Figure 1: Implementation of the greedy pursuit using Integrate-and-Fire Neurons. We show the raster plot of 16 neurons tuned for different orientations for the feed-forward (black bars) and the sparse spike coding (white bars) models during the first 150 ms. We simulated here the activity of a network of Integrate-and-Fire neurons tuned to form a simple model of an hyper-column in the primary visual area (V1) to the presentation of a horizontal edge at t=0. In thz sparse coding model, the correlation linked to the information already detected is propagated as a hyper-polarizing and shunting lateral interaction to the neighboring neurons: the response in both latency and spiking frequency to the oriented edge is clearly more selective.
An implementation of bayesian inference (as described in Publications/Perrinet04tauc) using IF neurons
based on a Occam razor criteria (see Publications/Perrinet06cns)
- Laurent Perrinet. Efficient Source Detection Using Integrate-and-Fire Neurons. In ICANN 2005, LNCS 3696, pages 167--72. Springer-Verlag, Berlin Heidelberg, 2005, url =http://invibe.net/LaurentPerrinet/Publications/Perrinet05icann abstract
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