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An empirical explanation of the speed-distance effect.

ABSTRACT: Understanding motion perception continues to be the subject of much debate, a central challenge being to account for why the speeds and directions seen accord with neither the physical movements of objects nor their projected movements on the retina. Here we investigate the varied perceptions of speed that occur when stimuli moving across the retina traverse different projected distances (the speed-distance effect). By analyzing a database of moving objects projected onto an image plane we show that this phenomenology can be quantitatively accounted for by the frequency of occurrence of image speeds generated by perspective transformation. These results indicate that speed-distance effects are determined empirically from accumulated past experience with the relationship between image speeds and moving objects.

SUBMITTER: Wojtach WT

PROVIDER: S-EPMC2727946 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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An empirical explanation of the speed-distance effect.

Wojtach William T WT Sung Kyongje K Purves Dale D

PloS one 20090826 8

Understanding motion perception continues to be the subject of much debate, a central challenge being to account for why the speeds and directions seen accord with neither the physical movements of objects nor their projected movements on the retina. Here we investigate the varied perceptions of speed that occur when stimuli moving across the retina traverse different projected distances (the speed-distance effect). By analyzing a database of moving objects projected onto an image plane we show ...[more]

PMID: 19707552

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Project description:Although estimating travel distance is essential to our ability to move through the world, our distance estimates can be inaccurate. These odometric errors occur because people tend to perceive that they have moved further than they had. Many of the studies investigating the perception of travel distance have primarily used forward translational movements, and postulate that perceived travel distance results from integration over distance and is independent of travel speed. Speed effects would imply integration over time as well as space. To examine travel distance perception with different directions and speeds, we used virtual reality (VR) to elicit visually induced self-motion. Participants (n = 15) were physically stationary while being visually "moved" through a virtual corridor, either judging distances by stopping at a previously seen target (Move-To-Target Task) or adjusting a target to the previous movement made (Adjust-Target Task). We measured participants' perceived travel distance over a range of speeds (1-5 m/s) and distances in four directions (up, down, forward, backward). We show that the simulated speed and direction of motion differentially affect the gain (perceived travel distance / actual travel distance). For the Adjust-Target task, forwards motion was associated with smaller gains than either backward, up, or down motion. For the Move-To-Target task, backward motion was associated with smaller gains than either forward, up or down motion. For both tasks, motion at the slower speed was associated with higher gains than the faster speeds. These results show that transforming visual motion into travel distance differs depending on the speed and direction of optic flow being perceived. We also found that a common model used to study the perception of travel distance was a better fit for the forward direction compared to the others. This implies that the model should be modified for these different non-forward motion directions.

Project description:BackgroundSpeed and distance traveled provide quantifiable links between behavior and energetics, and are among the metrics most routinely estimated from animal tracking data. Researchers typically sum over the straight-line displacements (SLDs) between sampled locations to quantify distance traveled, while speed is estimated by dividing these displacements by time. Problematically, this approach is highly sensitive to the measurement scale, with biases subject to the sampling frequency, the tortuosity of the animal's movement, and the amount of measurement error. Compounding the issue of scale-sensitivity, SLD estimates do not come equipped with confidence intervals to quantify their uncertainty.MethodsTo overcome the limitations of SLD estimation, we outline a continuous-time speed and distance (CTSD) estimation method. An inherent property of working in continuous-time is the ability to separate the underlying continuous-time movement process from the discrete-time sampling process, making these models less sensitive to the sampling schedule when estimating parameters. The first step of CTSD is to estimate the device's error parameters to calibrate the measurement error. Once the errors have been calibrated, model selection techniques are employed to identify the best fit continuous-time movement model for the data. A simulation-based approach is then employed to sample from the distribution of trajectories conditional on the data, from which the mean speed estimate and its confidence intervals can be extracted.ResultsUsing simulated data, we demonstrate how CTSD provides accurate, scale-insensitive estimates with reliable confidence intervals. When applied to empirical GPS data, we found that SLD estimates varied substantially with sampling frequency, whereas CTSD provided relatively consistent estimates, with often dramatic improvements over SLD.ConclusionsThe methods described in this study allow for the computationally efficient, scale-insensitive estimation of speed and distance traveled, without biases due to the sampling frequency, the tortuosity of the animal's movement, or the amount of measurement error. In addition to being robust to the sampling schedule, the point estimates come equipped with confidence intervals, permitting formal statistical inference. All the methods developed in this study are now freely available in the ctmmR package or the ctmmweb point-and-click web based graphical user interface.

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An empirical explanation of the speed-distance effect.

Publications

An empirical explanation of the speed-distance effect.

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