The study of consciousness faces unique challenges because it investigates subjective experience, which is accessible only from a first-person perspective, unlike objective third-person phenomena in other sciences. This article reviews historical and contemporary efforts to measure consciousness and its absence, focusing on two main approaches: objective performance-based measures and subjective report-based measures of awareness. It compares their advantages and disadvantages, evaluates them against methodological criteria, and discusses transforming both into a common sensitivity measure (d') for comparison. New approaches are explored, including Bayesian models to support claims of absent awareness and machine-learning decoding models, alongside future challenges such as measuring qualia—the qualitative contents of awareness.
Working memory may operate on unconscious perceptual contents, though it remains linked to conscious perception. A large, multisite replication (19 labs, 531 participants, 720 trials) of Soto et al. (2011) found above-chance accuracy (.55) on a visual discrimination task when participants reported not seeing the subliminal Gabor grating. Performance correlated positively with cue detection sensitivity (r = .228), and the regression intercept was significantly above chance (β₀ = .521). The study provides an open-access dataset and confirms that measures were reliable and valid, supporting the existence of unconscious working memory.