Ultra-Rapid Scene Categorization with a Wave of Spikes

  • Simon Thorpe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)


Recent experimental work has shown that the primate visual system can analyze complex natural scenes in only 100–150 ms. Such data, when combined with anatomical and physiological knowledge, seriously constrains current models of visual processing. In particular, it suggests that a lot of processing can be achieved using a single feed-forward pass through the visual system, and that each processing layer probably has no more than around 10 ms before the next stage has to respond. In this time, few neurons will have generated more than one spike, ruling out most conventional rate coding models. We have been exploring the possibility of using the fact that strongly activated neurons tend to fire early and that information can be encoded in the order in which a population of cells fire. These ideas have been tested using SpikeNet, a computer program that simulates the activity of very large networks of asynchronously firing neurons. The results have been extremely promising, and we have been able to develop artificial visual systems capable of processing complex natural scenes in real time using standard computer hardware (see


Visual System Firing Rate Human Visual System Natural Image Natural Scene 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Simon Thorpe
    • 1
    • 2
  1. 1.Centre de Recherche Cerveau & CognitionToulouseFrance
  2. 2.SpikeNet Technology S.A.R.L.RevelFrance

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