Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches?

  title={Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches?},
  author={Andreas Bruns},
  journal={Journal of Neuroscience Methods},
  • A. Bruns
  • Published 30 August 2004
  • Mathematics
  • Journal of Neuroscience Methods

Estimation of narrowband amplitude and phase from electrophysiology signals for phase-amplitude coupling studies: a comparison of methods

This work investigates how these two approaches perform in detecting the phenomenon of phase-amplitude coupling (PAC), whereby the amplitude of a high- frequency signal is driven by the phase of a low-frequency signal.

Cycle-by-cycle analysis of neural oscillations

A new analysis framework is presented, complementary to Fourier analysis, that quantifies cycle-by-cycle time-domain features of neural oscillations, and is validated on simulated noisy signals with oscillatory bursts and outperforms conventional metrics.

Measuring the average power of neural oscillations

Extensions of common approaches that are better suited for the physiological reality of how neural oscillations often manifest: as nonstationary, high-power bursts, rather than sustained rhythms are introduced.

A better way to define and describe Morlet wavelets for time-frequency analysis

This paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (as full-width at half-maximum).

Methodological Framework for EEG Feature Selection Based on Spectral and Temporal Profiles

The results indicate the ability of the proposed methodological framework to correctly identify and select the most prominent channels in terms of “activity encapsulation,” which are thought to be the most significant ones.

Cycle-by-cycle analysis of neural oscillations.

A new analysis framework is presented that is complementary to existing Fourier- and Hilbert-transform based approaches that quantifies oscillatory features in the time domain, on a cycle-by-cycle basis and is validated in simulation and against experimental recordings of patients with Parkinson's disease.

Application of time-frequency analysis in investigating non-phase locked components of EEG

: Since the introduction of the time-frequency analysis technique into the field of EEG data in the 1980’s, researchers can excavate non-phase locked components in EEG signals, overcoming the



Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence

The Fourier analysis of biological transients

  • C. Harris
  • Biology
    Journal of Neuroscience Methods
  • 1998

Measuring phase synchrony in brain signals

It is argued that whereas long‐scale effects do reflect cognitive processing, short‐scale synchronies are likely to be due to volume conduction, and ways to separate such conduction effects from true signal synchrony are discussed.

Performance of different synchronization measures in real data: a case study on electroencephalographic signals.

It is claimed that the applied measures used in the synchronization between left and right hemisphere rat electroencephalographic channels are valuable for the study of synchronization in real data and in the particular case of EEG signals their use as complementary variables could be of clinical relevance.

Fine temporal resolution of analytic phase reveals episodic synchronization by state transitions in gamma EEGs.

The results provide support for the hypothesis that neurons in mesoscopic neighborhoods in sensory cortices self-organize their activity by synaptic interactions into wave packets that have spatial patterns of amplitude and phase modulation of their spatially coherent carrier waves in the gamma range and that form and dissolve aperiodically at rates in and below the theta range.

Perception's shadow: long-distance synchronization of human brain activity

It is shown for the first time, to the knowledge, that only face perception induces a long-distance pattern of synchronization, corresponding to the moment of perception itself and to the ensuing motor response.

Amplitude envelope correlation detects coupling among incoherent brain signals

Amplitude envelope correlation (AEC) is applied to subdural recordings from humans performing a visual delayed match‐to‐sample task and shows that coherence and AEC are adapted to different cortical mechanisms of short‐ and long‐range interactions, respectively.

Task-related coupling from high- to low-frequency signals among visual cortical areas in human subdural recordings.

  • A. BrunsR. Eckhorn
  • Psychology
    International journal of psychophysiology : official journal of the International Organization of Psychophysiology
  • 2004

A new method for quantifying EEG event-related desynchronization:amplitude envelope analysis.