The strength of frequency-tagged neural activity during perceptual filling anti-correlates with the contents of consciousness, yet positively correlates with a neural measure of attention, dissociating these often confounded brain processes.

The brain ensures that blinks do not disrupt vision by deleting signals that represent discontinuities in visual input, rather than by recreating the missing input.

Changes in physiological arousal – as revealed by pupil dilation and heart rate – shape our confidence in decisions about uncertain perceptual information.

Perception in autism is sensitive to absolute rather than to relative metrics of the environment, encoding changes in the environment without calibrating the changes relative to reference stimulation.

Peripheral appearance models emphasising pooling processes that depend on retinal eccentricity will instead need to explore input-dependent grouping and segmentation.

Visual attention modulates the integration of the evidence that is most useful for achieving a goal in both perceptual and value-based decisions.

Autistic traits are associated with weaker influence of prior expectations in visual perception, which is due to more precise sensory representations.

Neural coding of previous-trial confidence affects current decision policy.

Sophisticated decision-making mechanisms and complex experimental paradigms can be modeled, simulated, and fit to empirical response time data, using a flexible and efficient computational modeling framework.

Activity in the midbrain responds to unexpected changes in outcome identity (i.e. sensory prediction error) but does not scale with perceptual distance between expected and receipt reward.