First spike latency sensitivity of spiking neuron models

Predicting Spike Train Responses of Neuron Models Predicting Spike Train Responses of Neuron Models

It is shown how neural spike train responses can be predicted by truncated Wiener series and by LN-cascade models. To prove the capability of these methods we test them on spike trains which have been generated by model neurons. The agreement of the approximated responses and the neuron response to known stimuli is analysed quantitatively by calculating least mean square errors and rates of coi...

Decoding first-spike latency: A likelihood approach

First-spike latency at the level of auditory cortex appears to correlate well with sound source direction. However, an unsettled issue with latency as a neural code is the apparent lack of temporal marking for the onset of the stimulus. One possible resolution is that relative ensemble latencies could be decoded rather than absolute latencies. How an ensemble timing referent might inform a theo...

Predicting spike train responses of neuron models

Neuron Modulation: A Digital Modulation Based on Spiking Neuron Models

In this paper, a novel digital modulation technique based on spiking neuron models is proposed. Thanks to the extremely simple and low-power spiking neuron circuits, this modulation scheme allows a less complex receiver at the cost of a more complicated transmitter. Accordingly, it is a good candidate for downlink transmission. Since the transmitted signal is generated based on Shannon’s interp...

Spiking Neuron Models Single Neurons, Populations, Plasticity

A catalogue record of this book is available from the British Library ISBN 0 521 81384 0 hardback ISBN 0 521 89079 9 paperback Contents Preface page xi Acknowledgments xiv 1 Introduction 1 1.1 Elements of neuronal systems 1 1.1.1 The ideal spiking neuron 2 1.1.2 Spike trains 3 1.1.3 Synapses 4 1.2 Elements of neuronal dynamics 4 1.2.1 Postsynaptic potentials 6 1.2.2 Firing threshold and action ...