Piers D. L. Howe

Using fMRI to distinguish components of the multiple object tracking task.

Multiple object tracking (MOT) has proven to be a powerful technique for studying sustained selective attention. However, surprisingly little is known about its underlying neural mechanisms. Previous fMRI investigations have identified several brain areas thought to be involved in MOT, but there were disagreements between the studies, none distinguished between the act of tracking targets and the act of attending targets, and none attempted to determine which of these brain areas interact with each other. Here we address these three issues. First, using more observers and a random effects analysis, we show that some of the previously identified areas may not play a specific role in MOT. Second, we show that the frontal eye fields (FEF), the anterior intraparietal sulcus (AIPS), the superior parietal lobule (SPL), the posterior intraparietal sulcus (PIPS) and the human motion area (MT+) are differentially activated by the act of tracking, as distinguished from the act of attention. Finally, by using an algorithm modified from the computer science literature, we were able to map the interactions between these brain areas.

Can we improve clinical prediction of at-risk older drivers?

OBJECTIVES To conduct a pilot study to evaluate the predictive value of the Montreal Cognitive Assessment test (MoCA) and a brief test of multiple object tracking (MOT) relative to other tests of cognition and attention in identifying at-risk older drivers, and to determine which combination of tests provided the best overall prediction. METHODS Forty-seven currently licensed drivers (58-95 years), primarily from a clinical driving evaluation program, participated. Their performance was measured on: (1) a screening test battery, comprising MoCA, MOT, Mini-Mental State Examination (MMSE), Trail-Making Test, visual acuity, contrast sensitivity, and Useful Field of View (UFOV) and (2) a standardized road test. RESULTS Eighteen participants were rated at-risk on the road test. UFOV subtest 2 was the best single predictor with an area under the curve (AUC) of .84. Neither MoCA nor MOT was a better predictor of the at-risk outcome than either MMSE or UFOV, respectively. The best four-test combination (MMSE, UFOV subtest 2, visual acuity and contrast sensitivity) was able to identify at-risk drivers with 95% specificity and 80% sensitivity (.91 AUC). CONCLUSIONS Although the best four-test combination was much better than a single test in identifying at-risk drivers, there is still much work to do in this field to establish test batteries that have both high sensitivity and specificity.

The what–where trade-off in multiple-identity tracking

Observers are poor at reporting the identities of objects that they have successfully tracked (Pylyshyn, Visual Cognition, 11, 801–822, 2004; Scholl & Pylyshyn, Cognitive Psychology, 38, 259–290, 1999). Consequently, it has been claimed that objects are tracked in a manner that does not encode their identities (Pylyshyn, 2004). Here, we present evidence that disputes this claim. In a series of experiments, we show that attempting to track the identities of objects can decrease an observer’s ability to track the objects’ locations. This indicates that the mechanisms that track, respectively, the locations and identities of objects draw upon a common resource. Furthermore, we show that this common resource can be voluntarily distributed between the two mechanisms. This is clear evidence that the location- and identity-tracking mechanisms are not entirely dissociable.

Hemifield Effects in Multiple Identity Tracking

In everyday life, we often need to attentively track moving objects. A previous study has claimed that this tracking occurs independently in the left and right visual hemifields (Alvarez & Cavanagh, 2005, Psychological Science,16, 637–647). Specifically, it was shown that observers were much more accurate at tracking objects that were spread over both visual hemifields as opposed to when all were confined to a single visual hemifield. In that study, observers were not required to remember the identities of the objects. Conversely, in real life, there is seldom any benefit to tracking an object unless you can also recall its identity. It has been predicted that when observers are required to remember the identities of the tracked objects a bilateral advantage should no longer be observed (Oksama & Hyönä, 2008, Cognitive Psychology, 56, 237–283). We tested this prediction and found that a bilateral advantage still occurred, though it was not as strong as when observers were not required to remember the identities of the targets. Even in the later case we found that tracking was not completely independent in the two visual hemifields. We present a combined model of multiple object tracking and multiple identity tracking that can explain our data.

Motion information is sometimes used as an aid to the visual tracking of objects

In everyday life, observers often need to visually track moving objects. Currently, there is a debate as to whether observers utilize motion information in doing this or whether they rely purely on positional information (e.g., frame-by-frame locations). In our experiments, we had observers keep track of a subset of moving objects. In one condition, the objects moved in straight lines and their future positions were thus predictable. In a second condition, the objects changed directions randomly. Across three experiments, tracking performance was better in the predictable condition, suggesting that observers can use motion to help them track objects, at least when tracking just two. When tracking four objects, performance was not different between the two conditions. We discuss these findings in relation to several theories of object tracking.

Remapping attention in multiple object tracking

Which coordinate system do we use to track moving objects? In a previous study using smooth pursuit eye movements, we argued that targets are tracked in both retinal (retinotopic) and scene-centered (allocentric) coordinates (Howe, Pinto, & Horowitz, 2010). However, multiple object tracking typically also elicits saccadic eye movements, which may change how object locations are represented. Observers fixated a cross while tracking three targets out of six identical disks confined to move within an imaginary square. The fixation cross alternated between two locations, requiring observers to make repeated saccades. By moving (or not moving) the imaginary square in sync with the fixation cross, we could disrupt either (or both) coordinate systems. Surprisingly, tracking performance was much worse when the objects moved with the fixation cross, although this manipulation preserved the retinal image across saccades, thereby avoiding the visual disruptions normally associated with saccades. Instead, tracking performance was best when the allocentric coordinate system was preserved, suggesting that targets locations are maintained in that coordinate system across saccades. This is consistent with a theoretical framework in which the positions of a small set of attentional pointers are predictively updated in advance of a saccade.

White's effect : Removing the junctions but preserving the strength of the illusion

Whites effect (also known as the Munker-White effect) is a lightness illusion in which, contrary to expectations based on simultaneous contrast and Wallachs rule, a gray rectangle predominantly surrounded by white appears lighter than an identical rectangle that is mainly surrounded by black. The illusion is often explained in terms of T-junctions that are formed by the three-way intersection of the gray rectangle, a black stripe, and a white stripe. I present a circular variant of Whites effect in which all the junctions have been removed without significantly affecting the strength of the illusion, suggesting that junctions are not an important consideration in all versions of Whites effect.

Resource demands of object tracking and differential allocation of the resource

The attentional processes for tracking moving objects may be largely hemisphere-specific. Indeed, in our first two experiments the maximum object speed (speed limit) for tracking targets in one visual hemifield (left or right) was not significantly affected by a requirement to track additional targets in the other hemifield. When the additional targets instead occupied the same hemifield as the original targets, the speed limit was reduced. At slow target speeds, however, adding a second target to the same hemifield had little effect. At high target speeds, the cost of adding a same-hemifield second target was approximately as large as would occur if observers could only track one of the targets. This shows that performance with a fast-moving target is very sensitive to the amount of resource allocated. In a third experiment, we investigated whether the resources for tracking can be distributed unequally between two targets. The speed limit for a given target was higher if the second target was slow rather than fast, suggesting that more resource was allocated to the faster of the two targets. This finding was statistically significant only for targets presented in the same hemifield, consistent with the theory of independent resources in the two hemifields. Some limited evidence was also found for resource sharing across hemifields, suggesting that attentional tracking resources may not be entirely hemifield-specific. Together, these experiments indicate that the largely hemisphere-specific tracking resource can be differentially allocated to faster targets.

The effect of visual distinctiveness on multiple object tracking performance.

Observers often need to attentively track moving objects. In everyday life, such objects are often visually distinctive. Previous studies have shown that tracking accuracy is increased when the targets contain a visual feature (e.g., a color) not possessed by the distractors. Conversely, a gain in tracking accuracy was not observed when the targets differed from the distractors by only a conjunction of features (Makovski and Jiang, 2009a). In this study we confirm that some conjunction targets have relatively little effect on tracking accuracy, but show that other conjunction targets can significantly aid tracking. For example, tracking accuracy is relatively high when the targets are small red squares and half the distractors are large red squares while the remaining distractors are small green squares. This seems to occur because the targets have a set of features (small and red) not shared by any one distractor. Attending to these features directs attention more to the targets than the distractors, thereby making the targets easier to track. Existing theories of attentive tracking cannot explain these results.

Measuring the Depth Induced by an Opposite-Luminance (but Not Anticorrelated) Stereogram

The same-sign hypothesis suggests that only those edges in the two retinal images whose luminance gradients have the same sign, known as same-sign edges, can be stereoscopically fused to generate a perception of depth. If true, one would expect that the magnitude of the depth induced by an opposite-luminance stereogram (eg one where the figure in one stereo half-image is black and the figure in the other is white) should be determined by the disparity of the same-sign edges. Despite the considerable work on the same-sign hypothesis this prediction has yet to be verified. Here we confirm this prediction for a particular opposite-luminance stereogram and discuss possible reasons why it is not true for opposite-luminance stereograms that are presented briefly or where each stereo half-image contains many elements.