Sciweavers

ICMLA
2010
13 years 9 months ago
Nonlinear Dynamical Multi-Scale Model of Associative Memory
How can we get such reliable behavior from the mind when the brain is made up of such unreliable elements as neurons? We propose that the answer is related to the emergence of stab...
Alexander M. Duda, Stephen E. Levinson
NECO
2010
154views more  NECO 2010»
13 years 9 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
SCHOLARPEDIA
2008
76views more  SCHOLARPEDIA 2008»
13 years 10 months ago
Stomatogastric ganglion
ABSTRACT: The lobster stomatogastric ganglion contains 30 neurons and when modulated can produce two distinct rhythmic motor patterns--the gastric mill and the pyloric. The complet...
Allen I. Selverston
IJON
2010
127views more  IJON 2010»
13 years 10 months ago
Oscillation in a network model of neocortex
A basic understanding of the relationship between activity of individual neurons and macroscopic electrical activity of local field potentials or electroencephalogram (EEG) may pro...
Jennifer Dwyer, Hyong Lee, Amber Martell, Rick L. ...
NN
2002
Springer
226views Neural Networks» more  NN 2002»
13 years 11 months ago
Data visualisation and manifold mapping using the ViSOM
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
Hujun Yin
JCNS
1998
84views more  JCNS 1998»
13 years 11 months ago
Representation of Visual Space in Area 7a Neurons Using the Center of Mass Equation
The firing rate of neurons in parietal area 7a of the behaving Rhesus monkey with its head fixed incorporates both visual and eye position information. This neural tuning is not ...
Ralph M. Siegel
IJON
2002
130views more  IJON 2002»
13 years 11 months ago
Error-backpropagation in temporally encoded networks of spiking neurons
For a network of spiking neurons that encodes information in the timing of individual spike times, we derive a supervised learning rule, SpikeProp, akin to traditional errorbackpr...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
IJON
2002
67views more  IJON 2002»
13 years 11 months ago
Synfire chain in a balanced network
We investigate the formation of ordered spatiotemporal activations of pools of neurons in synfire chains (SFC) within a balanced network, both by simulations and by analytic tools...
Yuval Aviel, E. Pavlov, Moshe Abeles, David Horn
BC
1998
118views more  BC 1998»
13 years 11 months ago
A cross-interval spike train analysis: the correlation between spike generation and temporal integration of doublets
Abstract. A stochastic spike train analysis technique is introduced to reveal the correlation between the firing of the next spike and the temporal integration period of two conse...
David C. Tam
NN
2000
Springer
167views Neural Networks» more  NN 2000»
13 years 11 months ago
Blind signal processing by the adaptive activation function neurons
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
Simone Fiori