Resonance or integration? Self-sustained dynamics and excitability of neural microcircuits

Raul C. Muresan, Cristina Savin

Research output: Contribution to journalArticlepeer-review


We investigated spontaneous activity and excitability in large networks of artificial spiking neurons. We compared three different spiking neuron models: integrate-and-fire (IF), regular-spiking (RS), and resonator (RES). First, we show that different models have different frequency-dependent response properties, yielding large differences in excitability. Then, we investigate the responsiveness of these models to a single afferent inhibitory/excitatory spike and calibrate the total synaptic drive such that they would exhibit similar peaks of the postsynaptic potentials (PSP). Based on the synaptic calibration, we build large microcircuits of IF, RS, and RES neurons and show that the resonance property favors homeostasis and self-sustainability of the network activity. On the other hand, integration produces instability while it endows the network with other useful properties, such as responsiveness to external inputs. We also investigate other potential sources of stable self-sustained activity and their relation to the membrane properties of neurons. We conclude that resonance and integration at the neuron level might interact in the brain to promote stability as well as flexibility and responsiveness to external input and that membrane properties, in general, are essential for determining the behavior of large networks of neurons.

Original languageEnglish (US)
Pages (from-to)1911-1930
Number of pages20
JournalJournal of neurophysiology
Issue number3
StatePublished - Mar 2007

ASJC Scopus subject areas

  • General Neuroscience
  • Physiology


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