Paul M. Bays

The paper quantifies ancillary information in neural populations about uncertainty using mutual information and Fisher information loss, showing non-Gaussian errors and bounds on metacognitive sensitivity.

The paper addresses criticisms of a previous study on visual cortex orientation representation and provides additional MEG data supporting the original findings.

The paper shows how intrinsic rewards influence visual processing by guiding resource allocation through reinforcement learning, affecting both performance and accuracy.

The paper develops a computational model explaining why self-generated forces are perceived as weaker, showing that attenuated sensations have greater variability due to added motor prediction noise.

The paper explains the Size-Weight Illusion using efficient coding principles, showing that perceptual biases arise from statistical properties of natural environments.

The paper introduces a dynamic neural resource model that explains memory fidelity changes over time by integrating sensory and working memory processes.

The paper shows that human visual system tuning reflects stimulus-specific variations not predicted by prior coding schemes, embedding environmental priors in sensory measurements.

This study investigates whether perceptual similarity judgments predict working memory errors and finds no consistent relationship between the two.

The paper investigates transsaccadic integration in different feature dimensions, finding that integration occurs independently for each feature and is influenced by change magnitude.

This study uses a stochastic sampling framework to unify models of working memory limits, showing random variability in sample counts, not discrete/continuous nature, explains human performance.

The paper shows that estimates of memory variability are bounded by neural tuning widths, challenging interpretations of previous studies on memory precision limits.

The paper shows that neural population coding models and psychophysical scaling models of working memory are mathematically similar, suggesting a convergence between neural and cognitive explanations of memory.

The paper investigates whether visual working memory is affected by cortical spacing between memoranda and finds no such effect, suggesting memory and perception use different neural mechanisms.