Confidence in consciousness research

Tactile shape discrimination for moving stimuli

In this study, we explored spatial-temporal dependencies and their impact on the tactile perception of moving objects. Building on previous research linking visual perception and human movement, we examined if an imputed motion mechanism operates within the tactile modality. We focused on how biological coherence between space and time, characteristic of human movement, influences tactile perception. An experiment was designed wherein participants were stimulated on their right palm with tactile patterns, either ambiguous (incongruent conditions) or non-ambiguous (congruent conditions) relative to a biological motion law (two-thirds power law) and asked to report perceived shape and associated confidence. Our findings reveal that introducing ambiguous tactile patterns (1) significantly diminishes tactile discrimination performance, implying motor features of shape recognition in vision are also observed in the tactile modality, and (2) undermines participants' response confidence, uncovering the accessibility degree of information determining the tactile percept's conscious representation. Analysis based on the Hierarchical Drift Diffusion Model unveiled the sensitivity of the evidence accumulation process to the stimulus's informational ambiguity and provides insight into tactile perception as predictive dynamics for reducing uncertainty. These discoveries deepen our understanding of tactile perception mechanisms and underscore the criticality of predictions in sensory information processing.

The cognitive reality monitoring network and theories of consciousness

Theories of consciousness abound. However, it is difficult to arbitrate reliably among competing theories because they target different levels of neural and cognitive processing or anatomical loci, and only some were developed with computational models in mind. In particular, theories of consciousness need to fully address the three levels of understanding of the brain proposed by David Marr: computational theory, algorithms and hardware. Most major theories refer to only one or two levels, often indirectly. The cognitive reality monitoring network (CRMN) model is derived from computational theories of mixture-of-experts architecture, hierarchical reinforcement learning and generative/inference computing modules, addressing all three levels of understanding. A central feature of the CRMN is the mapping of a gating network onto the prefrontal cortex, making it a prime coding circuit involved in monitoring the accuracy of one's mental states and distinguishing them from external reality. Because the CRMN builds on the hierarchical and layer structure of the cerebral cortex, it may connect research and findings across species, further enabling concrete computational models of consciousness with new, explicitly testable hypotheses. In sum, we discuss how the CRMN model can help further our understanding of the nature and function of consciousness.

Masked priming under the Bayesian microscope: Exploring the integration of local elements into global shape through Bayesian model comparison

To investigate whether local elements are grouped into global shapes in the absence of awareness, we introduced two different masked priming designs (e.g., the classic dissociation paradigm and a trial-wise probe and prime discrimination task) and collected both objective (i.e., performance based) and subjective (using the perceptual awareness scale [PAS]) awareness measures. Prime visibility was manipulated using three different prime-mask stimulus onset asynchronies (SOAs) and an unmasked condition. Our results showed that assessing prime visibility trial-wise heavily interfered with masked priming preventing any prime facilitation effect. The implementation of Bayesian regression models, which predict priming effects for participants whose awareness levels are at chance level, provided strong evidence in favor of the hypothesis that local elements group into global shape in the absence of awareness for SOAs longer than 50 ms, suggesting that prime-mask SOA is a crucial factor in the processing of the global shape without awareness.