In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

The concept that neural information is encoded in the firing rate of neurons has been the
dominant paradigm in neurobiology for many years. This paradigm has also been adopted …

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 …

Synaptic plasticity, the putative basis of learning and memory formation, manifests in various
forms and across different timescales. Here we show that the interaction of Hebbian …

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 nature and origin of the temporal irregularity in the electrical activity of cortical neurons
in vivo are not well understood. We consider the hypothesis that this irregularity is due to a …

Several neural network models in continuous time are reconsidered in the framework of a
general mean-field theory which is exact in the limit of a large and fully connected network …

The fundamental building block of every nervous system is the single neuron.
Understanding how these exquisitely structured elements operate is an integral part of the …

Several formulations of correlation-based Hebbian learning are reviewed. On the
presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival …

The integrate-and-fire neuron model describes the state of a neuron in terms of its
membrane potential, which is determined by the synaptic inputs and the injected current that …