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

There are no brain electrophysiological correlates of subjective experience, though occipital and left temporal correlates exist. Event-related brain potentials (ERPs) involve instantaneous phase changes, producing transient infinite frequency peaks that cannot be captured by standard methods like Wavelet Transform or Fast Fourier Transform, which rely on convolution. This original research shows that Empirical Mode Decomposition with post-processing Ensemble Empirical Mode Decomposition and the Hilbert-Huang Transform can analyze these instantaneous phase changes and account for transient frequency peaks in ERP structure.

Study at a glance

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).