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Background synaptic activity is sparse in neocortex.

Jack Waters1, Fritjof Helmchen

  • 1Abteilung Zellphysiologie, Max-Planck-Institut für Medizinische Forschung, 69120 Heidelberg, Germany. jackwaters@northwestern.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
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Summary
This summary is machine-generated.

Neocortical pyramidal neurons experience weak synaptic background activity, contrary to previous beliefs. This sparse, primarily excitatory input during "Up states" enhances synaptic effectiveness, suggesting quieter resting brain networks.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cellular Neuroscience

Background:

  • Neurons are constantly exposed to background synaptic activity in vivo.
  • The precise levels of excitation and inhibition in this background activity remain debated.
  • This activity is believed to influence neural information processing.

Purpose of the Study:

  • To investigate the nature of background synaptic activity in neocortical pyramidal neurons.
  • To determine the contribution of excitatory and inhibitory inputs during spontaneous neuronal depolarizations.
  • To assess the impact of synaptic background on neural information processing.

Main Methods:

  • Whole-cell recordings were performed in anesthetized rats.
  • Spontaneous depolarizations (Up states) in neocortical pyramidal neurons were analyzed.
  • Synaptic conductance changes and input resistance were measured.

Main Results:

  • Up states are driven by sparse, predominantly excitatory synaptic activity (less than five inputs/ms, ~10% inhibitory).
  • The mean synaptic conductance change is small (<10 nS at the soma).
  • Anomalous rectification leads to a net increase in input resistance during Up states, enhancing synaptic efficacy.

Conclusions:

  • Neocortical networks are relatively quiet at rest.
  • The influence of synaptic background activity on neural processing is weaker than previously assumed.
  • Sparse excitatory inputs during Up states effectively depolarize neurons due to network properties.