The amplitude modulation of Gaussian noise is a fingerprint of Gaussianity

Manuel, Hidalgo, Víctor; Letelier, Juan-Carlos; Díaz, Javier

doi:10.48550/arxiv.2203.16253

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Here, we used envelope analysis to characterize the human alpha rhythm. Envelope analysis offers an elegant time-domain method to assess Gaussianity based on the study of the envelope signal (Hidalgo et al, 2022). Previous studies regarding EEG Gaussianity can now be reassessed by envelope analysis (e.g.…”

Section: Discussionmentioning

confidence: 99%

Envelope analysis of the human alpha rhythm reveals EEG Gaussianity

Díaz²,

Mpodozis³

et al. 2021

Preprint

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The origin of the human alpha rhythm has been a matter of debate since Lord Adrian attributed it to synchronous neural populations in the occipital cortex. While some authors have pointed out the Gaussian characteristics of the alpha rhythm, their results have been repeatedly disregarded in favor of Adrian′s interpretation; even though the first EEG Gaussianity reports can be traced back to the origins of EEG. Here we revisit this problem using the envelope analysis — a method that relies on the fact that the coefficient of variation of the envelope (CVE) for continuous-time zero-mean Gaussian white noise (as well as for any filteredsub-band) is equal to √(4−π)/π≈0.523, thus making the CVE a fingerprint for Gaussianity. As a consequence, any significant deviation from Gaussianity is linked to synchronous neural dynamics. Low-CVE signals come from phase-locking dynamics, while mid-CVE signals constitute Gaussian noise. High-CVE signals have been linked to unsteady dynamics in populations of nonlinear oscillators. We analyzed occipital EEG and iEEG data from massive public databases and the order parameter of a population of weakly coupled oscillators using the envelope analysis. Our results showed that the human alpha rhythm can be characterized as a rhythmic, Gaussian, or pulsating signal due to intra- and inter-subject variability. Furthermore, Fourier analysis showed that the canonical spectral peak at≈10[Hz] is present in all three CVE classes, thus demonstrating that this same peak can be produced by rhythms, Gaussian noise, and pulsating ripples. Alpha-like signals obtained from a population of non-linear oscillators showed a different CVE depending only on the coupling constant, suggesting that the same neural population can produce the amplitude modulation patterns observed in experimental data. iEEG data, however, was found to be mostly Gaussian, specially the signals recorded from the calcarine cortex. These results suggest that a new interpretation for EEG event-related synchronization/desynchronization (ERS/ERD) may be needed. Envelope analysis constitutes a novel complement to traditional Fourier-based methods for neural signal analysis relating amplitude modulations (CVE) to signal energy.

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Section: Discussionmentioning

confidence: 99%

Envelope analysis of the human alpha rhythm reveals EEG Gaussianity

Díaz²,

Mpodozis³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

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Envelope Analysis of the Human Alpha Rhythm Reveals EEG Gaussianity

Manuel

Díaz

Mpodozis

et al. 2023

IEEE Trans. Biomed. Eng.

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The origin of the human alpha rhythm has been a matter of debate since Lord Adrian attributed it to synchronous neural populations in the occipital cortex. Although some authors have pointed out the Gaussian characteristics of the alpha rhythm, their results have been repeatedly disregarded in favor of Adrian's interpretation; even though the first EEG Gaussianity reports can be traced back to the origins of the field.Here we revisit this problem using the envelope analysis -a method that relies on the fact that the coefficient of variation of the envelope (CVE) for continuous-time zero-mean Gaussian noise (as well as for any filtered sub-band) is equal to (4 − π)/π ≈ 0.523, thus making the CVE a fingerprint for Gaussianity. As a consequence, any significant deviation from (4 − π)/π is linked to synchronous neural dynamics. We analyzed occipital EEG and iEEG data from massive public databases. Our results showed the human alpha rhythm can be characterized either as a synchronous or as a Gaussian signal based on the value of its CVE.Furthermore, Fourier analysis showed the canonical spectral peak at ≈ 10[Hz] is present in both the synchronous and Gaussian cases, thus demonstrating this same peak can be produced by different underlying neural dynamics. This study confirms the original interpretation of Adrian regarding the origin of the alpha rhythm but also opens the door for the study of Gaussianity in brain dynamics. These results suggest a broader interpretation for event-related synchronization/desynchronization (ERS/ERD) may be needed. Envelope analysis constitutes a novel complement to Fourier-based methods for neural signal analysis relating amplitude modulation patterns (CVE) to signal energy.

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The amplitude modulation of Gaussian noise is a fingerprint of Gaussianity

Cited by 2 publications

References 12 publications

Envelope analysis of the human alpha rhythm reveals EEG Gaussianity

Envelope analysis of the human alpha rhythm reveals EEG Gaussianity

Envelope Analysis of the Human Alpha Rhythm Reveals EEG Gaussianity

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