How brains build higher order representations of uncertainty
Philosophy and the Mind Sciences February 27, 2026 Megan A. K. Peters, Hojjat Azimi Asrari 1 citation
Higher-order representations encode information about an agent's own first-order representations, such as their reliability or structure, and are thought to be critical for metacognition, learning, and consciousness. The authors propose that metacognitive estimates of uncertainty reflect a read-out of higher-order "posteriors" from a Bayesian perspective. These posteriors combine higher-order "likelihoods" (current uncertainty evidence) and "priors" (learned distributions over expected uncertainty). The paper discusses emerging analytical approaches to examine the estimation processes and neural correlates of these under-explored components of experienced uncertainty.