Communicated priors tune the perception of control.

Action allows us to shape the world around us. But to act effectively we need to accurately sense what we can and cannot control. Classic theories across cognitive science suppose that this 'sense of agency' is constructed from the sensorimotor signals we experience as we interact with our surroundings.

Predictions and errors are distinctly represented across V1 layers.

Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive. Under "predictive processing" schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers. Predictions are compared with input to compute the "prediction error," which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.

Stubborn Predictions in Primary Visual Cortex.

Perceivers can use past experiences to make sense of ambiguous sensory signals. However, this may be inappropriate when the world changes and past experiences no longer predict what the future holds. Optimal learning models propose that observers decide whether to stick with or update their predictions by tracking the uncertainty or "precision" of their expectations.

Expectations about precision bias metacognition and awareness.

Bayesian models of the mind suggest that we estimate the reliability or "precision" of incoming sensory signals to guide perceptual inference and to construct feelings of confidence or uncertainty about what we are perceiving. However, accurately estimating precision is likely to be challenging for bounded systems like the brain. One way observers could overcome this challenge is to form about the precision of their perceptions and use these to guide metacognition and awareness.

Cancelling cancellation? Sensorimotor control, agency, and prediction.

For decades, classic theories of action control and action awareness have been built around the idea that the brain predictively 'cancels' expected action outcomes from perception. However, recent research casts doubt over this basic premise. What do these new findings mean for classic accounts of action? Should we now 'cancel' old data, theories and approaches generated under this idea? In this paper, we argue 'No'.

Causal surgery under a Markov blanket.

Bruineberg et al. provide compelling clarity on the roles Markov blankets could (and perhaps should) play in the study of life and mind. However, here we draw attention to a further role blankets might play: as a hypothesis about cognition itself.

Building better theories.

In this My word, Press et al. tackle the 'theory crisis' in cognitive science. Using examples of good and not-so-good theoretical practice, they distinguish theories from effects, predictions, hypotheses, typologies, and frameworks in a self-help checklist of seven questions to guide theory construction, evaluation, and testing.

Action Enhances Predicted Touch.

It is widely believed that predicted tactile action outcomes are perceptually attenuated. The present experiments determined whether predictive mechanisms necessarily generate attenuation or, instead, can enhance perception-as typically observed in sensory cognition domains outside of action. We manipulated probabilistic expectations in a paradigm often used to demonstrate tactile attenuation.

Precision and the Bayesian brain.

Scientific thinking about the minds of humans and other animals has been transformed by the idea that the brain is Bayesian. A cornerstone of this idea is that agents set the balance between prior knowledge and incoming evidence based on how reliable or 'precise' these different sources of information are - lending the most weight to that which is most reliable. This concept of precision has crept into several branches of cognitive science and is a lynchpin of emerging ideas in computational psychiatry - where unusual beliefs or experiences are explained as abnormalities in how the brain estimates precision.

Prediction and Learning: Understanding Uncertainty.

We build models of the world around us to guide perception and learning in the face of uncertainty. New evidence reveals a neurocomputational mechanism that links predictive processes across cognitive domains.

Action biases perceptual decisions toward expected outcomes.

We predict how our actions will influence the world around us. Prevailing models in the action control literature propose that we use these predictions to suppress or "cancel" perception of expected action outcomes, to highlight more informative surprising events. However, contrasting normative Bayesian models in sensory cognition suggest that we are more, not less, likely to perceive what we expect-given that what we expect is more likely to occur.

Illusions of control without delusions of grandeur.

We frequently experience feelings of agency over events we do not objectively influence - so-called 'illusions of control'. These illusions have prompted widespread claims that we can be insensitive to objective relationships between actions and outcomes, and instead rely on grandiose beliefs about our abilities. However, these illusory biases could instead arise if we are highly sensitive to action-outcome correlations, but attribute agency when such correlations emerge simply by chance.

Beliefs and desires in the predictive brain.

Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the mismatch between their expectations and reality. This principle could unify cognitive science with the broader natural sciences, but leave key elements of cognition and behaviour unexplained.

Association between action kinematics and emotion perception across adolescence.

Research with adults suggests that we interpret the internal states of others from kinematic cues, using models calibrated to our own action experiences. Changes in action production that occur during adolescence may therefore have implications for adolescents' understanding of others. Here we examined whether, like adults, adolescents use velocity cues to determine others' emotions and whether any differences in emotion perception would be those predicted based on differences in action production.

The Perceptual Prediction Paradox.

From the noisy information bombarding our senses, our brains must construct percepts that are veridical - reflecting the true state of the world - and informative - conveying what we did not already know. Influential theories suggest that both challenges are met through mechanisms that use expectations about the likely state of the world to shape perception. However, current models explaining how expectations render perception either veridical or informative are mutually incompatible.

Perceptual Prediction: Rapidly Making Sense of a Noisy World.

Prior knowledge shapes what we perceive. A new brain stimulation study suggests that this perceptual shaping is achieved by changes in sensory brain regions before the input arrives, with common mechanisms operating across different sensory areas.

Atypical emotion recognition from bodies is associated with perceptual difficulties in healthy aging.

A range of processes are required for recognizing others' affective states. It is particularly important that we process the perceptual cues providing information about these states. These experiments tested the hypothesis that difficulties with affective state identification in older adults (OAs) arise, at least partly, from deficits in perceptual processing.

The Predictive Brain as a Stubborn Scientist.

Bayesian theories of perception have traditionally cast the brain as an idealised scientist, refining predictions about the outside world based on evidence sampled by the senses. However, recent predictive coding models include predictions that are resistant to change, and these stubborn predictions can be usefully incorporated into cognitive models.

Action sharpens sensory representations of expected outcomes.

When we produce actions we predict their likely consequences. Dominant models of action control suggest that these predictions are used to 'cancel' perceptual processing of expected outcomes. However, normative Bayesian models of sensory cognition developed outside of action propose that rather than being cancelled, expected sensory signals are represented with greater fidelity (sharpened).

Sensory predictions during action support perception of imitative reactions across suprasecond delays.

Perception during action is optimized by sensory predictions about the likely consequences of our movements. Influential theories in social cognition propose that we use the same predictions during interaction, supporting perception of similar reactions in our social partners. However, while our own action outcomes typically occur at short, predictable delays after movement execution, the reactions of others occur at longer, variable delays in the order of seconds.

Our own action kinematics predict the perceived affective states of others.

Our movement kinematics provide useful cues about our affective states. Given that our experiences furnish models that help us to interpret our environment, and that a rich source of action experience comes from our own movements, in the present study, we examined whether we use models of our own action kinematics to make judgments about the affective states of others. For example, relative to one's typical kinematics, anger is associated with fast movements.

Predicted action consequences are perceptually facilitated before cancellation.

Models of action control suggest that predicted action outcomes are "cancelled" from perception, allowing agents to devote resources to more behaviorally relevant unexpected events. These models are supported by a range of findings demonstrating that expected consequences of action are perceived less intensely than unexpected events. A key assumption of these models is that the prediction is subtracted from the sensory input.

Time on your hands: Perceived duration of sensory events is biased toward concurrent actions.

Perceptual systems must rapidly generate accurate representations of the world from sensory inputs that are corrupted by internal and external noise. We can typically obtain more veridical representations by integrating information from multiple channels, but this integration can lead to biases when inputs are, in fact, not from the same source. Although a considerable amount is known about how different sources of information are combined to influence what we perceive, it is not known whether temporal features are combined.