Testing the prevalent consistency assumption of (un)conscious processing through massive feature extraction of inattentional blindness electroencephalography

Abstract

Freud’s iceberg metaphor has long been used to describe (un)consciousness: a huge unconsciousness supports a tiny tip of consciousness. Inspired by this, research has assumed that unconscious discriminative processing persists into consciousness, employing contrastive analysis to isolate the neural correlates of consciousness (NCC). For example, in electroencephalography (EEG) studies, features of time series are related to unconscious sensory processes if they discriminate presence of invisible visual stimuli. According to the consistency assumption, they should also discriminate these stimuli when they become visible and task relevant. Despite its prevalence, the assumption has never been directly questioned, and its general validity for EEG studies, regardless of the exact analysis method employed, is unclear. This registered report aims to explicitly test this assumption by utilising a toolbox providing over 7000 time-series features from various analysis methods from a wide range of research fields. We apply these features to an inattentional blindness paradigm and identify features which discriminate presence of a visual stimulus which is initially invisible, and then later visible and task relevant. We track the performance of each feature in discriminating the presence of the stimulus as it varies in visibility, and use a Bayesian framework to test whether the consistency assumption is likely to be valid. Pilot results suggest it is likely invalid across the range of time-series features.