Membrane potential resonance frequency directly influences network frequency through electrical coupling

Yinbo Chen, Xinping Li, Horacio G. Rotstein, Farzan Nadim

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Oscillatory networks often include neurons with membrane potential resonance, exhibiting a peak in the voltage amplitude as a function of current input at a nonzero (resonance) frequency (fres). Although fres has been correlated to the network frequency (fnet) in a variety of systems, a causal relationship between the two has not been established. We examine the hypothesis that combinations of biophysical parameters that shift fres, without changing other attributes of the impedance profile, also shift fnet in the same direction. We test this hypothesis, computationally and experimentally, in an electrically coupled network consisting of intrinsic oscillator (O) and resonator (R) neurons. We use a two-cell model of such a network to show that increasing fres of R directly increases fnet and that this effect becomes more prominent if the amplitude of resonance is increased. Notably, the effect of fres on fnet is independent of the parameters that define the oscillator or the combination of parameters in R that produce the shift in fres, as long as this combination produces the same impedance vs. frequency relationship. We use the dynamic clamp technique to experimentally verify the model predictions by connecting a model resonator to the pacemaker pyloric dilator neurons of the crab Cancer borealis pyloric network using electrical synapses and show that the pyloric network frequency can be shifted by changing fres in the resonator. Our results provide compelling evidence that fres and resonance amplitude strongly influence fnet, and therefore, modulators may target these attributes to modify rhythmic activity.

Original languageEnglish (US)
Pages (from-to)1554-1563
Number of pages10
JournalJournal of neurophysiology
Volume116
Issue number4
DOIs
StatePublished - Oct 2016

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Physiology

Keywords

  • Computational modeling
  • Dynamic clamp
  • Oscillations
  • Resonance
  • Stomatogastric

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