A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
What is the goal of sensory coding?
Neural Computation
Neural processing in the subsecond time range in the temporal cortex
Neural Computation
CNS '97 Proceedings of the sixth annual conference on Computational neuroscience : trends in research, 1998: trends in research, 1998
Spikes: exploring the neural code
Spikes: exploring the neural code
On decoding the responses of a population of neurons from short time windows
Neural Computation
SpikeCell: a deterministic spiking neuron
Neural Networks
Ultra-Rapid Scene Categorization with a Wave of Spikes
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Mean instantaneous firing frequency is always higher than the firing rate
Neural Computation
Natural Computing: an international journal
Neurons Tune to the Earliest Spikes Through STDP
Neural Computation
Efficient Computation Based on Stochastic Spikes
Neural Computation
Neural Computation
Arbitrated time-to-first spike CMOS image sensor with on-chip histogram equalization
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Closing the Sensory-Motor Loop on Dopamine Signalled Reinforcement Learning
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Capacity of a single spiking neuron channel
Neural Computation
Computation with spikes in a winner-take-all network
Neural Computation
Evaluating rank-order code performance using a biologically-derived retinal model
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Spike-latency codes and the effect of saccades
Neurocomputing
Biologically inspired means for rank-order encoding images: a quantitative analysis
IEEE Transactions on Neural Networks
A novel asynchronous pixel for an energy harvesting CMOS image sensor
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Expectation Truncation and the Benefits of Preselection In Training Generative Models
The Journal of Machine Learning Research
A bio-inspired image coder with temporal scalability
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Spike-Based image processing: can we reproduce biological vision in hardware?
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
A real-time, event-driven neuromorphic system for goal-directed attentional selection
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
A spike-timing-based integrated model for pattern recognition
Neural Computation
Temporal order detection and coding in nervous systems
Neural Computation
Optical flow estimation in cardiac CT images using the steered Hermite transform
Image Communication
A new supervised learning algorithm for spiking neurons
Neural Computation
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It is often supposed that the messages sent to the visual cortex by the retinal ganglion cells are encoded by the mean firing rates observed on spike trains generated with a Poisson process. Using an information transmission approach, we evaluate the performances of two such codes, one based on the spike count and the other on the mean interspike interval, and compare the results with a rank order code, where the first ganglion cells to emit a spike are given a maximal weight. Our results show that the rate codes are far from optimal for fast information transmission and that the temporal structure of the spike train can be efficiently used to maximize the information transfer rate under conditions where each cell needs to fire only one spike.