Evaluating signal detection models of perceptual decision confidence

Abstract

Event Abstract Back to Event Evaluating signal detection models of perceptual decision confidence Introduction In making perceptual decisions, humans and animals are able to report the level of confidence associated with the decision (1). In this work we investigate the mechanism underlying this confidence reporting procedure. In particular, is all the information used for perceptual decision making available to confidence reporting mechanisms? Some models of perception suggest that there are multiple channels of information, and subjective reports such as confidence ratings can only tap into one of the channels (e.g. cortical, but not subcortical channels). Is this popular view correct? We capitalize on an original psychophysical finding (2) that subjective reports of perceptual confidence and perceptual performance (d’) can dissociate, and apply formal model comparison techniques to identify the mechanism underlying confidence reporting. Methods and Results Signal detection theory (SDT) can be extended to characterize sensitivity and response bias in the type 2 task, i.e. the task of discriminating between one’s own correct and incorrect perceptual judgments using confidence ratings (3). We considered several such SDT models, including: 1: A simple SDT model where type 2 decisions are made by setting criteria on a transformation of the primary decision axis; 2: A decision noise model where type 2 sensitivity is affected by variation in type 2 criterion setting; 3: A late noise model where the noisy perceptual signal becomes even noisier when making confidence judgments; 4: A two-channel model where only one channel contributes to confidence judgments. Psychophysical data from the metacontrast masking paradigm dissociates perceptual performance from confidence in a manner that cannot plausibly be accounted for by differences in type 2 criterion setting (2). As such, this data presents a stringent test for models of type 2 performance. We compared models by evaluating the likelihood of each model, given the metacontrast masking data, using the Akaike information criterion. All models could account for perceptual performance, but only the late noise model provided a close fit to the observed performance-confidence dissociation. Discussion Our results suggest that traditional SDT models are not adequate to model type 2 performance, because they do not provide a process that allows for the kind of performance-confidence dissociation observed in the metacontrast masking paradigm. However, this extra process need not be an extra information processing channel. Our best-fitting model was a hierarchical, single-channel model where noisy perceptual signals accrued further noise when used for rating confidence. This suggests that confidence decisions may be made by mechanisms downstream from perceptual decision mechanisms.