Biology subjects

West, R. K.

Publications and source records attributed to West, R. K..

3 recordsLinked to original sources

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

Modality Independent or Modality Specific? Common Computations Underlie Confidence Judgements in Visual and Auditory Decisions

Humans possess the ability to evaluate their confidence in a range of different decisions. In this study, we investigated the computational processes that underlie confidence judgements and the extent to which these computations are the same for perceptual decisions in the visual and auditory modalities. Participants completed two versions of a categorisation task with visual or auditory stimuli and made confidence judgements about their category decisions. In each modality, we varied both evidence strength, (i.e., the strength of the evidence for a particular category) and sensory uncertainty (i.e., the intensity of the sensory signal). We evaluated several classes of models which formalise the mapping of evidence strength and sensory uncertainty to confidence in different ways: 1) unscaled evidence strength models, 2) scaled evidence strength models, and 3) Bayesian models. Our model comparison results showed that across tasks and modalities, participants take evidence strength and sensory uncertainty into account in a way that is consistent with the scaled evidence strength class. Notably, the Bayesian class provided a relatively poor account of the data across modalities, particularly in the more complex categorisation task. Our findings suggest that a common process is used for evaluating confidence in perceptual decisions across domains, but that the parameter settings governing the process are tuned differently in each modality. Overall, our results highlight the impact of sensory uncertainty on confidence and the unity of metacognitive processing across sensory modalities. Author SummaryIn this study, we investigated the computational processes that describe how people derive a sense of confidence in their decisions. In particular, we determined whether the computations that underlie the evaluation of confidence for a visual decision are the same as those for an auditory decision. We tested a range of different models from 3 distinct classes which make different predictions about the computations that are used. We found that a single class of models provided the best account of confidence, suggesting a common process for evaluating confidence across sensory modalities. Even though these computations are governed by the same general process, our results suggest that the process is still fine-tuned within each modality.

neuroscience↗

bioRxiv2021

Spatial structure, phase, and the contrast of natural images

The sensitivity of the human visual system is thought to be shaped by environmental statistics. A major endeavour in vision science, therefore, is to uncover the image statistics that predict perceptual and cognitive function. When searching for targets in natural images, for example, it has recently been proposed that target detection is inversely related to the spatial similarity of the target to its local background. We tested this hypothesis by measuring observers sensitivity to targets that were blended with natural image backgrounds. Targets were designed to have a spatial structure that was either similar or dissimilar to the background. Contrary to masking from similarity, we found that observers were most sensitive to targets that were most similar to their backgrounds. We hypothesised that a coincidence of phase-alignment between target and background results in a local contrast signal that facilitates detection when target-background similarity is high. We confirmed this prediction in a second experiment. Indeed, we show that, by solely manipulating the phase of a target relative to its background, the target can be rendered easily visible or undetectable. Our study thus reveals that, in addition to its structural similarity, the phase of the target relative to the background must be considered when predicting detection sensitivity in natural images.

neuroscience↗