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

TL;DR

This paper investigates the electrophysiological correlates of subjective conscious experience, focusing on instantaneous amplitude and frequency oscillations in occipital and left temporal brain regions, using advanced signal analysis methods.

Contribution

It introduces the use of Empirical Mode Decomposition with post processing and Hilbert-Huang Transform to analyze transient frequency peaks in event-related potentials related to consciousness.

Findings

Identifies transient frequency peaks linked to conscious experience.

Demonstrates the effectiveness of EEMD and HHT in analyzing EEG signals.

Provides new insights into neural correlates of consciousness.

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).