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  1. Research

    Emergent Dynamical Properties of the BCM Learning Rule

    The Bienenstock–Cooper–Munro (BCM) learning rule provides a simple setup for synaptic modification that combines a Hebbian product rule with a homeostatic mechanism that keeps the weights bounded. The homeosta...

    Lawrence C. Udeigwe, Paul W. Munro and G. Bard Ermentrout

    The Journal of Mathematical Neuroscience 2017 7:2

    Published on: 20 February 2017

  2. Research

    Analytic Modeling of Neural Tissue: I. A Spherical Bidomain

    Presented here is a model of neural tissue in a conductive medium stimulated by externally injected currents. The tissue is described as a conductively isotropic bidomain, i.e. comprised of intra and extracell...

    Benjamin L. Schwartz, Munish Chauhan and Rosalind J. Sadleir

    The Journal of Mathematical Neuroscience 2016 6:9

    Published on: 9 September 2016

  3. Research

    Ill-Posed Point Neuron Models

    We show that point-neuron models with a Heaviside firing rate function can be ill posed. More specifically, the initial-condition-to-solution map might become discontinuous in finite time. Consequently, if finite...

    Bjørn Fredrik Nielsen and John Wyller

    The Journal of Mathematical Neuroscience 2016 6:7

    Published on: 30 April 2016

  4. Research

    Entrainment Ranges for Chains of Forced Neural and Phase Oscillators

    Sensory input to the lamprey central pattern generator (CPG) for locomotion is known to have a significant role in modulating lamprey swimming. Lamprey CPGs are known to have the ability to entrain to a bendin...

    Nicole Massarelli, Geoffrey Clapp, Kathleen Hoffman and Tim Kiemel

    The Journal of Mathematical Neuroscience 2016 6:6

    Published on: 18 April 2016

  5. Research

    Wave Generation in Unidirectional Chains of Idealized Neural Oscillators

    We investigate the dynamics of unidirectional semi-infinite chains of type-I oscillators that are periodically forced at their root node, as an archetype of wave generation in neural networks. In previous stud...

    Bastien Fernandez and Stanislav M. Mintchev

    The Journal of Mathematical Neuroscience 2016 6:5

    Published on: 8 April 2016

  6. Research

    Neural Field Models with Threshold Noise

    The original neural field model of Wilson and Cowan is often interpreted as the averaged behaviour of a network of switch like neural elements with a distribution of switch thresholds, giving rise to the class...

    Rüdiger Thul, Stephen Coombes and Carlo R. Laing

    The Journal of Mathematical Neuroscience 2016 6:3

    Published on: 2 March 2016

  7. Review

    Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience

    The tools of weakly coupled phase oscillator theory have had a profound impact on the neuroscience community, providing insight into a variety of network behaviours ranging from central pattern generation to s...

    Peter Ashwin, Stephen Coombes and Rachel Nicks

    The Journal of Mathematical Neuroscience 2016 6:2

    Published on: 6 January 2016

  8. Research

    Wilson–Cowan Equations for Neocortical Dynamics

    In 1972–1973 Wilson and Cowan introduced a mathematical model of the population dynamics of synaptically coupled excitatory and inhibitory neurons in the neocortex. The model dealt only with the mean numbers o...

    Jack D. Cowan, Jeremy Neuman and Wim van Drongelen

    The Journal of Mathematical Neuroscience 2016 6:1

    Published on: 4 January 2016

  9. Research

    A Mechanistic Neural Field Theory of How Anesthesia Suppresses Consciousness: Synaptic Drive Dynamics, Bifurcations, Attractors, and Partial State Equipartitioning

    With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus ...

    Saing Paul Hou, Wassim M. Haddad, Nader Meskin and James M. Bailey

    The Journal of Mathematical Neuroscience (JMN) 2015 5:20

    Published on: 5 October 2015

  10. Short report

    Clarification and Complement to “Mean-Field Description and Propagation of Chaos in Networks of Hodgkin–Huxley and FitzHugh–Nagumo Neurons”

    In this note, we clarify the well-posedness of the limit equations to the mean-field N-neuron models proposed in (Baladron et al. in J. Math. Neurosci. 2:10, 2012) and we prove the associated propagation of chaos...

    Mireille Bossy, Olivier Faugeras and Denis Talay

    The Journal of Mathematical Neuroscience (JMN) 2015 5:19

    Published on: 1 September 2015

  11. Short report

    Extensive Four-Dimensional Chaos in a Mesoscopic Model of the Electroencephalogram

    In a previous work (Dafilis et al. in Chaos 23(2):023111, 2013), evidence was presented for four-dimensional chaos in Liley’s mesoscopic model of the electroencephalogram. The study was limited to one paramete...

    Mathew P. Dafilis, Federico Frascoli, Peter J. Cadusch and David T. J. Liley

    The Journal of Mathematical Neuroscience (JMN) 2015 5:18

    Published on: 12 August 2015

  12. Research

    Neural Excitability and Singular Bifurcations

    We discuss the notion of excitability in 2D slow/fast neural models from a geometric singular perturbation theory point of view. We focus on the inherent singular nature of slow/fast neural models and define e...

    Peter De Maesschalck and Martin Wechselberger

    The Journal of Mathematical Neuroscience (JMN) 2015 5:16

    Published on: 6 August 2015

  13. Research

    The Minimal k-Core Problem for Modeling k-Assemblies

    The concept of cell assembly was introduced by Hebb and formalized mathematically by Palm in the framework of graph theory. In the study of associative memory, a cell assembly is a group of neurons that are st...

    Cynthia I. Wood and Illya V. Hicks

    The Journal of Mathematical Neuroscience (JMN) 2015 5:14

    Published on: 14 July 2015

  14. Research

    Orientation Maps in V1 and Non-Euclidean Geometry

    In the primary visual cortex, the processing of information uses the distribution of orientations in the visual input: neurons react to some orientations in the stimulus more than to others. In many species, o...

    Alexandre Afgoustidis

    The Journal of Mathematical Neuroscience (JMN) 2015 5:12

    Published on: 17 June 2015

  15. Research

    Noise-Induced Precursors of State Transitions in the Stochastic Wilson–Cowan Model

    The Wilson–Cowan neural field equations describe the dynamical behavior of a 1-D continuum of excitatory and inhibitory cortical neural aggregates, using a pair of coupled integro-differential equations. Here ...

    Ehsan Negahbani, D. Alistair Steyn-Ross, Moira L. Steyn-Ross, Marcus T. Wilson and Jamie W. Sleigh

    The Journal of Mathematical Neuroscience (JMN) 2015 5:9

    Published on: 8 April 2015

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