Neuronal Noise pp 387-404 | Cite as

Conclusions and Perspectives

  • Alain Destexhe
  • Michelle Rudolph-Lilith
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 8)


In this book, we have overviewed several recent developments of the exploration of the integrative properties of central neurons in the presence of “noise,” with an emphasis on the largest noise source in neurons, synaptic noise. Investigating the properties of neurons in the presence of intense synaptic activity is a popular theme in modeling studies, starting from seminal work (Barrett and Crill 1974; Barrett 1975; Bryant and Segundo 1976; Holmes and Woody 1989), which was followed by compartmental model studies (Bernander et al. 1991; Rapp et al. 1992; De Schutter and Bower 1994). In the last two decades, significant progress was made in several aspects of this problem. The different chapters of this book have overviewed different facets of this exploration. In this final chapter, we first summarize the different facets of synaptic noise, as overviewed in the different chapters. We then speculate on how “noise,” and in particular “noisy states,” is a central aspect of neuronal computations.


Network Activity Integrative Property Synaptic Conductance Neuronal Responsiveness Primary Sensory Cortex 
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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Unité de Neuroscience, Information et ComplexitéCNRS, UPR-2191Gif-sur-YvetteFrance

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