Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis
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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-08-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.673369/full |
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| author | Chi-Hung Juan Chi-Hung Juan Chi-Hung Juan Kien Trong Nguyen Kien Trong Nguyen Wei-Kuang Liang Wei-Kuang Liang Andrew J. Quinn Andrew J. Quinn Yen-Hsun Chen Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Jia-Rong Yeh Mark W. Woolrich Mark W. Woolrich Anna C. Nobre Anna C. Nobre Anna C. Nobre Norden E. Huang Norden E. Huang |
| author_facet | Chi-Hung Juan Chi-Hung Juan Chi-Hung Juan Kien Trong Nguyen Kien Trong Nguyen Wei-Kuang Liang Wei-Kuang Liang Andrew J. Quinn Andrew J. Quinn Yen-Hsun Chen Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Jia-Rong Yeh Mark W. Woolrich Mark W. Woolrich Anna C. Nobre Anna C. Nobre Anna C. Nobre Norden E. Huang Norden E. Huang |
| author_sort | Chi-Hung Juan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T12:48:20Z |
| format | Article |
| id | doaj.art-9da117209753404eab9c470ece4be055 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-17T12:48:20Z |
| publishDate | 2021-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-9da117209753404eab9c470ece4be0552022-12-21T21:47:40ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2021-08-011510.3389/fnins.2021.673369673369Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral AnalysisChi-Hung Juan0Chi-Hung Juan1Chi-Hung Juan2Kien Trong Nguyen3Kien Trong Nguyen4Wei-Kuang Liang5Wei-Kuang Liang6Andrew J. Quinn7Andrew J. Quinn8Yen-Hsun Chen9Neil G. Muggleton10Neil G. Muggleton11Neil G. Muggleton12Neil G. Muggleton13Jia-Rong Yeh14Mark W. Woolrich15Mark W. Woolrich16Anna C. Nobre17Anna C. Nobre18Anna C. Nobre19Norden E. Huang20Norden E. Huang21Institute of Cognitive Neuroscience, National Central University, Taoyuan City, TaiwanCognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, TaiwanDepartment of Psychology, Kaohsiung Medical University, Kaohsiung City, TaiwanInstitute of Cognitive Neuroscience, National Central University, Taoyuan City, TaiwanFaculty of Electronics Engineering, Posts and Telecommunications Institute of Technology, Ho Chi Minh City, VietnamInstitute of Cognitive Neuroscience, National Central University, Taoyuan City, TaiwanCognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, TaiwanOxford Centre for Human Brain Activity, University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United KingdomInstitute of Cognitive Neuroscience, National Central University, Taoyuan City, TaiwanInstitute of Cognitive Neuroscience, National Central University, Taoyuan City, TaiwanCognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, TaiwanDepartment of Psychology, Goldsmiths, University of London, London, United KingdomInstitute of Cognitive Neuroscience, University College London, London, United KingdomCognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, TaiwanOxford Centre for Human Brain Activity, University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United KingdomOxford Centre for Human Brain Activity, University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United KingdomDepartment of Experimental Psychology, University of Oxford, Oxford, United KingdomCognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, Taiwan0Data Analysis and Application Laboratory, The First Institute of Oceanography, Qingdao, ChinaPatterns 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.https://www.frontiersin.org/articles/10.3389/fnins.2021.673369/fullthe dynamic visual entrainmentHolo-Hilbert spectral analysiscross-frequency couplingsteady-state visual evoked potentialphase-amplitude coupling |
| spellingShingle | Chi-Hung Juan Chi-Hung Juan Chi-Hung Juan Kien Trong Nguyen Kien Trong Nguyen Wei-Kuang Liang Wei-Kuang Liang Andrew J. Quinn Andrew J. Quinn Yen-Hsun Chen Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Neil G. Muggleton Jia-Rong Yeh Mark W. Woolrich Mark W. Woolrich Anna C. Nobre Anna C. Nobre Anna C. Nobre Norden E. Huang Norden E. Huang Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis Frontiers in Neuroscience the dynamic visual entrainment Holo-Hilbert spectral analysis cross-frequency coupling steady-state visual evoked potential phase-amplitude coupling |
| title | Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis |
| title_full | Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis |
| title_fullStr | Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis |
| title_full_unstemmed | Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis |
| title_short | Revealing the Dynamic Nature of Amplitude Modulated Neural Entrainment With Holo-Hilbert Spectral Analysis |
| title_sort | revealing the dynamic nature of amplitude modulated neural entrainment with holo hilbert spectral analysis |
| topic | the dynamic visual entrainment Holo-Hilbert spectral analysis cross-frequency coupling steady-state visual evoked potential phase-amplitude coupling |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2021.673369/full |
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