Estimation of synaptic conductances and their variances from intracellular recordings of neocortical neurons in vivo

Michael Rudolph, J. Guillaume Pelletier, Denis Paré, Alain Destexhe

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

During intense network activity, neocortical neurons are in a "high-conductance" state. To estimate the respective contributions of excitatory and inhibitory conductances in generating such states, we combined computational models with intracellular recordings obtained in cat parietal cortex in vivo. Fitting a fluctuating-conductance model to the recordings revealed that inhibitory conductances are dominant (several times larger than excitation). Conductance variance (i.e., the "noise") was also larger for inhibition, indicating that inhibitory dynamics have a pronounced impact on membrane potential fluctuations. We conclude that the synaptic bombardment of neocortical neurons in vivo is not excitatory, but mostly determined by inhibitory conductances.

Original languageEnglish (US)
Pages (from-to)387-392
Number of pages6
JournalNeurocomputing
Volume58-60
DOIs
StatePublished - Jun 1 2004

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Keywords

  • Cerebral cortex
  • Stochastic systems
  • Subthreshold activity
  • Synaptic noise

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