In search of an integrative method to study unconscious processing: an application of Bayesian and General Recognition Theory models to the processing of hierarchical patterns in the absence of awareness.

The dissociation between conscious and unconscious perception is one of the most controversial issues in the study of consciousness. Some authors argue in favor of the existence of high-level unconscious processing, while others claim that most of the results obtained can be explained by a mixture of methodological issues and erroneous (or at least questionable) assumptions about what can be considered non-conscious. Particularly, one of the most debated topics involves the way in which the awareness of the stimuli is assessed, with a wide variety of measures and associated methods being proposed throughout the history of the field. To address this question, in the present study an integrative paradigm was devised to assess the extent to which masked hierarchical stimuli can be processed in the absence of awareness. We combined a primming task where participants were presented with Navon-like hierarchical masked stimuli, with the use of subjective and objective awareness measures collected either in a separate block (offline) or trial-by-trial during the main task (online). The unconscious processing of the masked primes was then evaluated through two different novel model-based methods. A Bayesian modeling approach and a General Recognition Theory modeling approach. Crucially, these two approaches assess unconscious processing through different theoretical assumptions and employing different awareness measures. The results showed that although there is a high correlation between awareness measures, the use of alternative approaches under different theoretical assumptions to analyze unconscious processing, leads to somewhat diverging conclusions about the extent of the unconscious processing of the masked primes.