Systematic Biases in Human Heading Estimation

Cuturi, Luigi F.; MacNeilage, Paul R.

doi:10.1371/journal.pone.0056862

Cited by 52 publications

(97 citation statements)

References 43 publications

(63 reference statements)

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“…Apart from the variability of dispersion observed in experiment I, the findings on dispersion are consistent with the literature: inertial dispersion is larger than visual dispersion, and patterns in dispersion show that the smallest values occur around the cardinal axes, with values increasing as the heading angle deviates away from these axes [17, 21, 22, 27]. …”

Section: Discussionsupporting

confidence: 89%

“…In a number of recent studies, both visual and inertial heading estimates were found to be biased away from the cardinal axes [21, 22, 27]. The present data show that visual heading estimates are on average also biased away from the fore-aft axis, in both experiments; inertial heading estimates were biased away from the cardinal axes in experiment I and biased towards the cardinal axes in experiment II.…”

Section: Discussionsupporting

confidence: 56%

“…Interestingly, the absence of a decline in the size of sensory bias for longer duration motions supports the notion that biases in heading estimation result from non-uniformity in the distribution of preferred directions rather than a-priori preferences for particular heading directions [22]; if bias in heading estimation was due to a-priori beliefs favoring particular directions, the relative impact of these beliefs on the resultant estimate should decline for longer duration motions, as accumulating sensory evidence devoid of bias would eventually outweigh any prior beliefs.…”

Section: Discussionmentioning

confidence: 65%

“…From the responses obtained in the unisensory conditions, we determined whether patterns of bias and dispersion differed between motion profiles, and whether observations corresponded to the literature [17, 21, 22]; from the responses obtained in the multisensory conditions, we firstly determined whether either of a number of variants of a CI model could account for the data, and secondly whether there were differences in model parameters for different motion profiles.…”

Section: Resultsmentioning

confidence: 99%

“…Unisensory visual and inertial heading estimation were described using a model that can account for periodic patterns of bias and dispersion as these are reported in the literature [17, 21, 22, 29]. …”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

Causal Inference in Multisensory Heading Estimation

2017

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A large body of research shows that the Central Nervous System (CNS) integrates multisensory information. However, this strategy should only apply to multisensory signals that have a common cause; independent signals should be segregated. Causal Inference (CI) models account for this notion. Surprisingly, previous findings suggested that visual and inertial cues on heading of self-motion are integrated regardless of discrepancy. We hypothesized that CI does occur, but that characteristics of the motion profiles affect multisensory processing. Participants estimated heading of visual-inertial motion stimuli with several different motion profiles and a range of intersensory discrepancies. The results support the hypothesis that judgments of signal causality are included in the heading estimation process. Moreover, the data suggest a decreasing tolerance for discrepancies and an increasing reliance on visual cues for longer duration motions.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 56%

Section: Discussionmentioning

confidence: 65%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Causal Inference in Multisensory Heading Estimation

2017

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Optimal visual–vestibular integration under conditions of conflicting intersensory motion profiles

2014

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Passive movement through an environment is typically perceived by integrating information from different sensory signals, including visual and vestibular information. A wealth of previous research in the field of multisensory integration has shown that if different sensory signals are spatially or temporally discrepant, they may not combine in a statistically optimal fashion; however, this has not been well explored for visual-vestibular integration. Self-motion perception involves the integration of various movement parameters including displacement, velocity, acceleration and higher derivatives such as jerk. It is often assumed that the vestibular system is optimized for the processing of acceleration and higher derivatives, while the visual system is specialized to process position and velocity. In order to determine the interactions between different spatiotemporal properties for self-motion perception, in Experiment 1, we first asked whether the velocity profile of a visual trajectory affects discrimination performance in a heading task. Participants performed a two-interval forced choice heading task while stationary. They were asked to make heading discriminations while the visual stimulus moved at a constant velocity (C-Vis) or with a raised cosine velocity (R-Vis) motion profile. Experiment 2 was designed to assess how the visual and vestibular velocity profiles combined during the same heading task. In this case, participants were seated on a Stewart motion platform and motion information was presented via visual information alone, vestibular information alone or both cues combined. The combined condition consisted of congruent blocks (R-Vis/R-Vest) in which both visual and vestibular cues consisted of a raised cosine velocity profile and incongruent blocks (C-Vis/R-Vest) in which the visual motion profile consisted of a constant velocity motion, while the vestibular motion consisted of a raised cosine velocity profile. Results from both Experiments 1 and 2 demonstrated that visual heading estimates are indeed affected by the velocity profile of the movement trajectory, with lower thresholds observed for the R-Vis compared to the C-Vis. In Exp. 2 when visual-vestibular inputs were both present, they were combined in a statistically optimal fashion irrespective of the type of visual velocity profile, thus demonstrating robust integration of visual and vestibular cues. The study suggests that while the time course of the velocity did affect visual heading judgments, a moderate conflict between visual and vestibular motion profiles does not cause a breakdown in optimal integration for heading.

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Perception of rotation, path, and heading in circular trajectories

et al. 2016

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When in darkness, humans can perceive the direction and magnitude of rotations and of linear translations in the horizontal plane. The current paper addresses the integrated perception of combined translational and rotational motion, as it occurs when moving along a curved trajectory. We questioned whether the perceived motion through the environment follows the predictions of a self-motion perception model (e.g., Merfeld et al. in J Vestib Res 3:141–161, 1993; Newman in A multisensory observer model for human spatial orientation perception, 2009), which assume linear addition of rotational and translational components. For curved motion in darkness, such models predict a non-veridical motion percept, consisting of an underestimation of the perceived rotation, a distortion of the perceived travelled path, and a bias in the perceived heading (i.e., the perceived instantaneous direction of motion with respect to the body). These model predictions were evaluated in two experiments. In Experiment 1, seven participants were moved along a circular trajectory in darkness while facing the motion direction. They indicated perceived yaw rotation using an online tracking task, and perceived travelled path by drawings. In Experiment 2, the heading was systematically varied, and six participants indicated, in a 2-alternative forced-choice task, whether they perceived facing inward or outward of the circular path. Overall, we found no evidence for the heading bias predicted by the model. This suggests that the sum of the perceived rotational and translational components alone cannot adequately explain the overall perceived motion through the environment. Possibly, knowledge about motion dynamics and familiar stimuli combinations may play an important additional role in shaping the percept.

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Systematic Biases in Human Heading Estimation

Cited by 52 publications

References 43 publications

Causal Inference in Multisensory Heading Estimation

Causal Inference in Multisensory Heading Estimation

Optimal visual–vestibular integration under conditions of conflicting intersensory motion profiles

Perception of rotation, path, and heading in circular trajectories

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