Seeing “what” through “why”: Evidence from probing the causal structure of hierarchical motion.

Xu, Haokui; Tang, Ning; Zhou, Jifan; Shen, Mowei; Gao, Tao

doi:10.1037/xge0000310

Cited by 11 publications

(17 citation statements)

References 67 publications

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“…Previous research has shown that causal inference and the perception of co-occurrence in events are strongly related. Causal inference can affect the perceptual organization of events: Since Heider (1958), psychologists have seen causal inference as a means of imposing order on the environment, and organizing multiple stimuli into coherent units or Gestalts (Read, Vanman, & Miller, 1997;Xu, Tang, Zhou, Shen, & Gao, 2017). Conversely, causal inference is strongly influenced by the perception of at least two kinds of regularity.…”

Section: Lessons From the Literature On Co-occurrence And Causal Infementioning

confidence: 99%

Suspicious binds: Conspiracy thinking and tenuous perceptions of causal connections between co‐occurring and spuriously correlated events

Wal

Sutton

Lange

et al. 2018

Euro J Social Psych

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Previous research indicates that conspiracy thinking is informed by the psychological imposition of order and meaning on the environment, including the perception of causal relations between random events. Four studies indicate that conspiracy belief is driven by readiness to draw implausible causal connections even when events are not random, but instead conform to an objective pattern. Study 1 (N = 195) showed that conspiracy belief was related to the causal interpretation of real‐life, spurious correlations (e.g., between chocolate consumption and Nobel prizes). In Study 2 (N = 216), this effect held adjusting for correlates including magical and non‐analytical thinking. Study 3 (N = 214) showed that preference for conspiracy explanations was associated with the perception that a focal event (e.g., the death of a journalist) was causally connected to similar, recent events. Study 4 (N = 211) showed that conspiracy explanations for human tragedies were favored when they comprised part of a cluster of similar events (vs. occurring in isolation); crucially, they were independently increased by a manipulation of causal perception. We discuss the implications of these findings for previous, mixed findings in the literature and for the relation between conspiracy thinking and other cognitive processes.

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Section: Lessons From the Literature On Co-occurrence And Causal Infementioning

confidence: 99%

Suspicious binds: Conspiracy thinking and tenuous perceptions of causal connections between co‐occurring and spuriously correlated events

Wal

Sutton

Lange

et al. 2018

Euro J Social Psych

View full text Add to dashboard Cite

show abstract

“…Understanding motion perception as Bayesian inference has a rich scientific history [10,11,16,[23][24][25][26][27]. Bayesian models of low-level perception [23][24][25] were extended to explain human multiple object tracking of independent dot movement [16,27].…”

Section: Discussionmentioning

confidence: 99%

“…Our work extends this line of research to structured motion, revealing the use of structured motion priors during tracking. Our aim to resolve the fine structure of human motion priors led to the development of a novel probabilistic multiple object prediction task that augments single object prediction [11] with velocity covariances within a tractable protocol. Including posterior covariance matrices in the observer model greatly enhanced the log-likelihood ratios in the prediction task beyond the resolution achievable in single object prediction (see Appendix, Fig.…”

Section: Discussionmentioning

confidence: 99%

“…We further colored the dots according to their role in the motion structure to prevent dot confusion. In contrast to previous single-dot prediction tasks [11], the rationale for simultaneously predicting two dot locations is that the covariance pattern of errors convey additional information about the motion structure assumptions of our participants. For example, if global motion was assumed, we would expect the participants to jointly over-or underestimate the red and green targets' final locations.…”

Section: Revealing the Structure Of Human Motion Priorsmentioning

confidence: 93%

“…In some cases this is because we perceive objects as deforming non-rigidly. In other cases, we perceive objects that are hierarchically structured [9][10][11]: the parts of an object move rigidly relative to a reference frame (the object), which itself could be a rigidly moving part of another object, and so on. For example, we perceive the motion of hands relative to the motion of arms, and the motion of arms relative to the motion of the torso (Fig.…”

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confidence: 99%

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Hierarchical structure is employed by humans during visual motion perception

Bill

Pailian

Gershman

et al. 2019

Preprint

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In the real world, complex dynamic scenes often arise from the composition of simpler parts. The visual system exploits this structure by hierarchically decomposing dynamic scenes: when we see a person walking on a train or an animal running in a herd, we recognize the individual's movement as nested within a reference frame that is itself moving. Despite its ubiquity, surprisingly little is understood about the computations underlying hierarchical motion perception. To address this gap, we develop a novel class of stimuli that grant tight control over statistical relations among object velocities in dynamic scenes. We first demonstrate that structured motion stimuli benefit human multiple object tracking performance. This performance advantage is well-explained by a Bayesian observer model that exploits hierarchical structure. A second experiment, using a motion prediction task, reinforced this conclusion and provided fine-grained information about how the visual system flexibly exploits motion structure.The visual scenes our brains perceive in everyday life are filled with complex dynamics. Information hitting the retina changes not only with every motion in the scene, but also with every head movement and saccade. Noise, occlusions, and ambiguities further make visual information inherently unreliable. In order to maintain stable, coherent percepts in the face of complex and unreliable inputs, our brains exploit the spatially and temporally structured nature of the environment [1].Motion structure refers to statistical relations of velocities. One form of structure common in natural scenes is motion grouping: when a rigid object is set in motion, all of its visual features move coherently. This structure allows us to infer the existence of objects based on the coherent motion of features-the Gestalt grouping cue known as common fate [2]. Grouping based on common fate has been shown to influence our ability to track objects [3][4][5][6], to search displays [7], and to store information in short-term memory [8].However, the strict definition of common fate is too brittle to accommodate natural scenes in which visual features do not move together rigidly and yet are still grouped together. In some cases this is because we perceive objects as deforming non-rigidly. In other cases, we perceive objects that are hierarchically structured [9][10][11]: the parts of an object move rigidly relative to a reference frame (the object), which itself could be a rigidly moving part of another object, and so on. For example, we perceive the motion of hands relative to the motion of arms, and the motion of arms relative to the motion of the torso (Fig. 1A,B). The entire body may be moving relative to another reference frame (a train or escalator). The perception of hierarchically organized motion suggests a powerful "divide-and-conquer" strategy for parsing complex dynamic scenes.Recent work has formalized the representation and discovery of hierarchical motion structures [10]. However, we still know relatively little about if a...

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