The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

The integrate-and-fire neuron model is one of the most widely used models for analyzing the
behavior of neural systems. It describes the membrane potential of a neuron in terms of the …

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

What happens in our brain when we make a decision? What triggers a neuron to send out a
signal? What is the neural code? This textbook for advanced undergraduate and beginning …

An ongoing challenge in neuromorphic computing is to devise general and computationally
efficient models of inference and learning which are compatible with the spatial and …

A major goal of neuroscience, statistical physics, and nonlinear dynamics is to understand
how brain function arises from the collective dynamics of networks of spiking neurons. This …

Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

Neurons in the brain communicate by short electrical pulses, the so-called action potentials
or spikes. How can we understand the process of spike generation? How can we …

The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire
neurons are studied analytically. The analysis reveals a rich repertoire of states, including …

Neural network modeling is often concerned with stimulus-driven responses, but most of the
activity in the brain is internally generated. Here, we review network models of internally …