Skip to content

Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness

Vitor Manuel Dinis Pereira

arXiv Preprint Archive December 26, 2020 Peer reviewed via arXiv

Summary

The author argues that while there are no brain electrophysiological correlates of subjective experience (the hard problem of consciousness), there are correlates in occipital and left temporal regions. However, standard frequency analysis methods like Wavelet or Fast Fourier Transforms cannot capture the instantaneous phase changes in event-related brain potentials, which can produce transient infinite frequencies. The report presents Empirical Mode Decomposition with Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform as a suitable method for analyzing such instantaneous changes.

Study at a glance

Design original research report
Key finding Empirical Mode Decomposition with Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform is a suitable method for analyzing instantaneous phase changes in event-related brain potentials.

Abstract

Given the hard problem of consciousness (Chalmers, 1995) there are no brain electrophysiological correlates of the subjective experience (the felt quality of redness or the redness of red, the experience of dark and light, the quality of depth in a visual field, the sound of a clarinet, the smell of mothball, bodily sensations from pains to orgasms, mental images that are conjured up internally, the felt quality of emotion, the experience of a stream of conscious thought or the phenomenology of thought). However, there are brain occipital and left temporal electrophysiological correlates of the subjective experience (Pereira, 2015). Notwithstanding, as evoked signal, the change in event-related brain potentials phase (frequency is the change in phase over time) is instantaneous, that is, the frequency will transiently be infinite: a transient peak in frequency (positive or negative), if any, is instantaneous in electroencephalogram averaging or filtering that the event-related brain potentials required and the underlying structure of the event-related brain potentials in the frequency domain cannot be accounted, for example, by the Wavelet Transform (WT) or the Fast Fourier Transform (FFT) analysis, because they require that frequency is derived by convolution rather than by differentiation. However, as I show in the current original research report, one suitable method for analyse the instantaneous change in event-related brain potentials phase and accounted for a transient peak in frequency (positive or negative), if any, in the underlying structure of the event-related brain potentials is the Empirical Mode Decomposition with post processing (Xie et al., 2014) Ensemble Empirical Mode Decomposition (postEEMD) and Hilbert-Huang Transform (HHT).

Tags

Comments

No comments yet.

Log in to comment