The coherence between neural spike trains and local-field potential recordings, called spike-field coherence, is of key importance in many neuroscience studies. In this work, aside from questions of estimator performance, we demonstrate that theoretical spike-field coherence for a broad class of spiking models depends on the expected rate of spiking. This rate dependence confounds the phase loc...

Spiking neural P systems are a new candidate in spiking neural network models. By using neuron division and budding, such systems can generate/produce exponential working space in linear computational steps, thus provide a way to solve computational hard problems in feasible (linear or polynomial) time with a "time-space trade-off" strategy. In this work, a new mechanism called neuron dissoluti...

This paper presents pulse-coupled two bifurcating neurons. The single neuron is represented by a spike position map and the coupled neurons can be represented by a composition of the spike position maps. Using the composite map, we can analyze basic bifurcation phenomena and can find some interesting phenomena that are caused by the pulse-coupling and are impossible in the single neuron. Presen...

Effects of time delay on Hindmarsh-Rose(HR) model neuron are studied. For an individual neuron, with the scaling delay time and synaptic intensity, neuronal firing pattern’s transform among tonic spiking, busting and resting firing state, and the neuronal chaotic spike could be controlled. Furthermore, two coupled HR neuronal system could be fully synchronized under certain coupled strength and...

“Spikes are the neural code”: this claim is about 15 years old (Shadlen & Newsome, 1994; Rieke, Warland, Steveninck, & Bialek, 1996), preceded by theoretical studies on the underlying mathematical processes (e.g., (Gerstein & Mandelbrot, 1964)), and followed by many developments regarding biological modelling or computational paradigms, or both (e.g., (Thorpe, Delorme, & VanRullen, 2001)). Howe...

Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dend...

Background: Recently, ultrasonic neuromodulation research has been an important and interesting issue. Ultrasonic neuromodulation is possible by the use of low-intensity transcranial focused ultrasound (tFUS) to stimulate or inhibit the neural structures. The primary capability of this method is the improvement in the treatment progress of certain neurological and psychiatric disorders noninvas...

With a similar capability of processing spikes as biological neural systems, networks of spiking neurons are expected to achieve a performance similar to that of living brains. Despite the achievement of spiking neuron based applications, most of them assume noise-free condition for learning and testing. This assumption, though fairly general, ignores the fact that noise widely exists in spikin...