Synaptic noise improves detection of subthreshold signals in hippocampal CA1 neurons

J Neurophysiol. 2001 Sep;86(3):1104-12. doi: 10.1152/jn.2001.86.3.1104.


Stochastic resonance (SR) is a phenomenon whereby the detection of a low-level signal is enhanced in a nonlinear system by the introduction of noise. Studies of the effects of SR in neurons have suggested that noise could play a prominent role in improving detection of small signals. Most experimental SR research has focused on the role of noise in sensory neurons using physiological stimuli. Computer simulations show that signal detection in hippocampal neurons is improved by the addition of physiological levels of noise applied extracellularly to synaptic inputs. These results were confirmed experimentally. We now report that endogenous noise sources can also improve signal detection. The noise source was generated by modulating the random synaptic activity on the apical dendrites of CA1 cells in rat hippocampal slices using subthreshold cathodic current. Intracellular recordings of CA1 cells showed that even small increases of synaptic noise are able to greatly improve the detection of an independent, synaptic, subthreshold stimulus as predicted by the simulations. The noise variance in the CA1 cell was compared with the resting variance and with variance changes caused by several endogenous noise sources. In all cases, the increased noise variance was well within the physiological range. These results were supplemented and analyzed with a CA1 computer model. The improved signal detection with small amounts of endogenous noise suggests that the diverse inputs to CA1 are able to improve detection of subthreshold synaptic signals and could provide a means to modulate detection of specific inputs in the hippocampus.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / physiology
  • Animals
  • Computer Simulation
  • Denervation
  • Electrodes
  • Excitatory Postsynaptic Potentials / physiology
  • Hippocampus / cytology*
  • Models, Neurological*
  • Neurons / physiology*
  • Nonlinear Dynamics
  • Organ Culture Techniques
  • Rats
  • Rats, Sprague-Dawley
  • Stochastic Processes
  • Synapses / physiology*