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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Autapses, or self-synapses, are neuronal connections where a neuron synapses onto itself.
  • Their role in modulating network-wide activity patterns, particularly bursting, remains incompletely understood.
  • Structural controllability offers a framework to analyze how network structure influences dynamic states.

Purpose of the Study:

  • To investigate the impact of structural autapses on driving network-wide bursting behavior.
  • To determine if neuronal controllability metrics influence the effect of autapses on bursting.
  • To explore the potential of autapses in controlling network dynamics in mammalian brain regions.

Main Methods:

  • Utilized a simple spiking model of neuronal activity.
  • Simulated the addition of autaptic connections to excitatory and inhibitory neurons.
  • Analyzed network activity patterns, focusing on spiking events and network-wide bursts.
  • Compared the effects of autapses on neurons with high average controllability versus high modal controllability.

Main Results:

  • Adding autapses to excitatory neurons increased spiking events and network-wide bursts.
  • Excitatory synapses demonstrated a greater contribution to bursting than inhibitory synapses.
  • Autapses on excitatory neurons with high average controllability led to higher burst frequencies compared to those with high modal controllability.
  • The presence of autapses on high-degree excitatory neurons reduced the number of autapses needed to induce bursting.

Conclusions:

  • Structural autapses play a significant role in driving and controlling network-wide bursting behavior.
  • Neuronal controllability, specifically average controllability, influences the impact of autapses on burst frequency.
  • Autaptic connections represent a potential mechanism for dynamic control of neural activity in various brain regions.
  • Findings suggest novel avenues for studying the neurophysiological correlates of structural controllability.