Perceptual Set: How Expectations Influence What We Perceive

Author: Angela Bogdanova · Published: October 16, 2026 · Editorial Policy

Research cluster: Attention, Perception & Cognitive Control · Written by Artificial Sapiens

Perceptual set is a state of readiness to interpret incoming sensory information in a particular way. It develops through prior experience, contextual cues, current goals, learned categories, and expectations about what is likely to appear. When a signal admits more than one plausible interpretation, perceptual set can favor one interpretation, speed recognition of expected patterns, or make an unexpected alternative harder to identify. The concept also describes the immediate orientation of an observer toward task-relevant features, such as a driver looking for road hazards or a reader anticipating the next word. The American Psychological Association's Dictionary of Psychology recognizes both temporary readiness and more established interpretive frames.

Consider an ambiguous mark that could be the letter B or the number 13. In a row of letters, many observers read it as B; in a sequence of numbers, they are more likely to read it as 13. Context makes one interpretation more plausible. The retinal input can remain nearly identical while the reported identity changes. Such an example illustrates the central phenomenon, but the scientific explanation requires identifying the processing stage at which context exerts its influence. A different report can result from a different perceptual experience, a shift in the decision rule, a change in attention, or several interacting mechanisms. Contemporary reviews therefore treat expectation effects as a family of experimentally distinguishable processes rather than as one all-purpose explanation. de Lange et al. (2018) Bang and Rahnev (2017)

What Is Perceptual Set in Psychology?

The defining property of perceptual set is selective preparedness: previous information gives some interpretations an advantage when sensory evidence arrives. This preparedness can be established in seconds by a verbal cue, in minutes by the statistical structure of an experimental sequence, or across years by familiarity with objects and situations. Its expression depends on the task, the reliability of the current signal, and the relevance of the learned expectation. Summerfield and de Lange (2014)

Perceptual set belongs to the psychology of perception because its immediate object is the interpretation and identification of sensory events. It is closely related to the broader interaction between incoming evidence and existing knowledge described in Bottom-Up vs Top-Down Processing in Perception: Examples and Evidence. Perceptual set identifies a particular source of that interaction: an observer is prepared for one class of inputs or meanings. It can influence the allocation of attention, the efficiency of identification, the interpretation of ambiguity, and the judgment used to produce a response.

A working scientific definition

In experimental terms, a perceptual-set effect occurs when manipulating an observer's prior context, learned probability, instruction, category, or expectation changes a perceptual report or performance while relevant sensory evidence is held constant or carefully controlled. Researchers then investigate whether the effect reflects sensory encoding, attentional selection, recognition, awareness, memory, or a later decision. This operational definition keeps the observation separate from its causal interpretation. Firestone and Scholl (2016)

Two people can bring different perceptual sets to the same environment. A botanist walking through a garden is prepared to identify leaf patterns and species distinctions; a landscape designer may immediately register sightlines and spatial composition. Experience directs which distinctions are useful and which interpretations come readily to mind. This is a plausible everyday illustration of task-based perceptual preparedness; it should not be read as proof that the earliest visual encoding of the garden differs between observers. Research on perceptual learning provides a more precise account of how repeated experience changes discrimination and feature weighting. Goldstone (1998)

How Perceptual Set Works: The Main Mechanisms

Several mechanisms can produce an expectation-consistent response. Distinguishing them is essential because the same behavioral result can arise in different parts of the processing sequence.

Prior probability and learned regularities

People learn that certain objects, sounds, and sequences occur more often than others. These regularities create expectations about what is likely to happen next. A familiar kitchen scene makes a kettle or mug probable; a familiar musical phrase makes some continuations more predictable than others. Context thus narrows the range of plausible hypotheses before an individual signal has been fully analyzed. A review of object recognition emphasizes that relationships between scenes and objects can guide identification of partially available visual information. Bar (2004)

The prediction can be accurate or inaccurate. When expectations match the environment, recognition may become more efficient. When they conflict with a novel event, a perceiver may require stronger evidence or more time to revise the initial interpretation. This is an important trade-off in an environment where most events are structured but surprising events still matter. Peelen et al. (2024)

Contextual interpretation and ambiguity resolution

Ambiguous signals support multiple interpretations because their features are compatible with more than one object or event. Surrounding information can favor one interpretation over another. A drawn contour may belong to different overlapping shapes; a masked letter may fit different words; an indistinct sound may fit different phonemes. The effect can be examined by changing context while presenting the same target signal. This is especially instructive when researchers match contrast, duration, location, and response requirements across conditions. de Lange et al. (2018)

Context also operates at different timescales. Immediately adjacent symbols establish local context, a sentence provides linguistic expectations, a scene conveys the likelihood of particular objects, and repeated trials teach a statistical pattern. Each has the potential to generate an expectation without requiring a durable belief about the world. Bar (2004) Warren (1970)

Attentional priorities and task instructions

A person told to detect a red shape prepares to prioritize color; someone asked to identify an object at a specified location prepares to prioritize spatial information. Task instructions can therefore create a perceptual set by altering where attention is directed and which features are relevant. Expectation and attention often cooperate, but they refer to different variables. An expected event is one considered likely; an attended event is one prioritized because it matters to the current task. A probable stimulus can be irrelevant, and a rare stimulus can be the primary target. Summerfield and de Lange (2014)

An experimentally observed advantage for a predicted object may consequently arise because the participant attended to the object's distinctive feature. A study that aims to identify a pure probability effect must control feature relevance and spatial attention, not merely compare valid and invalid cues. Bang and Rahnev (2017)

Decision criteria and response bias

When evidence is uncertain, participants must decide whether a stimulus was present or which category to report. Expectation can shift the threshold for choosing an answer. If a tone is predicted to occur frequently, an observer might report hearing it on weaker evidence; the rate of correct detections may rise alongside false alarms. This is a genuine effect of expectation on reported perception, even if the underlying sensory representation has not improved. Bang and Rahnev (2017)

Signal detection theory helps separate the sensitivity of a task from the willingness to make a particular response. Sensitivity is commonly summarized as d-prime (d′), and response bias with a criterion measure such as c, under the assumptions of a chosen signal detection model. These quantities describe performance patterns; they do not automatically locate the responsible process in the brain. A criterion shift and a change in sensory evidence can produce overlapping behavioral signatures, so experimental design matters as much as the equation. Bang and Rahnev (2017)

Classic Experiments That Established the Idea

Bruner and Postman: incongruous playing cards

In their influential 1949 study, Jerome Bruner and Leo Postman exposed participants to playing cards that sometimes violated familiar conventions, including cards with unexpected color-suit combinations. Participants commonly used familiar card categories when describing unusual stimuli and sometimes needed longer exposures before identifying the incongruity. The work showed how established categories can structure early interpretations and how contradictory information can prompt a reorganization of the perceptual report. Bruner and Postman (1949)

The experiment is historically important because it made expectations testable by manipulating an object that viewers believed they already understood. Its results are best interpreted with the methods of the period in mind: exposure duration, verbal identification, surprising stimulus configurations, and participant response strategies were closely intertwined. It demonstrated expectation-consistent identification and the difficulty of recognizing incongruity; by contemporary standards it does not by itself establish that conscious visual experience changed at the earliest stage of sensory encoding. Bruner and Postman (1949) Firestone and Scholl (2016)

Ambiguous letters, numbers, and pictures

The familiar B/13 demonstration illustrates contextual categorization: neighboring letters invite a letter interpretation, whereas neighboring numerals invite a numerical interpretation. Ambiguous figures can similarly support different category judgments when preceded by different examples. These demonstrations are useful educational tools because they show why a perceptual report depends partly on the question the observer is prepared to answer. Their explanatory value remains strongest when the physical display, exposure time, and response instructions are documented. The general role of prior context is supported by subsequent experimental and computational research. Bar (2004) de Lange et al. (2018)

Warren: restoring a missing speech sound

Richard Warren's classic phonemic-restoration experiment replaced a speech sound in a recorded sentence with an extraneous noise. Listeners frequently experienced the sentence as containing a continuous speech sequence and had difficulty locating the missing segment. When silence replaced the phoneme, the interruption was easier to detect. The experiment illustrates how sentence structure and linguistic context can support the interpretation of degraded auditory input. It also shows why perceptual set extends beyond vision. Warren (1970)

Phonemic restoration must be understood as an auditory phenomenon with specific stimulus and masking conditions, rather than a guarantee that people always hear what they expect. Speech understanding draws upon both acoustic details and knowledge of language; this helps listeners in ordinary noisy environments but may also favor an incorrect interpretation when the signal is unclear.

Modern Research: Can Expectation Change Visual Experience?

The strongest contemporary question concerns the locus of an expectation effect. A participant may be faster or more confident in reporting an expected object, but those observations leave open whether perception itself, access to awareness, attention, or the later choice process has changed. Researchers test this question using fine-grained psychophysics, brain measurements, computational models, and experimental controls for response bias.

Expected stimuli and early visual representations

Kok, Jehee, and de Lange used functional MRI and multivariate pattern analysis to examine visual expectation in human primary visual cortex. They reported reduced overall response amplitude but more informative stimulus-specific activity patterns when a stimulus was expected, with behavioral improvement related to the representation change under task-relevant conditions. Their findings support a potential neural mechanism through which prior information sharpens certain sensory representations. The experiment is a specific imaging result, not evidence that every belief can change every form of seeing. Kok et al. (2012)

Neural responses to expected events can be smaller for several reasons, including adaptation, more efficient coding, or differences in the information represented. A smaller brain signal should not be treated automatically as worse perception; nor is a change in brain response automatically proof of changed subjective experience. Reviews distinguish the magnitude of evoked activity, the discriminability of stimulus representations, and the participant's decision. Summerfield and de Lange (2014) de Lange et al. (2018)

Language as a perceptual cue

Lupyan and Ward tested whether a word can alter access to a visually suppressed object. Participants heard labels that either matched or mismatched objects shown under continuous flash suppression. Valid labels improved performance relative to an uninformative baseline, whereas invalid labels impeded it; the study also reported effects on sensitivity estimates. The results suggest that learned categories and linguistic context can affect visual task performance under limited awareness. Interpreting the precise processing stage still depends on the controls used for attention and decisions. Lupyan and Ward (2013)

Pinto and colleagues combined predictive cues with continuous flash suppression across four experiments. Expected stimuli entered reported visual awareness more quickly than neutral or unexpected ones under their conditions. The authors argued that several simple response and attentional alternatives were insufficient to account for the pattern. These findings provide evidence that expectations can affect the timing of reported awareness; they do not settle every theoretical dispute about the relation between perception and cognition. Pinto et al. (2015)

The decision-criterion challenge

A crucial counterpoint comes from Bang and Rahnev's experiments comparing cues presented before and after a visual stimulus. Their participants judged the average orientation of a series of Gabor patches. Cues given after presentation influenced choice bias strongly, even though they could not have prepared early visual encoding before the stimulus arrived. Across their analyses, expectation-driven choices were compatible with a shift in decision criterion without a detectable change in the sensory signal. Bang and Rahnev (2017)

This result does not invalidate research showing neural modulation or enhanced sensitivity in other tasks. It establishes a key methodological requirement: when an observer reports the expected alternative more frequently, researchers must examine whether a decision-level account could explain the same data. Changes in early visual activity, perceptual sensitivity, response time, and subjective awareness should be measured as distinct outcomes.

Bayesian Models: How Prior Knowledge and Sensory Evidence Combine

Bayesian accounts formalize how perception can combine evidence from a current stimulus with learned probabilities. In simple terms, the probability of a hypothesis after observing a signal is proportional to the likelihood of that signal under the hypothesis multiplied by the prior probability of the hypothesis. Researchers write this relation as posterior ∝ likelihood × prior. The model captures why the same noisy input may support different interpretations when the environment provides different prior information. de Lange et al. (2018)

Suppose an observer hears an ambiguous syllable while listening to a coherent sentence. The acoustic input provides a likelihood for several words. The sentence supplies prior probabilities that make some words more plausible. Their combination can favor the word that fits the sentence, provided the acoustic signal is compatible. If the acoustic information is clear and contradictory, a properly calibrated observer should revise the expectation. This is an explanatory analogy, not a claim that all sentence perception follows one exact Bayesian neural algorithm.

The influence of a prior depends on uncertainty. When sensory evidence is noisy, weak, or incomplete, the prior may carry greater relative weight. When sensory evidence is precise, it can constrain the result more strongly. Bayesian models specify an idealized computation; real observers may learn inaccurate probabilities, apply inconsistent decision rules, or weigh different cues in ways that vary by task. Model fit alone does not uniquely identify a neural implementation. Summerfield and de Lange (2014) de Lange et al. (2018)

Predictive processing and perceptual set

Predictive-processing theories propose that a perceptual system generates expectations about incoming sensory information and updates them when the actual signal differs. Some models emphasize the exchange of predictions and prediction errors across processing levels. Such frameworks offer hypotheses about how learned context influences neural activity and recognition. They are relevant to perceptual set because both focus on the role of prior knowledge in interpreting present evidence. de Lange et al. (2018)

Perceptual set and predictive processing operate at different explanatory levels. Perceptual set describes a readiness or experimentally observed bias toward a class of interpretations. Predictive processing is a wider computational and mechanistic research program that may explain some forms of that readiness. There are several implementations and ongoing debates over the predictions they uniquely make. The more detailed theoretical questions belong to a dedicated treatment of predictive processing rather than being folded into the definition of perceptual set. Peelen et al. (2024)

What Shapes a Person's Perceptual Set?

Immediate context and explicit instructions

A preceding image, word, category label, or task instruction can establish a brief expectation. Laboratory experiments use these manipulations because a researcher can keep the test stimulus constant and vary the contextual cue. A genuinely informative cue may aid recognition, while an inaccurate cue can introduce confusion or cause a slower decision. Such an effect should be assessed against neutral conditions, and the consequences of cue validity should be separated from general practice improvements. Lupyan and Ward (2013) Pinto et al. (2015)

Experience, categories, and expertise

Longer experience can tune discrimination. A musician may detect distinctions in familiar musical material that a beginner misses; a trained observer may learn which visual features reliably identify categories in a specific field. Perceptual learning research identifies mechanisms including attentional weighting, differentiation, and the consolidation of complex feature combinations. Those enduring skills overlap with perceptual set but are not identical to a temporary expectancy induced by a single cue. Goldstone (1998)

Goals, concerns, and task relevance

Current goals influence which signals merit attention. An observer looking for a missing key inspects surfaces differently from someone studying the room's architecture. A person expecting an important message may monitor notification signals more closely than during an unrelated task. These cases illustrate goal-directed priority and learned expectation, but they involve attention as well as perception. It would be inaccurate to infer that a person has a particular clinical condition merely because a goal or concern shapes what they notice. Summerfield and de Lange (2014)

Culture and language

Language supplies categories that can guide recognition, while local familiarity supplies predictions about ordinary objects and scenes. Studies of labels and perception support some context-dependent effects, but general statements that members of different cultures literally see the world in categorically different ways require carefully matched cross-cultural evidence. A culture may shape learned expectations without determining every person's sensory experience. The appropriate scientific questions concern specific tasks, stimulus familiarity, linguistic cues, and measurement invariance. Lupyan and Ward (2013) Goldstone (1998)

Perceptual Set, Selective Attention, and Cognitive Bias: Important Distinctions

Perceptual set can be confused with several neighboring concepts. They are related but answer different scientific questions.

Perceptual set versus selective attention

Selective attention concerns the prioritization of information for processing. Perceptual set concerns readiness for particular sensory categories or interpretations. Attention can mediate an expectation effect, and an experiment may manipulate both at once. Distinguishing probability from task relevance allows a stronger inference about the role of expectation. Summerfield and de Lange (2014)

Perceptual set versus confirmation bias

Confirmation bias is a broader pattern of seeking, interpreting, or remembering information in ways that favor an existing belief, especially in reasoning and judgment. Perceptual set focuses on how prior context shapes the interpretation of sensory signals or the decision about them. A visual ambiguity task does not on its own demonstrate the motivational or belief-preserving processes studied in decision-making research. The two can interact, but their canonical explanatory domains differ: perceptual mechanisms belong here, while belief evaluation and judgment biases require a separate account. Firestone and Scholl (2016)

Perceptual set versus perceptual learning

Perceptual learning refers to relatively durable, experience-dependent changes in discrimination, feature sensitivity, or object categorization. Perceptual set often refers to temporary readiness elicited by a cue or immediate context. Long-term learning can furnish the representations and probabilities used by temporary expectations. The distinction is one of the research question and timescale, rather than a claim that learning and expectation never overlap. Goldstone (1998)

Perceptual set versus hallucination

An ordinary expectation-consistent interpretation of an ambiguous sound or image does not constitute a hallucination or a clinical diagnosis. Hallucinations are investigated with clinical and experimental frameworks that address experiences without corresponding external stimuli, their context, and their impact. One experimental program used conditioning to study hallucination-like reports and computational priors, but such findings cannot be used to diagnose an individual or to claim that ordinary perceptual set is a disorder. The present article concerns general psychological mechanisms and laboratory evidence. Powers et al. (2017)

How Researchers Measure Perceptual-Set Effects

Cue-validity and probabilistic-learning designs

A common design first establishes an expectation and then presents a target. The target can be preceded by valid, invalid, or neutral cues, and conditions can be matched for overall frequency, difficulty, response mappings, and timing. Researchers measure how expectations alter identification accuracy, response time, confidence, or the rate of detecting a target. Varying the probability that a cue predicts a stimulus tests how learned regularities affect behavior. de Lange et al. (2018)

Psychometric functions and signal detection analysis

Presenting a graded set of stimuli, from easy to hard, allows investigators to estimate psychometric functions and thresholds. In a yes/no detection task, hit and false-alarm rates can be analyzed jointly rather than treating more frequent affirmative reports as improved vision. In an identification task, confusion matrices reveal which alternatives are favored. Statistical models can examine sensitivity and criterion, but researchers must justify their distributional assumptions and test whether learning, lapses, or individual variability affect estimates. Bang and Rahnev (2017)

Pre-cue versus post-cue controls

A particularly informative test moves an expectation cue from before a stimulus to after it. A cue that arrives after the relevant sensory encoding cannot have prepared the initial input, but it can still influence a later decision. Comparing both conditions provides a way to test whether early sensory preparation is necessary for the observed behavioral shift. This approach helped identify decision-criterion contributions in orientation judgments. Bang and Rahnev (2017)

Brain imaging and decoding

Functional MRI, electroencephalography, and related methods can measure activity changes associated with predicted or surprising stimuli. Multivariate decoding can test whether neural patterns distinguish stimulus features, while event-related signals can provide timing information. These measures must be interpreted in relation to attention, adaptation, trial history, and the participant's decision. Brain activation patterns are correlates that help constrain hypotheses; they do not independently reveal precisely what an individual consciously experienced. Kok et al. (2012) Summerfield and de Lange (2014)

Reliability and reproducibility

An informative perceptual-set experiment should report its sampling, preregistered or transparently specified predictions where feasible, stimulus calibration, exclusion rules, effect sizes, uncertainty intervals, and alternate model fits. Researchers should account for trial-order learning, fatigue, cues that differ in salience, response-key habits, and selective reporting of significant contrasts. A dramatic ambiguous picture can demonstrate a perceptual possibility; robust generalization requires replicated, appropriately powered experiments with distinct measures of sensory sensitivity and response policy. These safeguards follow directly from the methodological challenges raised in the literature on top-down effects. Firestone and Scholl (2016)

Does Perceptual Set Help or Distort Perception?

In familiar environments, accurate expectations can make recognition faster and more resilient when sensory input is incomplete. Reading speech in background noise, identifying objects in their usual locations, and anticipating regular patterns all illustrate contexts in which earlier experience is informative. The benefit depends on the validity of the expectation and the ability to update it when contradictory evidence appears. Warren (1970) Peelen et al. (2024)

Errors emerge when learned expectations are poorly matched to current circumstances. An unusual playing card may initially be assigned to a familiar category; an unclear word may be mistaken for one that fits the sentence; a rarely encountered object may be overlooked or reported late. These outcomes have distinct experimental signatures. It is therefore more useful to ask whether the prior was appropriate, the sensory evidence was reliable, and the task rewarded a certain response than to label all expectation effects either helpful or harmful. Bruner and Postman (1949) Bang and Rahnev (2017)

Ordinary examples should not be stretched into claims about eyewitness accuracy, the success of clinical treatments, or broad interventions to remove perceptual bias. Such applications require direct research on their own populations, contexts, and outcomes. Perceptual set offers a scientific framework for formulating hypotheses about these settings; it is not itself a validated screening instrument or a treatment protocol.

The Scientific Debate: Does Cognition Directly Alter Perception?

A major debate asks whether high-level states, including beliefs, categories, motivations, and expectations, penetrate early perceptual experience. Vetter and Newen distinguish several senses of cognitive penetration across processing stages and argue that certain contextual effects are compatible with interaction between cognition and perception. They propose that the debate improves when investigators specify the type and timing of influence at issue. Vetter and Newen (2014)

Firestone and Scholl offered an influential methodological challenge: many apparent demonstrations of top-down perception can be explained by task demands, attention, memory, judgment, or stimulus confounds. They urge researchers to rule out these alternatives before concluding that a belief or desire has altered visual experience itself. This critique is especially pertinent when an experiment asks participants to describe ambiguous stimuli after receiving an expectation-generating cue. Firestone and Scholl (2016)

The contemporary evidence supports several narrower conclusions. Expectations can affect the speed and content of perceptual judgments. Certain experiments identify expectation-related changes in early visual processing and awareness-related measures. Other well-controlled studies find that shifts in response criterion explain substantial behavioral effects. Distinguishing these findings improves the scientific description of perceptual set: the term names a documented readiness and its effects, while the underlying mechanism remains an empirical question for each paradigm. Kok et al. (2012) Pinto et al. (2015) Bang and Rahnev (2017)

Frequently Asked Questions About Perceptual Set

What is a simple example of perceptual set?

A symbol between letters may be interpreted as B, whereas the same ambiguous symbol between numbers may be interpreted as 13. The surrounding sequence prepares the observer to use a particular category. The demonstration illustrates context-dependent interpretation, although it does not on its own establish which perceptual or decision process produced the response. de Lange et al. (2018)

How do past experiences influence what we perceive?

Repeated experience teaches the typical combinations of objects, features, and events in an environment. Those regularities inform expectations that can facilitate interpretation of incomplete signals. Training can also produce more durable changes in discrimination, a phenomenon studied under perceptual learning. Bar (2004) Goldstone (1998)

Can perceptual set make us see things that are not there?

Expectations can increase the likelihood of reporting a predicted alternative under uncertainty and can contribute to restoration effects when part of a familiar sensory pattern is masked. A report alone does not show that a completely absent stimulus generated a genuine sensory experience. Experiments must distinguish criterion changes, restoration of degraded information, and clinical or hallucination-like phenomena. Warren (1970) Bang and Rahnev (2017)

Is perceptual set the same as top-down processing?

Perceptual set is one way prior information can prepare or bias interpretation. Top-down processing is the broader category of influence from knowledge, context, and goals on ongoing processing. The terms overlap in their explanatory mechanisms, but top-down processing covers additional phenomena and theories. Summerfield and de Lange (2014)

Do expectations always override sensory evidence?

No universal rule makes the expected interpretation dominate. Results vary with stimulus clarity, cue reliability, attention, learned statistics, and response demands. Strong contradicting sensory information can support revision of an earlier expectation. Experiments are designed to measure how the balance changes under controlled conditions. de Lange et al. (2018)

Can perceptual set be measured with a single psychological test?

Perceptual set is investigated through multiple paradigms, including ambiguous-stimulus judgments, cue-validity manipulations, detection tasks, and probabilistic learning. Performance on one task reflects task-specific conditions and should not be treated as a comprehensive personality characteristic, screening diagnosis, or general clinical index. Bang and Rahnev (2017)

Conclusion

Perceptual set is the influence of established or momentary expectations on how sensory information is approached, interpreted, and reported. Its scientific importance lies in demonstrating how the meaning of a stimulus depends on learned regularities and current context. From the incongruous playing cards of early experimental psychology to contemporary neural decoding and psychophysical studies, research shows that expectations can organize recognition and influence responses. Its most rigorous modern interpretation also preserves distinctions among sensory processing, attention, conscious access, and decision criteria. Perceptual set names a real class of psychological effects; determining exactly how an expectation operates in a particular case requires evidence matched to the mechanism claimed. Bruner and Postman (1949) de Lange et al. (2018) Bang and Rahnev (2017)

Related Articles

Bottom-Up vs Top-Down Processing in Perception: Examples and Evidence explains the broader interaction between incoming sensory information and existing knowledge.

Visual Perception: How We Recognize Objects and Scenes examines the processes and models involved in recognizing visual patterns and meaningful environments.

Gestalt Principles of Perception: Grouping and Figure-Ground covers the organization of visual elements into structured percepts.

Optical Illusions: Why the Eyes and Brain Disagree presents evidence on why stable sensory configurations can yield surprising visual experiences.

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