Challenging the fixed-criterion model of perceptual decision-making

Automatic multisensory integration follows subjective confidence rather than objective performance

It is well known that sensory information from one modality can automatically affect judgments from a different sensory modality. However, it remains unclear what determines the strength of the influence of an irrelevant sensory cue from one modality on a perceptual judgment for a different modality. Here we test whether the strength of multisensory impact by an irrelevant sensory cue depends on participants' objective accuracy or subjective confidence for that cue. We created visual motion stimuli with low vs. high overall motion energy, where high-energy stimuli yielded higher confidence but lower accuracy in a visual-only task. We then tested the impact of the low- and high-energy visual stimuli on auditory motion perception. We found that the high-energy visual stimuli influenced the auditory motion judgments more strongly than the low-energy visual stimuli, consistent with their higher confidence but contrary to their lower accuracy. A computational model assuming common principles underlying confidence reports and multisensory integration captured these effects. Our findings show that automatic multisensory integration follows subjective confidence rather than objective performance and suggest the existence of common computations across vastly different stages of perceptual decision making.

Challenging the Bayesian confidence hypothesis in perceptual decision-making

The Bayesian confidence hypothesis (BCH), which postulates that confidence reflects the posterior probability that a decision is correct, is currently the most prominent theory of confidence. Although several recent studies have found evidence against it in the context of relatively complex tasks, BCH remains dominant for simpler tasks. The major alternative to BCH is the confidence in raw evidence space (CRES) hypothesis, according to which confidence is based directly on the raw sensory evidence without explicit probability computations. Here, we tested these competing hypotheses in the context of perceptual tasks that are assumed to induce Gaussian evidence distributions. We show that providing information about task difficulty gives rise to a basic behavioral signature that distinguishes BCH from CRES models even for simple 2-choice tasks. We examined this signature in three experiments and found that all experiments exhibited behavioral signatures in line with CRES computations but contrary to BCH ones. We further performed an extensive comparison of 16 models that implemented either BCH or CRES confidence computations and systematically differed in their auxiliary assumptions. These model comparisons provided overwhelming support for the CRES models over their BCH counterparts across all model variants and across all three experiments. These observations challenge BCH and instead suggest that humans may make confidence judgments by placing criteria directly in the space of the sensory evidence.

How to get rich from inflation

We seem to have rich experience across our visual field. Yet we are surprisingly poor at tasks involving the periphery and low spatial attention. Recently, Lau and collaborators have argued that a phenomenon known as "subjective inflation" allows us to reconcile these phenomena. I show inflation is consistent with multiple interpretations, with starkly different consequences for richness and for theories of consciousness more broadly. What's more, we have only weak reasons favouring any of these interpretations over the others. I provisionally argue for an interpretation on which subjective experience is genuinely rich, but (in peripheral/unattended areas) unreliable as a guide to the external world. The main challenge for this view is that it appears to imply that experience in the periphery is not just unreliable but unstable. However, I argue that this consequence, while initially appearing unintuitive, is in fact plausible.