A neural cocktail-party processor
Biological Cybernetics
Dynamics of functional coupling in the cerebral cortex: an attempt at a model-based interpretation
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Dynamical cell assembly hypothesis—theoretical possibility of spatio-temporal coding in the cortex
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Temporally asymmetric Hebbian learning, spike timing and neuronal response variability
Proceedings of the 1998 conference on Advances in neural information processing systems II
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Spatiotemporal spike-encoding of a continuous external signal
Neural Computation
Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning
Neural Computation
Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning
Neural Computation
Dynamic switching of neural codes in networks with gap junctions
Neural Networks
An asynchronous spiking chaotic neuron integrated circuit
Neurocomputing
Stochastic perturbation methods for spike-timing-dependent plasticity
Neural Computation
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It has been a matter of debate how firing rates or spatiotemporal spike patterns carry information in the brain. Recent experimental and theoretical work in part showed that these codes, especially a population rate code and a synchronous code, can be dually used in a single architecture. However, we are not yet able to relate the role of firing rates and synchrony to the spatiotemporal structure of inputs and the architecture of neural networks. In this article, we examine how feedforward neural networks encode multiple input sources in the firing patterns. We apply spiketime-dependent plasticity as a fundamental mechanism to yield synaptic competition and the associated input filtering. We use the Fokker-Planck formalism to analyze the mechanism for synaptic competition in the case of multiple inputs, which underlies the formation of functional clusters in downstream layers in a self-organizing manner. Depending on the types of feedback coupling and shared connectivity, clusters are independently engaged in population rate coding or synchronous coding, or they interact to serve as input filters. Classes of dual codings and functional roles of spike-time-dependent plasticity are also discussed.