NN
2008
Springer
13 years 5 months ago
2008
Springer
A silicon neuron circuit that produces spiking and bursting firing patterns, with biologically plausible spike shape, is presented. The circuit mimics the behaviour of known class...
NECO
2008
13 years 5 months ago
2008
Spike correlations between neurons are ubiquitous in the cortex, but their role is at present not understood. Here we describe the firing response of a leaky integrate-and-fire ne...
JCNS
2008
13 years 5 months ago
2008
Using a realistic model of activity dependent dynamical synapse, which includes both depressing and facilitating mechanisms, we study the conditions in which a postsynaptic neuron...
IJON
2006
13 years 5 months ago
2006
In this work, we propose a variation of a direct reinforcement learning algorithm, suitable for usage with spiking neurons based on the spike response model (SRM). The SRM is a bi...
IJON
2006
13 years 5 months ago
2006
The synapse from the lateral pyloric (LP) to the pyloric dilator (PD) neuron in the stomatogastric nervous system of the crab Cancer borealis has both a graded and a spike-mediate...
IJFCS
2006
13 years 5 months ago
2006
We continue here the study of the recently introduced spiking neural P systems, which mimic the way that neurons communicate with each other by means of short electrical impulses, ...
FUIN
2006
13 years 5 months ago
2006
This paper is an attempt to incorporate the idea of spiking neurons into the area of membrane computing, and to this aim we introduce a class of neural-like P systems which we cal...
BC
2007
13 years 5 months ago
2007
Correlation measures are important tools for the analysis of simultaneously recorded spike trains. A well-known measure with probabilistic interpretation is the cross-intensity fun...
NIPS
2004
13 years 6 months ago
2004
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
ESANN
2001
13 years 6 months ago
2001
Neural networks use neurons of the same type in each layer but such architecture cannot lead to data models of optimal complexity and accuracy. Networks with architectures (number ...