Prior expectations about the visual world facilitate perception by allowing us to quickly deduce plausible interpretations from noisy and ambiguous data. The neural mechanisms of this facilitation remain largely unclear. Here, we used functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA) techniques to measure both the amplitude and representational content of neural activity in the early visual cortex of human volunteers. We find that while perceptual expectation reduces the neural response amplitude in the primary visual cortex (V1), it improves the stimulus representation in this area, as revealed by MVPA. This informational improvement was independent of attentional modulations by task relevance. Finally, the informational improvement in V1 correlated with subjects' behavioral improvement when the expected stimulus feature was relevant. These data suggest that expectation facilitates perception by sharpening sensory representations.

Recent studies claim that visual perception of stimulus features, such as orientation, numerosity, and faces, is systematically biased toward visual input from the immediate past [1-3]. However, the extent to which these positive biases truly reflect changes in perception rather than changes in post-perceptual processes is unclear [4, 5]. In the current study we sought to disentangle perceptual and decisional biases in visual perception. We found that post-perceptual decisions about orientation were indeed systematically biased toward previous stimuli and this positive bias did not strongly depend on the spatial location of previous stimuli (replicating previous work [1]). In contrast, observers' perception was repelled away from previous stimuli, particularly when previous stimuli were presented at the same spatial location. This repulsive effect resembles the well-known negative tilt-aftereffect in orientation perception [6]. Moreover, we found that the magnitude of the positive decisional bias increased when a longer interval was imposed between perception and decision, suggesting a shift of working memory representations toward the recent history as a source of the decisional bias. We conclude that positive aftereffects on perceptual choice are likely introduced at a post-perceptual stage. Conversely, perception is negatively biased away from recent visual input. We speculate that these opposite effects on perception and post-perceptual decision may derive from the distinct goals of perception and decision-making processes: whereas perception may be optimized for detecting changes in the environment, decision processes may integrate over longer time periods to form stable representations.

Perception and perceptual decision-making are strongly facilitated by prior knowledge about the probabilistic structure of the world. While the computational benefits of using prior expectation in perception are clear, there are myriad ways in which this computation can be realized. We review here recent advances in our understanding of the neural sources and targets of expectations in perception. Furthermore, we discuss Bayesian theories of perception that prescribe how an agent should integrate prior knowledge and sensory information, and investigate how current and future empirical data can inform and constrain computational frameworks that implement such probabilistic integration in perception.

Sensory signals are highly structured in both space and time. These structural regularities in visual information allow expectations to form about future stimulation, thereby facilitating decisions about visual features and objects. Here, we discuss how expectation modulates neural signals and behaviour in humans and other primates. We consider how expectations bias visual activity before a stimulus occurs, and how neural signals elicited by expected and unexpected stimuli differ. We discuss how expectations may influence decision signals at the computational level. Finally, we consider the relationship between visual expectation and related concepts, such as attention and adaptation.

A recent study found that, across individuals, gray matter volume in the frontal polar region was correlated with visual metacognition capacity (i.e., how well one’s confidence ratings distinguish between correct and incorrect judgments). A question arises as to whether the putative metacognitive mechanisms in this region are also used in other metacognitive tasks involving, for example, memory. A novel psychophysical measure allowed us to assess metacognitive efficiency separately in a visual and a memory task, while taking variations in basic task performance capacity into account. We found that, across individuals, metacognitive efficiencies positively correlated between the two tasks. However, voxel-based morphometry analysis revealed distinct brain structures for the two kinds of metacognition. Replicating a previous finding, variation in visual metacognitive efficiency was correlated with volume of frontal polar regions. However, variation in memory metacognitive efficiency was correlated with volume of the precuneus. There was also a weak correlation between visual metacognitive efficiency and precuneus volume, which may account for the behavioral correlation between visual and memory metacognition (i.e., the precuneus may contain common mechanisms for both types of metacognition). However, we also found that gray matter volumes of the frontal polar and precuneus regions themselves correlated across individuals, and a formal model comparison analysis suggested that this structural covariation was sufficient to account for the behavioral correlation of metacognition in the two tasks. These results highlight the importance of the precuneus in higher-order memory processing and suggest that there may be functionally distinct metacognitive systems in the human brain.