A-Izzeddin, E. J. | bioRxiv Science

bioRxiv2023

Priors for natural image statistics inform confidence in perceptual decisions

Decision confidence plays a critical role in humans ability to make adaptive decisions in a noisy perceptual world. Despite its importance, there is currently little consensus about the computations underlying confidence judgements in perceptual decisions. In order to better understand these mechanisms, in this study we sought to address the extent to which confidence is informed by a naturalistic prior probability distribution. Contrary to previous research, we did not require participants to internalise the parameters of an arbitrary prior distribution. Instead we used a novel psychophysical paradigm which allowed us to capitalise on probability distributions of low-level image features in natural scenes, which are well-known to influence perception. Participants reported the subjective upright of naturalistic image target patches, and then reported their confidence in their orientation responses. We used computational modelling to relate the statistics of the low-level features in the targets to the distribution of these features across many natural images. As expected, we found that participants used an internalised prior of the regularities of low-level natural image statistics to inform their perceptual judgements. Critically, we also show that the same low-level image statistics predict participants confidence judgements. Overall, our study highlights the importance of using naturalistic task designs that capitalise on existing, long-term priors to further our understanding of the computational basis of confidence.

neuroscience↗

bioRxiv2022

Contextual influences of visual perceptual inferences

Humans have well-documented priors for many features present in nature that guide visual perception. Despite being putatively grounded in the statistical regularities of the environment, scene priors are frequently violated due to the inherent variability of visual features from one scene to the next. However, these repeated violations do not appreciably challenge visuo-cognitive function, necessitating the broad use of priors in conjunction with context-specific information. We investigated the trade-off between participants internal expectations formed from both longer-term priors and those formed from immediate contextual information using a perceptual inference task and naturalistic stimuli. Notably, our task required participants to make perceptual inferences about naturalistic images using their own internal criteria, rather than making comparative judgements. Nonetheless, we show that observers performance is well approximated by a model that makes inferences using a prior for low-level image statistics, aggregated over many images. We further show that the dependence on this prior is rapidly re-weighted against contextual information, whether relevant or irrelevant. Our results therefore provide insight into how apparent high-level interpretations of scene appearances follow from the most basic of perceptual processes, which are grounded in the statistics of natural images.

neuroscience↗