Face processing using one spike per neurone. Rullen, R. V.; Gautrais, J.; Delorme, A.; and Thorpe, S. Biosystems, 48(1-3):229-239, Centre de Recherche Cerveau et Cognition, UMR 5549, Toulouse, France., Sep, 1998.
abstract   bibtex   
The speed with which neurones in the monkey temporal lobe can respond selectively to the presence of a face implies that processing may be possible using only one spike per neurone, a finding that is problematic for conventional rate coding models that need at least two spikes to estimate interspike interval. One way of avoiding this problem uses the fact that integrate-and-fire neurones will tend to fire at different times, with the most strongly activated neurones firing first (Thorpe, 1990, Parallel Processing in Neural Systems). Under such conditions, processing can be performed by using the order in which cells in a particular layer fire as a code. To test this idea, we have explored a range of architectures using SpikeNET (Thorpe and Gautrais, 1997, Neural Information Processing Systems, 9), a simulator designed for modelling large populations of integrate-and-fire neurones. One such network used a simple four-layer feed-forward architecture to detect and localise the presence of human faces in natural images. Performance of the model was tested with a large range of grey-scale images of faces and other objects and was found to be remarkably good by comparison with more classic image processing techniques. The most remarkable feature of these results is that they were obtained using a purely feed-forward neural network in which none of the neurones fired more than one spike (thus ruling out conventional rate coding mechanisms). It thus appears that the combination of asynchronous spike propagation and rank order coding may provide an important key to understanding how the nervous system can achieve such a huge amount of processing in so little time.
@article{ VanRullen_etal98,
  author = {R. Van Rullen and J. Gautrais and A. Delorme and S. Thorpe},
  title = {Face processing using one spike per neurone},
  journal = {Biosystems},
  year = {1998},
  volume = {48},
  pages = {229-239},
  number = {1-3},
  month = {Sep},
  abstract = {The speed with which neurones in the monkey temporal lobe can respond
	selectively to the presence of a face implies that processing may
	be possible using only one spike per neurone, a finding that is problematic
	for conventional rate coding models that need at least two spikes
	to estimate interspike interval. One way of avoiding this problem
	uses the fact that integrate-and-fire neurones will tend to fire
	at different times, with the most strongly activated neurones firing
	first (Thorpe, 1990, Parallel Processing in Neural Systems). Under
	such conditions, processing can be performed by using the order in
	which cells in a particular layer fire as a code. To test this idea,
	we have explored a range of architectures using SpikeNET (Thorpe
	and Gautrais, 1997, Neural Information Processing Systems, 9), a
	simulator designed for modelling large populations of integrate-and-fire
	neurones. One such network used a simple four-layer feed-forward
	architecture to detect and localise the presence of human faces in
	natural images. Performance of the model was tested with a large
	range of grey-scale images of faces and other objects and was found
	to be remarkably good by comparison with more classic image processing
	techniques. The most remarkable feature of these results is that
	they were obtained using a purely feed-forward neural network in
	which none of the neurones fired more than one spike (thus ruling
	out conventional rate coding mechanisms). It thus appears that the
	combination of asynchronous spike propagation and rank order coding
	may provide an important key to understanding how the nervous system
	can achieve such a huge amount of processing in so little time.},
  address = {Centre de Recherche Cerveau et Cognition, UMR 5549, Toulouse, France.},
  keywords = {*Action Potentials | *Face | Female | Human | Male | Models, Neurological
	| Neurons/*physiology | *Visual Perception | 1999/01/14 00:01}
}
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