Most Recent Articles: The Journal of Mathematical Neurosciencehttps://mathematical-neuroscience.springeropen.comMost Recent Articles: The Journal of Mathematical NeuroscienceRegularization of Ill-Posed Point Neuron Modelshttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0049-1Point neuron models with a Heaviside firing rate function can be ill-posed. That is, the initial-condition-to-solution map might become discontinuous in finite time. If a Lipschitz continuous but steep firing rat...Fri, 14 Jul 2017 00:00:00 GMThttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0049-1Bjørn Fredrik Nielsen2017-07-14T00:00:00ZFinite-Size Effects on Traveling Wave Solutions to Neural Field Equationshttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0048-2Neural field equations are used to describe the spatio-temporal evolution of the activity in a network of synaptically coupled populations of neurons in the continuum limit. Their heuristic derivation involves...Thu, 06 Jul 2017 00:00:00 GMThttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0048-2Eva Lang and Wilhelm Stannat2017-07-06T00:00:00ZHow Adaptation Makes Low Firing Rates Robusthttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0047-3Low frequency firing is modeled by Type 1 neurons with a SNIC, but, because of the vertical slope of the square-root-like f–I curve, low f only occurs over a narrow range of I. When an adaptive current is added, ...Sat, 24 Jun 2017 00:00:00 GMThttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0047-3Arthur S. Sherman and Joon Ha2017-06-24T00:00:00ZTimescales and Mechanisms of Sigh-Like Bursting and Spiking in Models of Rhythmic Respiratory Neuronshttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0045-5Neural networks generate a variety of rhythmic activity patterns, often involving different timescales. One example arises in the respiratory network in the pre-Bötzinger complex of the mammalian brainstem, wh...Tue, 06 Jun 2017 00:00:00 GMThttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0045-5Yangyang Wang and Jonathan E. Rubin2017-06-06T00:00:00ZEmergent Dynamical Properties of the BCM Learning Rulehttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0044-6The 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...Mon, 20 Feb 2017 00:00:00 GMThttps://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-017-0044-6Lawrence C. Udeigwe, Paul W. Munro and G. Bard Ermentrout2017-02-20T00:00:00Z