Biology subjects

Constant, M.

Publications and source records attributed to Constant, M..

2 recordsLinked to original sources

bioRxiv2022

Prior information differentially affects discrimination decisions and subjective confidence reports

According to Bayesian models, both decisions and confidence are based on the same precision-weighted integration of prior expectations ("priors") and incoming information ("likelihoods"). This assumes that priors are integrated optimally and equally in decisions and confidence, which has not been tested. In two experiments, we quantitatively assessed how priors inform both decisions and confidence. With a gamified dual-decision task we controlled the strength of priors and likelihoods to create pairs of conditions that were matched in posterior information, but differed on whether the prior or likelihood was more informative. We found that priors were underweighted in discrimination decisions, but used to a greater extent in confidence about those decisions, and this was not due to differences in processing time. With a Bayesian model we quantified the weighting parameters for the prior at both levels, and confirmed that priors are more optimally used in explicit confidence, even when underused in decisions.

neuroscience↗

bioRxiv2021

Judgments of agency are affected by sensory noise without recruiting metacognitive processing

Judgments of agency, our sense of control over our actions and the environment, often occur in noisy conditions. We examined the computations underlying judgments of agency, in particular under the influence of sensory noise. Building on previous literature, we studied whether judgments of agency incorporate uncertainty in the same way that confidence judgments do, which would imply that the former share computational mechanisms with metacognitive judgments. In two tasks, participants rated agency, or confidence in a decision about their agency, over a virtual hand that tracked their movements, either synchronously or with a delay and either under high or low noise. We compared the predictions of two computational models to participants ratings and found that agency ratings, unlike confidence, were best explained by a model involving no estimates of sensory noise. We propose that agency judgments reflect first-order measures of the internal signal, without involving metacognitive computations, challenging the assumed link between the two cognitive processes.

neuroscience↗