High-level visual prediction errors in early visual cortex.

Perception is shaped by both incoming sensory input and expectations derived from our prior knowledge. Numerous studies have shown stronger neural activity for surprising inputs, suggestive of predictive processing. However, it is largely unclear what predictions are made across the cortical hierarchy, and therefore what kind of surprise drives this up-regulation of activity.

Individual differences in information demand have a low dimensional structure predicted by some curiosity traits.

To understand human learning and progress, it is crucial to understand curiosity. But how consistent is curiosity's conception and assessment across scientific research disciplines? We present the results of a large collaborative project assessing the correspondence between curiosity measures in personality psychology and cognitive science. A total of 820 participants completed 15 personality trait measures and 9 cognitive tasks that tested multiple aspects of information demand.

Spatial Predictive Context Speeds Up Visual Search by Biasing Local Attentional Competition.

The human visual system is equipped to rapidly and implicitly learn and exploit the statistical regularities in our environment. Within visual search, contextual cueing demonstrates how implicit knowledge of scenes can improve search performance. This is commonly interpreted as spatial context in the scenes becoming predictive of the target location, which leads to a more efficient guidance of attention during search.

Forward and backward blocking in statistical learning.

Prediction errors have a prominent role in many forms of learning. For example, in reinforcement learning, agents learn by updating the association between states and outcomes as a function of the prediction error elicited by the event. One paradigm often used to study error-driven learning is blocking.

Predictive processing of scenes and objects.

Real-world visual input consists of rich scenes that are meaningfully composed of multiple objects which interact in complex, but predictable, ways. Despite this complexity, we recognize scenes, and objects within these scenes, from a brief glance at an image. In this review, we synthesize recent behavioral and neural findings that elucidate the mechanisms underlying this impressive ability.

Amodal completion across the brain: The impact of structure and knowledge.

This study investigates the phenomenon of amodal completion within the context of naturalistic objects, employing a repetition suppression paradigm to disentangle the influence of structure and knowledge cues on how objects are completed. The research focuses on early visual cortex (EVC) and lateral occipital complex (LOC), shedding light on how these brain regions respond to different completion scenarios. In LOC, we observed suppressed responses to structure and knowledge-compatible stimuli, providing evidence that both cues influence neural processing in higher-level visual areas.

Perceptual confirmation bias and decision bias underlie adaptation to sequential regularities.

Our perception does not depend exclusively on the immediate sensory input. It is also influenced by our internal predictions derived from prior observations and the temporal regularities of the environment, which can result in choice history biases. However, it is unclear how this flexible use of prior information to predict the future influences perceptual decisions.

Lexical Processing Strongly Affects Reading Times But Not Skipping During Natural Reading.

In a typical text, readers look much longer at some words than at others, even skipping many altogether. Historically, researchers explained this variation via low-level visual or oculomotor factors, but today it is primarily explained via factors determining a word's lexical processing ease, such as how well word identity can be predicted from context or discerned from parafoveal preview. While the existence of these effects is well established in controlled experiments, the relative importance of prediction, preview and low-level factors in natural reading remains unclear.

Expected distractor context biases the attentional template for target shapes.

Visual search is supported by an internal representation of the target, the attentional template. However, which features are diagnostic of target presence critically depends on the distractors. Accordingly, previous research showed that consistent distractor context shapes the attentional template for simple targets, with the template emphasizing diagnostic dimensions (e.

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.

Conceptual Associations Generate Sensory Predictions.

A crucial ability of the human brain is to learn and exploit probabilistic associations between stimuli to facilitate perception and behavior by predicting future events. Although studies have shown how perceptual relationships are used to predict sensory inputs, relational knowledge is often between concepts rather than percepts (e.g.

Humans predict the forest, not the trees: statistical learning of spatiotemporal structure in visual scenes.

The human brain is capable of using statistical regularities to predict future inputs. In the real world, such inputs typically comprise a collection of objects (e.g.

An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory.

The relationship between conscious experience and brain activity has intrigued scientists and philosophers for centuries. In the last decades, several theories have suggested different accounts for these relationships. These theories have developed in parallel, with little to no cross-talk among them.

Successor-like representation guides the prediction of future events in human visual cortex and hippocampus.

Human agents build models of their environment, which enable them to anticipate and plan upcoming events. However, little is known about the properties of such predictive models. Recently, it has been proposed that hippocampal representations take the form of a predictive map-like structure, the so-called successor representation (SR).

Magnetoencephalography recordings reveal the neural mechanisms of auditory contributions to improved visual detection.

Sounds enhance the detection of visual stimuli while concurrently biasing an observer's decisions. To investigate the neural mechanisms that underlie such multisensory interactions, we decoded time-resolved Signal Detection Theory sensitivity and criterion parameters from magneto-encephalographic recordings of participants that performed a visual detection task. We found that sounds improved visual detection sensitivity by enhancing the accumulation and maintenance of perceptual evidence over time.

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience.

Expectations shape our experience of music. However, the internal model upon which listeners form melodic expectations is still debated. Do expectations stem from Gestalt-like principles or statistical learning? If the latter, does long-term experience play an important role, or are short-term regularities sufficient? And finally, what length of context informs contextual expectations? To answer these questions, we presented human listeners with diverse naturalistic compositions from Western classical music, while recording neural activity using MEG.

Choice Boosts Curiosity.

In our connected era, we spend significant time and effort satisfying our curiosity. Often, we choose which information we seek, but sometimes the selection is made for us. We hypothesized that humans exhibit enhanced curiosity in the context of choice.

Updating Contextual Sensory Expectations for Adaptive Behavior.

The brain has the extraordinary capacity to construct predictive models of the environment by internalizing statistical regularities in the sensory inputs. The resulting sensory expectations shape how we perceive and react to the world; at the neural level, this relates to decreased neural responses to expected than unexpected stimuli ("expectation suppression"). Crucially, expectations may need revision as context changes.

Reconstructing the predictive architecture of the mind and brain.

Predictive processing has become an influential framework in cognitive neuroscience. However, it often lacks specificity and direct empirical support. How can we probe the nature and limits of the predictive brain? We highlight the potential of recent advances in artificial intelligence (AI) for providing a richer and more computationally explicit test of this theory of cortical function.

Dampened sensory representations for expected input across the ventral visual stream.

Expectations, derived from previous experience, can help in making perception faster, more reliable and informative. A key neural signature of perceptual expectations is expectation suppression, an attenuated neural response to expected compared with unexpected stimuli. While expectation suppression has been reported using a variety of paradigms and recording methods, it remains unclear what neural modulation underlies this response attenuation.

A hierarchy of linguistic predictions during natural language comprehension.

Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions.

Flexible recoding of visual input for memory storage.

Working memory enables us to maintain relevant past information for future behavior. In this issue of Neuron, Kwak and Curtis (2022) demonstrate that early visual areas do not simply maintain but flexibly recode sensory percepts into mnemonic codes containing goal-relevant information.

Acute threat enhances perceptual sensitivity without affecting the decision criterion.

Threatening situations ask for rapid and accurate perceptual decisions to optimize coping. Theoretical models have stated that psychophysiological states, such as bradycardia during threat-anticipatory freezing, may facilitate perception. However, it's unclear if this occurs via enhanced bottom-up sensory processing or by relying more on prior expectations.

Adaptation and serial choice bias for low-level visual features are unaltered in autistic adolescents.

Autism spectrum disorder (ASD), or autism, is characterized by social and non-social symptoms, including sensory hyper- and hyposensitivities. A suggestion has been put forward that some of these symptoms could be explained by differences in how sensory information is integrated with its context, including a lower tendency to leverage the past in the processing of new perceptual input. At least two history-dependent effects of opposite directions have been described in the visual perception literature: a repulsive adaptation effect, where perception of a stimulus is biased away from an adaptor stimulus, and an attractive serial choice bias, where perceptual choices are biased toward the previous choice.

Brief Stimuli Cast a Persistent Long-Term Trace in Visual Cortex.

Visual processing is strongly influenced by recent stimulus history, a phenomenon termed adaptation. Prominent theories cast adaptation as a consequence of optimized encoding of visual information by exploiting the temporal statistics of the world. However, this would require the visual system to track the history of individual briefly experienced events, within a stream of visual input, to build up statistical representations over longer timescales.