Revealing the dynamic nature of amplitude modulated neural entrainment with Holo-Hilbert spectral analysis

Chi Hung Juan*, Kien Trong Nguyen*, Wei Kuang Liang, Andrew J. Quinn, Yen Hsun Chen, Neil G. Muggleton, Jia Rong Yeh, Mark W. Woolrich, Anna C. Nobre, Norden E. Huang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
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Patterns in external sensory stimuli can rapidly entrain neuronally generated oscillations observed in electrophysiological data. Here, we manipulated the temporal dynamics of visual stimuli with cross-frequency coupling (CFC) characteristics to generate steady-state visual evoked potentials (SSVEPs). Although CFC plays a pivotal role in neural communication, some cases reporting CFC may be false positives due to non-sinusoidal oscillations that can generate artificially inflated coupling values. Additionally, temporal characteristics of dynamic and non-linear neural oscillations cannot be fully derived with conventional Fourier-based analyses mainly due to trade off of temporal resolution for frequency precision. In an attempt to resolve these limitations of linear analytical methods, Holo-Hilbert Spectral Analysis (HHSA) was investigated as a potential approach for examination of non-linear and non-stationary CFC dynamics in this study. Results from both simulation and SSVEPs demonstrated that temporal dynamic and non-linear CFC features can be revealed with HHSA. Specifically, the results of simulation showed that the HHSA is less affected by the non-sinusoidal oscillation and showed possible cross frequency interactions embedded in the simulation without any a priori assumptions. In the SSVEPs, we found that the time-varying cross-frequency interaction and the bidirectional coupling between delta and alpha/beta bands can be observed using HHSA, confirming dynamic physiological signatures of neural entrainment related to cross-frequency coupling. These findings not only validate the efficacy of the HHSA in revealing the natural characteristics of signals, but also shed new light on further applications in analysis of brain electrophysiological data with the aim of understanding the functional roles of neuronal oscillation in various cognitive functions.

Original languageEnglish
Article number673369
Number of pages18
JournalFrontiers in Neuroscience
Publication statusPublished - 5 Aug 2021

Bibliographical note

Funding Information:
This work was sponsored by the Ministry of Science and Technology, Taiwan (Grant Nos. 109-2639-H-008-001-ASP, 110-2321-B-037-003, 108-2321-B-075-004-MY2, and 107-2628-H-008-002-MY3) and the Taiwan Ministry of Education’s “Academic Strategic Alliance: Taiwan and Oxford University” project grant (MOE Oxford-NCU collaborative project). This work was supported by a Wellcome Trust Senior Investigator Award (104571/Z/14/Z) and a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award (220020448) to N, a Wellcome Investigator Award to MW (106183/Z/14/Z), the Medical Research Council (RG94383/RG89702), and the NIHR Oxford Health Biomedical Research Centre. The Wellcome Centre for Integrative Neuroimaging was supported by core funding from the Wellcome Trust (203139/Z/16/Z).

Publisher Copyright:
© Copyright © 2021 Juan, Nguyen, Liang, Quinn, Chen, Muggleton, Yeh, Woolrich, Nobre and Huang.


  • cross-frequency coupling
  • Holo-Hilbert spectral analysis
  • phase-amplitude coupling
  • steady-state visual evoked potential
  • the dynamic visual entrainment

ASJC Scopus subject areas

  • General Neuroscience


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