The nervous system is made of a large number of neurons. Time-varying balance between
excitatory and inhibitory neurons is important to activate appropriate modes of electrical …

Conductance-based equations for electrically active cells form one of the most widely
studied mathematical frameworks in computational biology. This framework, as expressed …

We derive the mean-field equations arising as the limit of a network of interacting spiking
neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of …

The investigation of the human intelligence, cognitive systems and functional complexity of
human brain is significantly facilitated by high-performance computational platforms. In this …

The concepts of equilibrium and nonequilibrium steady states are introduced in the present
review as mathematical concepts associated with stationary Markov processes. For both …

Potassium ion and sodium ion channels play important roles in the propagation of action
potentials along a myelinated axon. The random opening and closing of ion channels can …

Inverse stochastic resonance (ISR) is a phenomenon in which the firing activity of a neuron
is inhibited at a certain noise level. In this paper, the effects of potassium channel blockage …

Spiking Neuromorphic systems have been introduced as promising platforms for energy-
efficient spiking neural network (SNNs) execution. SNNs incorporate neuronal and synaptic …

Motivated by neuroscience discoveries during the last few years, many studies consider
pulse-coupled neural networks with spike-timing as an essential component in information …

When using mathematical models to make quantitative predictions for clinical or industrial
use, it is important that predictions come with a reliable estimate of their accuracy …