Inhibitory conductance dynamics in cortical neurons during activated states

  • Pospischil M
  • Piwkowska Z
  • Rudolph M
 et al. 
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During activated states in vivo, neocortical neurons are subject to intense synaptic activity and high-amplitude membrane potential (Vm) fluctuations. These "high-conductance" states may strongly affect the integrative properties of cortical neurons. We investigated the responsiveness of cortical neurons during different states using a combination of computational models and in vitro experiments (dynamic-clamp) in the visual cortex of adult guinea pigs. Spike responses were monitored following stochastic conductance injection in both experiments and models. We found that cortical neurons can operate in a continuum between two different modes: during states with equal excitatory and inhibitory conductances, the firing is mostly correlated with an increase in excitatory conductance, which is a rather classic scenario. In contrast, during states dominated by inhibition, the firing is mostly related to a decrease in inhibitory conductances (dis-inhibition). This model prediction was tested experimentally using dynamic-clamp, and the same modes of firing were identified. We also found that the signature of spikes evoked by dis-inhibition is a transient drop of the total membrane conductance prior to the spike, which is typical of states with dominant inhibitory conductances. Such a drop should be identifiable from intracellular recordings in vivo, which would provide an important test for the presence of inhibition-dominated states. In conclusion, we show that in artificial activated states, not only inhibition can determine the conductance state of the membrane, but inhibitory inputs may also have a determinant influence on spiking. Future analyses and models should focus on verifying if such a determinant influence of inhibitory conductance dynamics is also present in vivo. © 2006 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Conductance dynamics
  • Dynamic-clamp
  • Spike-triggered average

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