The frequency architecture of brain and brain body oscillations: an analysis

Eur J Neurosci. 2018 Oct;48(7):2431-2453. doi: 10.1111/ejn.14192.

Abstract

Research on brain oscillations has brought up a picture of coupled oscillators. Some of the most important questions that will be analyzed are, how many frequencies are there, what are the coupling principles, what their functional meaning is, and whether body oscillations follow similar coupling principles. It is argued that physiologically, two basic coupling principles govern brain as well as body oscillations: (i) amplitude (envelope) modulation between any frequencies m and n, where the phase of the slower frequency m modulates the envelope of the faster frequency n, and (ii) phase coupling between m and n, where the frequency of n is a harmonic multiple of m. An analysis of the center frequency of traditional frequency bands and their coupling principles suggest a binary hierarchy of frequencies. This principle leads to the foundation of the binary hierarchy brain body oscillation theory. Its central hypotheses are that the frequencies of body oscillations can be predicted from brain oscillations and that brain and body oscillations are aligned to each other. The empirical evaluation of the predicted frequencies for body oscillations is discussed on the basis of findings for heart rate, heart rate variability, breathing frequencies, fluctuations in the BOLD signal, and other body oscillations. The conclusion is that brain and many body oscillations can be described by a single system, where the cross talk - reflecting communication - within and between brain and body oscillations is governed by m : n phase to envelope and phase to phase coupling.

Keywords: body oscillations; brain oscillations; cross-frequency coupling; oscillatory hierarchy; phase coupling.

Publication types

  • Review

MeSH terms

  • Animals
  • Behavior / physiology*
  • Brain / physiology*
  • Electroencephalography / methods
  • Excitation Contraction Coupling
  • Humans
  • Memory / physiology*
  • Signal Processing, Computer-Assisted*