Transparent Motion
Random-dot motion stimuli have been a workhorse of vision research for decades. When a field of identical dots moves according to a common pattern — such as translation, rotation, or expansion — observers readily perceive a coherent global motion, even when no individual dot uniquely specifies that motion. These stimuli have provided powerful tools for understanding how the visual system integrates local sensory signals into unified percepts.
Transparent-motion stimuli present an even more demanding challenge. Two dot patterns moving in different directions occupy the same region of visual space and thus the visual system must determine the most likely interpretation: numerous independent local dot motions or two coherently moving surfaces, one moving atop the other. This is the same problem, in simplified form, that the visual system faces with natural scenes which are typically composed of multiple moving objects overlapping in the visual image.
The demonstrations below illustrate two principles underlying transparent motion. The first (left) shows a classic transparent-motion display composed of two counter-rotating dot fields. Most observers will see one of the two surfaces ever so slightly in front of the other despite the absence of explicit depth cues. This depth-ordering is bistable with first one dot field, then the other, appearing in front over time. Depth-ordering is an inherent part of transparent-motion perception. The second demonstration (right) is nearly identical, except the identities of the individual dots are periodically exchanged between the two moving surfaces. Unless they scrutinize individual dots, most observers remain unaware of these exchanges, revealing that the perception of these primitive perceptual objects is seemingly independent of which particular elements happen to belong to those objects at any given moment.
Two Counter-Rotating Dot Fields (Dot Membership Constant)
Two superimposed dot fields rotate in opposite directions. Most observers perceive two distinct surfaces moving over one another rather than a single collection of independently moving dots.
Two Counter-Rotating Dot Fields (Dot Membership Swaps every 500 ms)
Same as stimulus to the left except that every 500 ms, 50% of the dots of the two dot fields switch color and rotation direction. Without close scutiny, this dot switching tends to go unnoticed emphasizing that its the global directions, rather than the local motions of the dots, that generally underlie our perception of these moving surfaces.
Transparent Motion and Object-Based Attention
Visual attention is often described as operating at multiple levels. Attention can be directed to a location in space (“where”), to a visual feature such as color or motion direction (“what”), or to an object or surface as a coherent perceptual entity. While spatial and feature-based attention are relatively easy to reconcile with the known organization of visual cortex, the mechanisms that allow selective processing of whole objects remain less well understood.
Transparent-motion stimuli provide a powerful way to study this problem. In these displays, two moving dot patterns are superimposed in the same region of space, yet observers perceive two distinct moving surfaces, one moving atop the other. Because the surfaces occupy the same location, spatial selection could not seemingly allow for the selective processing of one surface over the other. Yet Valdes-Sosa, Cobo, and Pinilla (1998) introduced a transparent-motion paradigm that demonstrated that observers can selectively process one of the two dot fields. In their design, observers report the translation direction of either a cued or an uncued dot field. It was found that observers report the translation direction of the cued dot field more reliably than the translation direction of the uncued dot field. Because translation direction is unpredictable and uncorrelated with the rotation direction, these results rule out feature-based attention to motion direction. Later studies also ruled out color-based selective processing (Mitchell, Stoner, Fallah, & Reynolds, 2003; see also Stoner and Blanc, 2010).
There have been numerous follow-up studies that have used variants of that design to investigate the behavioral and neural correlates of object-based attention. In our current set of studies we use a delayed-onset variant of this design. One of the two surfaces appears slightly later than the other; one of the dot fields then briefly translates, and observers report its direction. Stoner and Blanc (2010) and Çatak et al. (2022) discuss how this paradigm constitutes a simplified version of the original Valdes-Sosa et al. paradigm. They also offer a brief review of the various other studies that have built on the original work of Valdes-Sosa and colleagues.
The demonstrations below illustrate the basic cued and uncued conditions used with this design. For clarity, they are played at half speed with extended translation durations; only half of the dots within each field translate coherently. The left stimulus shows translations of the delayed surface; the right shows translations of the non-delayed surface. The delayed onset serves as an exogenous attentional cue (Reynolds, Alborzian, & Stoner, 2003) such that attention is briefly attached to the delayed dot field: Most observers find the translations easier to judge on the delayed surface — a result that has been interpreted as evidence for object- or surface-based selection.
Stoner and Blanc (2010) asked whether these effects were based on the global direction of motion and color configurations (as might be expected by demonstrations like that above) or rather were specific to dots of the two dot fields. Specifically, they swapped the color and motion directions of the dot fields at the time of translation. They found that the performance advantage was specific to the individual dots not the global feature configuration. This result is surprising given previous studies that have shown that the perception of these moving surfaces is relatively insensitive to the individual dots that happen to compose these dot fields (as observed in the demo above; refs to be added). These findings suggest that the selective process underlying these performance effects is spatially fine-grained (see Çatak et al., 2022). Stoner devised a model that can account for these results based on feedback from area MT and/or area MST onto area V1 neurons (Stoner, 2018, SFN poster). This model predicts that increasing the density of these dot fields would reduce the performance asymmetry as spatial selection, even if operating at a fine spatial scale, should break down as dots from the two fields crowd one another. Investigating the impact of spatially crowding these dots is one of the manipulations used in ongoing experiments.
Another area of investigation is the role of depth-order in these stimuli. As observed above, perceptual depth-ordering of these dot fields happens despite the absence of explicit depth cues. This suggests the possibility that depth may be an organizing principle by which the visual system selects one set of dots over the other. By explicitly introducing depth-from-disparity cues into these stimuli, we are investigating this hypothesis in another set of experiments.
Cued — delayed-onset field translates
The delayed (cued) dot field, shown in green, translates. Observers more reliably judge these cued translations than the corresponding uncued translations. (Cued refers to which set of dots was delayed at trial onset.)
Uncued — always-on field translates
The non-delayed (uncued) dot field, shown in green, translates. Observers judge these uncued translations less reliably than the corresponding cued translations.
Cued — with motion + color swap
At the moment of translation, both the colors and the rotation directions of the two dot fields are exchanged. Globally — in colors and motion — the resulting configuration matches the uncued no-swap demo above. Yet observers still judge these cued translations more reliably than corresponding uncued ones: the visual system somehow tracks the individual dots that were originally delayed, not just the global features (Stoner & Blanc, 2010).
Uncued — with motion + color swap
At the moment of translation, both the colors and the rotation directions of the two dot fields are exchanged. Globally the resulting configuration matches the cued no-swap demo above. Yet observers still judge these uncued translations less reliably than the corresponding cued ones, consistent with selection by individual-dot identity rather than global features.
For the Curious
For those curious about the underlying science, here is a selection of relevant papers organized by topic.
Introductory / Conceptual
- – Duncan (1984) — Selective attention and the organization of visual information. The foundational paper establishing objects as units of attentional selection.
- – Cavanagh (2011) — Visual Cognition. Vision Research, 51(13), 1538–1551. An accessible review of object-based attention and its relationship to visual cognition more broadly.
Transparent Motion and Superimposed Stimuli
- – Valdés-Sosa, Cobo & Pinilla (2000) — Attention to object files defined by transparent motion. Demonstrates that transparently overlapping motion fields define distinct attentional objects.
- – Reynolds, Alborzian & Stoner (2003) — Exogenously cued attention triggers competitive selection of surfaces. Vision Research, 43(1), 59–66.
- – Stoner & Blanc (2010) — Exploring the mechanisms underlying surface-based stimulus selection. Vision Research, 50(2), 229–238.
- – Çatak, Özkan, Kafaligonul & Stoner (2022) — Behavioral and ERP evidence that object-based attention utilizes fine-grained spatial mechanisms. Cortex, 151, 89–104.
Neural / ERP / Physiological Studies
- – O'Craven, Downing & Kanwisher (1999) — fMRI evidence for objects as the units of attentional selection. Nature, 401, 584–587.
- – Hillyard, Vogel & Luck (1998) — Sensory gain control as a mechanism of selective attention: electrophysiological and neuroimaging evidence.
- – Hillyard & Anllo-Vento (1998) — Event-related brain potentials in the study of visual selective attention.
- – Wannig, Rodríguez & Freiwald (2007) — Attention to surfaces modulates motion processing in extrastriate area MT. Nature Neuroscience, 10, 803–809.
- – Roelfsema (2006) — Cortical algorithms for perceptual grouping. Annual Review of Neuroscience, 29, 203–227.
Broader Reviews
- – Scholl (2001) — Objects and attention: The state of the art. Cognition, 80, 1–46. A comprehensive review of the field.
- – Chen (2012) — Object-based attention: A tutorial review. Attention, Perception, & Psychophysics, 74, 784–802.
- – Frontiers Review (2016) — Mechanisms of Object-Based Attention.
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Computational Modeling
Re-implementing the published accounts of surface-based selection
Transparent, parameter-by-parameter models we can falsify against the VR data.
Starting with the motion-competition model of Stoner & Blanc (2010) — every prediction traces back to explicit neurons and equations.
For Collaborators
Access by invitation
Internal data, session logs, analysis scripts, and experimental protocols are available to invited collaborators. To request access contact Generstoner@gmail.com.