State-dependent entrainment of cerebellar nuclear neurons to the local field potential during voluntary movements

Yuval Baumel, Dana Cohen

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Understanding the relationship between the local field potential (LFP) and single neurons is essential if we are to understand network dynamics and the entrainment of neuronal activity. Here, we investigated the interaction between the LFP and single neurons recorded in the rat cerebellar nuclei (CN), which are part of the sensorimotor network, in freely moving rats. During movement, the LFP displayed persistent oscillations in the theta band frequency, whereas CN neurons displayed intermittent oscillations in the same frequency band contingent on the instantaneous LFP power; the neurons oscillated primarily when the concurrent LFP power was either high or low. Quantification of the relative instantaneous frequency and phase locking showed that CN neurons exhibited phase locked rhythmic activity at a frequency similar to that of the LFP or at a shifted frequency during high and low LFP power, respectively. We suggest that this nonlinear interaction between cerebellar neurons and the LFP power, which occurs solely during movement, contributes to the shaping of cerebellar output patterns. NEW & NOTEWORTHY We studied the interaction between single neurons and the LFP in the cerebellar nuclei of freely moving rats. We show that during movement, the neurons oscillated in the theta frequency band contingent on the concurrent LFP oscillation power in the same band; the neurons oscillated primarily when the LFP power was either high or low. We are the first to demonstrate a nonlinear, state-dependent entrainment of single neurons to the LFP.

Original languageEnglish
Pages (from-to)112-122
Number of pages11
JournalJournal of Neurophysiology
Volume126
Issue number1
DOIs
StatePublished - 1 Jul 2021

Bibliographical note

Publisher Copyright:
Copyright © 2021 the American Physiological Society.

Keywords

  • Chronic recording
  • LFP
  • Oscillations
  • Phase locking
  • Sensorimotor network

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