Short term memory in recurrent networks of spiking neurons
We present in this paper a general model of recurrent networks of spiking neurons, composed of several populations, and whose interaction pattern is set with a random draw. We use for simplicity discrete time neuron updating, and the emitted spikes are ...
Finding independent components using spikes: A natural result of Hebbian learning in a sparse spike coding scheme
As an alternative to classical representations in machine learning algorithms, we explore coding strategies using events as is observed for spiking neurons in the central nervous system. Focusing on visual processing, we have previously shown that we can ...
A pulsed neural network model of spectro-temporal receptivefields and population coding in auditory cortex
The existence of spectro-temporal receptive fields and evidence for population coding in auditory cortex motivate the development of such models, that explicitly operate in the time-frequency domain and are based on a pulsed neural network. In presenting ...
The evidence for neural information processing with precise spike-times: A survey
This paper surveys recent findings in neuroscience regarding the behavioral relevancy of the precise timing with which real spiking neurons emit spikes. The literature suggests that in almost any system where the processing-speed of a neural (sub)-system ...
SINBAD automation of scientific discovery: From factor analysis to theory synthesis
Modern science is turning to progressively more complex and data-rich subjects, which challenges the existing methods of data analysis and interpretation. Consequently, there is a pressing need for development of ever more powerful methods of extracting ...
