cultural exchange between East and West, in particular, between England and India. It concludes that Brunnee and Toope's framework, although it does not deal at any length with General Principles of law (a source of in ternational law in which practice plays a relatively minor role) , is nevertheless a useful tool for understanding how a culturally contested principIe fits into international law and ultimately supports the view that there is a General principIe of international law concerning animal welfare

Hermann Cuntz - One of the best experts on this subject based on the ideXlab platform.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    Neuron, 2021
    Co-Authors: Hermann Cuntz, Alex D Bird, Martin Mittag, Marcel Beining, Marius Schneider
    Abstract:

    Summary Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    bioRxiv, 2019
    Co-Authors: Hermann Cuntz, Alex D Bird, Marcel Beining, Marius Schneider, Laura Mediavilla, Felix Z Hoffmann
    Abstract:

    Abstract Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental Principle of dendritic constancy that has consequences for the overall computation in neural circuits. In brief We show that realistic neuron models essentially collapse to point neurons when stimulated by randomly distributed inputs instead of by single synapses or current injection in the soma. Highlights A simple equation that predicts voltage in response to distributed synaptic inputs. Responses to distributed and clustered inputs are largely independent of dendritic length. Spike rates in various Hodgkin Huxley (HH) like or Leaky Integrate-and-Fire (LIF) models are largely independent of morphology. Precise spike timing (firing pattern) depends on dendritic morphology. NeuroMorpho.Org database-wide analysis of the relation between dendritic morphology and electrophysiology. Our equations set precise input-output relations in realistic dendrite models.

Alex D Bird - One of the best experts on this subject based on the ideXlab platform.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    Neuron, 2021
    Co-Authors: Hermann Cuntz, Alex D Bird, Martin Mittag, Marcel Beining, Marius Schneider
    Abstract:

    Summary Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    bioRxiv, 2019
    Co-Authors: Hermann Cuntz, Alex D Bird, Marcel Beining, Marius Schneider, Laura Mediavilla, Felix Z Hoffmann
    Abstract:

    Abstract Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental Principle of dendritic constancy that has consequences for the overall computation in neural circuits. In brief We show that realistic neuron models essentially collapse to point neurons when stimulated by randomly distributed inputs instead of by single synapses or current injection in the soma. Highlights A simple equation that predicts voltage in response to distributed synaptic inputs. Responses to distributed and clustered inputs are largely independent of dendritic length. Spike rates in various Hodgkin Huxley (HH) like or Leaky Integrate-and-Fire (LIF) models are largely independent of morphology. Precise spike timing (firing pattern) depends on dendritic morphology. NeuroMorpho.Org database-wide analysis of the relation between dendritic morphology and electrophysiology. Our equations set precise input-output relations in realistic dendrite models.

Martin Mittag - One of the best experts on this subject based on the ideXlab platform.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    Neuron, 2021
    Co-Authors: Hermann Cuntz, Alex D Bird, Martin Mittag, Marcel Beining, Marius Schneider
    Abstract:

    Summary Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

Marius Schneider - One of the best experts on this subject based on the ideXlab platform.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    Neuron, 2021
    Co-Authors: Hermann Cuntz, Alex D Bird, Martin Mittag, Marcel Beining, Marius Schneider
    Abstract:

    Summary Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

  • a General Principle of dendritic constancy a neuron s size and shape invariant excitability
    bioRxiv, 2019
    Co-Authors: Hermann Cuntz, Alex D Bird, Marcel Beining, Marius Schneider, Laura Mediavilla, Felix Z Hoffmann
    Abstract:

    Abstract Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental Principle of dendritic constancy that has consequences for the overall computation in neural circuits. In brief We show that realistic neuron models essentially collapse to point neurons when stimulated by randomly distributed inputs instead of by single synapses or current injection in the soma. Highlights A simple equation that predicts voltage in response to distributed synaptic inputs. Responses to distributed and clustered inputs are largely independent of dendritic length. Spike rates in various Hodgkin Huxley (HH) like or Leaky Integrate-and-Fire (LIF) models are largely independent of morphology. Precise spike timing (firing pattern) depends on dendritic morphology. NeuroMorpho.Org database-wide analysis of the relation between dendritic morphology and electrophysiology. Our equations set precise input-output relations in realistic dendrite models.