The reverse motion illusion in random dot motion displays and implications for understanding development.
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ABSTRACT:
SUBMITTER: Manning C
PROVIDER: S-EPMC7612299 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Computational models of motion perception suggest that the perceived direction of weak motion signals may sometimes be directly opposite to the true stimulus motion direction. However, this possibility cannot be assessed by using standard 2AFC motion discrimination paradigms because two opposite directions of motion were used in most studies (e.g., leftward vs. rightward). We were able to obtain robust evidence of opposite-direction motion reports by using a random-dot-kinematogram (RDK) paradigm in which the motion direction varied over 360° and observers were asked to estimate the exact motion direction. These opposite-direction motion reports were replicable across multiple display types and feedback conditions, and observers had greater confidence in their opposite-direction responses than in true guess responses. When we fed RDKs into a computational model of motion processing, we found that the model estimated substantial motion activity in the direction opposite to the coherent stimulus direction, even though no such motion was objectively present in the stimuli, suggesting that the opposite-direction motion perception may be a consequence of the properties of motion-selective neurons in visual cortex. Together, these results demonstrate that the known properties of the visual system may lead to reports of motion that are directly opposite to the true direction.
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Project description:Random Dot Motion (RDM) displays refer to clouds of independently moving dots that can be parametrically manipulated to provide a perception of the overall cloud moving coherently in a specified direction of motion. As a well-studied probe of motion perception, RDMs have been widely employed to understand underlying neural mechanisms of motion perception, perceptual decision-making, and perceptual learning, among other processes. Despite their wide use, RDM stimuli implementation is highly dependent on the parameters and the generation algorithm of the stimuli; both can greatly influence behavioral performance on RDM tasks. With the advent of the COVID pandemic and an increased need for more accessible platforms, we aimed to validate a novel RDM paradigm on Inquisit Millisecond, a platform for the online administration of cognitive and neuropsychological tests and assessments. We directly compared, in the same participants using the same display, a novel RDM paradigm on both Inquisit Millisecond and MATLAB with Psychtoolbox. We found that psychometric functions of Coherence largely match between Inquisit Millisecond and MATLAB, as do the effects of Duration. These data demonstrate that the Millisecond RDM provides data largely consistent with those previously found in laboratory-based systems, and the present findings can serve as a reference point for expected thresholds for when these procedures are used remotely on different platforms.
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Project description:The performance of Watson & Ahumada's model of human visual motion sensing is compared against human psychophysical performance. The stimulus consists of random dots undergoing rotary motion, displayed in a circular annulus. The model matches psychophysical observer performance with respect to most parameters. It is able to replicate some key psychophysical findings such as invariance of observer performance to dot density in the display, and decrease of observer performance with frame duration of the display.Associated with the concept of rotary motion is the notion of a center about which rotation occurs. One might think that for accurate estimation of rotary motion in the display, this center must be accurately known. A simple vector analysis reveals that this need not be the case. Numerical simulations confirm this result, and may explain the position invariance of MST(d) cells. Position invariance is the experimental finding that rotary motion sensitive cells are insensitive to where in their receptive field rotation occurs.When all the dots in the display are randomly drawn from a uniform distribution, illusory rotary motion is perceived. This case was investigated by Rose & Blake previously, who termed the illusory rotary motion the omega effect. Two important experimental findings are reported concerning this effect. First, although the display of random dots evokes perception of rotary motion, the direction of motion perceived does not depend on what dot pattern is shown. Second, the time interval between spontaneous flips in perceived direction is lognormally distributed (mode approximately 2 s). These findings suggest the omega effect fits in the category of a typical bistable illusion, and therefore the processes that give rise to this illusion may be the same processes that underlie much of other bistable phenomenon.
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Project description:The popular random-dot motion (RDM) task has recently been applied to multiple-choice perceptual decision-making. However, changes in the number of alternatives on an RDM display lead to changes in the similarity between the alternatives, complicating the study of multiple-choice effects. To disentangle the effects of similarity and number of alternatives, we analyzed behavior in the RDM task using an optimal-observer model. The model applies Bayesian principles to give an account of how changes in the stimulus influence the decision-making process. A possible neural implementation of the optimal-observer model is discussed, and we provide behavioral data that support the model. We verify the predictions from the optimal-observer model by fitting a descriptive model of choice behavior (the linear ballistic accumulator model) to the behavioral data. The results show that (a) there is a natural interaction in the RDM task between similarity and the number of alternatives; (b) the number of alternatives influences “response caution”, whereas the similarity between the alternatives influences “drift rate”; and (c) decisions in the RDM task are near optimal when participants are presented with multiple alternatives.
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Project description:When the visual system analyzes distributed patterns of sensory inputs, what features of those distributions does it use? It has been previously demonstrated that higher-order statistical moments of luminance distributions influence perception of static surfaces and textures. Here, we tested whether the brain also represents higher-order moments of dynamic stimuli. We constructed random dot kinematograms, where dots moved according to probability distributions that selectively differed in terms of their mean, variance, skewness, or kurtosis. When viewing these stimuli, human observers were sensitive to the mean direction of coherent motion and to the variance of dot displacement angles, but they were insensitive to skewness and kurtosis. Observer behavior accorded with a model of directional motion energy, suggesting that information about higher-order moments is discarded early in the visual processing hierarchy. These results demonstrate that use of higher-order moments is not a general property of visual perception.
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Project description:All moving objects generate sequential retinotopic activations representing a series of discrete locations in space and time (motion trajectory). How direction-selective neurons in mammalian early visual cortices process motion trajectory remains to be clarified. Using single-cell recording and optical imaging of intrinsic signals along with mathematical simulation, we studied response properties of cat visual areas 17 and 18 to random dots moving at various speeds. We found that, the motion trajectory at low speed was encoded primarily as a direction signal by groups of neurons preferring that motion direction. Above certain transition speeds, the motion trajectory is perceived as a spatial orientation representing the motion axis of the moving dots. In both areas studied, above these speeds, other groups of direction-selective neurons with perpendicular direction preferences were activated to encode the motion trajectory as motion-axis information. This applied to both simple and complex neurons. The average transition speed for switching between encoding motion direction and axis was about 31°/s in area 18 and 15°/s in area 17. A spatio-temporal energy model predicted the transition speeds accurately in both areas, but not the direction-selective indexes to random-dot stimuli in area 18. In addition, above transition speeds, the change of direction preferences of population responses recorded by optical imaging can be revealed using vector maximum but not vector summation method. Together, this combined processing of motion direction and axis by neurons with orthogonal direction preferences associated with speed may serve as a common principle of early visual motion processing.
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Project description:Random dot motion (RDM) displays have emerged as one of the standard stimulus types employed in psychophysical and physiological studies of motion processing. RDMs are convenient because it is straightforward to manipulate the relative motion energy for a given motion direction in addition to stimulus parameters such as the speed, contrast, duration, density, aperture, etc. However, as widely as RDMs are employed so do they vary in their details of implementation. As a result, it is often difficult to make direct comparisons across studies employing different RDM algorithms and parameters. Here, we systematically measure the ability of human subjects to estimate motion direction for four commonly used RDM algorithms under a range of parameters in order to understand how these different algorithms compare in their perceptibility. We find that parametric and algorithmic differences can produce dramatically different performances. These effects, while surprising, can be understood in relationship to pertinent neurophysiological data regarding spatiotemporal displacement tuning properties of cells in area MT and how the tuning function changes with stimulus contrast and retinal eccentricity. These data help give a baseline by which different RDM algorithms can be compared, demonstrate a need for clearly reporting RDM details in the methods of papers, and also pose new constraints and challenges to models of motion direction processing.
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Project description:The study of neuronal responses to random-dot motion patterns has provided some of the most valuable insights into how the activity of neurons is related to perception. In the opposite directions of motion paradigm, the motion signal strength is decreased by manipulating the coherence of random dot patterns to examine how well the activity of single neurons represents the direction of motion. To extend this paradigm to populations of neurons, studies have used modelling based on data from pairs of neurons, but several important questions require further investigation with larger neuronal datasets. We recorded neuronal populations in the middle temporal (MT) and medial superior temporal (MST) areas of anaesthetized marmosets with electrode arrays, while varying the coherence of random dot patterns in two opposite directions of motion (left and right). Using the spike rates of simultaneously recorded neurons, we decoded the direction of motion at each level of coherence with linear classifiers. We found that the presence of correlations had a detrimental effect to decoding performance, but that learning the correlation structure produced better decoding performance compared to decoders that ignored the correlation structure. We also found that reducing motion coherence increased neuronal correlations, but decoders did not need to be optimized for each coherence level. Finally, we showed that decoder weights depend of left-right selectivity at 100% coherence, rather than the preferred direction. These results have implications for understanding how the information encoded by populations of neurons is affected by correlations in spiking activity.
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