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Six separate projects have explored how velocity and acceleration are encoded in the human visual system. (1) Welch demonstrated speed discrimination for coherent plaid patterns formed of two superimposed gratings was limited by the speed of the gratings, not the apparent speed of the plaid itself. (2) Bowne et al. and more recently Grzywacz, applied 'motion-energy' models to the psychophysics of speed discrimination. (3) McKee and Welch compared the relative precision of velocity and size constancy, finding little evidence for velocity constancy in human motion processing. (4) Watamaniuk demonstrated that the visual system integrates diverse speeds (2-8 deg/sec) in a random dot display to obtain a precise estimate of the mean speed. (5) McKee and Watamaniuk found that a single point (the signal) moving in apparent motion (the noise), even though the spatial and temporal characteristics of the signal and noise points were identical on a frame-by-frame basis. (6) Bravo and Watamaniuk showed the two sets of randomly distributed dots moving in the same direction, but at two very different speeds, formed two transparent planes; discrimination of small changes in the speed of one set of dots was unaffected by the presence of the other dots.

The main objective of this project was the analysis of the detection of trajectory signals in random motion noise. Results from experiments demonstrated that detection was limited by the probability of mismatch, not noise density per se; detection was based on a motion signal, not a form or position signal; detection was limited by higher-order aspects of motion processing, not the ratio of signal to noise in the primary motion detectors. The Yuille-Grzywacz "Motion Coherence" model was modified to provide a computational model for these findings. Computer simulations showed that this model was adequate to reproduce our results. In addition, three other projects were supported by this grant: motion transparency from speed signals alone; speed discrimination for targets moving in depth; trajectory motion detection in three-dimensional noise. Nine papers from this project have been accepted in referred journals; one additional paper has been submitted. Four chapters were also supported by this grant. (AN)

The aim of this study is to investigate the effects of a single dose of alcohol (0.4 g/kg) on visual processing. Participants attend two sessions (alcohol, placebo) and during each session complete two tasks - a visual search task and a visual illusion task. We hypothesise that alcohol may interfere with top-down regulation of object recognition, and therefore may attenuate top-down disruption during visual search of composite shapes and on susceptibility to perceiving a visual illusion.

In this longitudinal study, we will assess whether individual differences in visual object processing predict children’s reading performance. Contributors are listed in alphabetical order.

This research analyzed the human ability to detect targets moving on predictable paths in the midst of temporally-changing noise. Results from experiments showed that observers easily detected a target (a single bright dot) moving in a consistent direction in the midst of considerable noise, even when this noise consisted of identical features (bright dots) in random motion. Presumably, this ability to detect trajectory motion enables pilots or other military personnel to find aircraft or missiles in the midst of jamming noise. Observers improve their ability to detect motion trajectories with practice, so presumably they learn better strategies with experience. Thus, this task may be useful in training personnel who are required to detect or track targets in noise. Experimental analysis showed that observers use attention to increase the gain of the response to consistent motion, and to reduce the response to the surrounding noise. Fourteen papers were accepted for publication in refereed journals; another paper is in preparation.

The present study examines to what extent preference is moderated by visual or conceptual differences between objects. We use a diverse image set of chairs and tables to examine the effects of Category (chair vs. table) and Contour (angular vs. curved) on preference and gaze behaviour.

The visual system can use local speed information to determine whether one surface or two transparent surfaces are visible. The local speed signals are very noisy, so a large difference in speed is necessary to produce surface segregation. Once the segregation has occurred, the visual system then integrates the local speed signals associated with each surface to improve the precision of the speed information. To study this phenomenon, speed discrimination was measured for a display composed of random dots all moving in one direction, but at two different speeds. When the speeds were sufficiently different to create the perception of two transparent planes, speed discrimination was as precise for either of the two speeds as when each was viewed alone. The local motion vectors specifying the two speeds had to be present simultaneously to produce segregation (and good speed discrimination). If all dots alternated rapidly between the two speeds in synchrony, no segregation was observed. On the other hand, asynchronous alternation, in which different subsets of dots changed speed in every frame, produced excellent segregation.

Several models of human motion discrimination have been proposed over the last decade. All are loosely related to the correlator approach originally used by Hassenstein and Reichardt to describe motion discrimination in insect eyes. These correlator models use simple spatial and temporal filtering followed by a non-linear multiplicative operation to account for human direction discrimination of sinusoidal stimuli near contrast threshold. Nevertheless, these models are extremely limited in scope. Research in this laboratory has shown that the correlator models cannot explain human speed discrimination even for sinusoidal targets. Apparently, a higher order network formed by combining local 'motion energy units' is required to encode speed. This laboratory has also studied how different features (object components) are combined so that complicated objects move at a uniform velocity. The combination rules are fairly arbitrary, but are limited by physical constraints. Basically, features with similar contrasts, wavelengths, spatial frequencies and temporal frequencies are combined to form a coherent whole moving at a single perceived velocity. Dissimilar features move independently. (aw)

The human ability to discriminate small differences in velocity has been used to explore human motion processing. Velocity discrimination is independent of target contrast above a contrast of 2 -5%. A model based on the ratio of signals in two temporal mechanisms (sustained and transient) can explain this contrast independence at low contrast levels, but fails at high contrast levels. Human observers have difficulty detecting acceleration which may be due to physiological summation (integration) of the velocity signals from many motion sensors. Human observers cannot use disparity information to translate the angular velocity signal (deg/sec) into a precise estimate of objective velocity (cm/sec), a result that suggests that there is no mechanism for velocity constancy. Visual acuity, Vision.

Human observers can easily detect a signal dot moving, in apparent motion, on a trajectory embedded in a background of random-direction motion noise. A high detection rate is possible even though the spatial and temporal characteristics(step size and frame rate) of the signal are identical to the noise, making the signal indistinguishable from the noise on the basis of a single pair of frames. The success rate for detecting the signal dot was as high as 90% when the probability of mismatch from frame-to-frame, based on nearest neighbor matching was 0.3 control experiments showed that trajectory detection is not based on detecting a 'string' of collinear dots, i.e., a stationary position cue. Nor is a trajectory detected because produces stronger signals in independent 'local' motion detectors. For one thing, trajectory detection improves with increases in duration, up to 250 - 400 msec, a duration longer than the integration typically associated with a single motion detector. Moreover, the signal dot need not travel in a straight line to be detectable. The signal dot was as reliably detected when it changed its direction a small amount (30 deg) each frame. Consistent with this, circular paths of sufficiently low curvature were as detectable as straight trajectories.

This research analyzed human detection of object motion in random motion noise. Results from experiments demonstrated that: (1) a flexible neural network enhances detection of a feature moving in a constant direction or changing direction slowly; (2) the network uses a highly non-linear facilitation, rather than the linear sum of contrast or luminance signals; (3) a stimulus pattern that moves along the motion path is more detectable than one oriented orthogonal to it; (4) stereopsis does not provide much benefit for detecting motion signals in noise; (5) motion along the z-axis (motion in depth) can be masked by static disparity noise; and (6) the motion system can simultaneously encode both the local directions of small features and the global direction of the flow field. A Bayesian model of object motion and surface segmentation is being developed to explain these observations. Future work will explore whether this model of human motion processing can be implemented computationally in VLSI hardware for detecting moving projectiles in the midst of noise. Twelve papers were accepted for publication in referred journals; four chapters were also supported by this grant.

This article is from Scientific Reports , volume 4 . Abstract Brightness illusions demonstrate that an object's perceived brightness depends on its visual context, leading to theoretical explanations ranging from simple lateral inhibition to those based on the influence of knowledge of and experience with the world. We measure the relative brightness of mid-luminance test disks embedded in gray-scale images, and show that rankings of test disk brightness are independent of viewing distance, implying that the rankings depend on the physical object size, not the size of disks subtended on the retina. A single filter that removes low spatial frequency content, adjusted to the diameters of the test disks, can account for the relative brightness of the disks. We note that the removal of low spatial frequency content is a principle common to many different approaches to brightness/lightness phenomena; furthermore, object-size representations--as opposed to retinal-size representations--inherently remove low spatial frequency content, therefore, any process that creates object representations should also produce brightness illusions.

This article is from Frontiers in Integrative Neuroscience , volume 7 . Abstract Functional magnetic resonance imaging (MRI) showed that the superior temporal and occipital cortex are involved in multisensory integration. Probabilistic fiber tracking based on diffusion-weighted MRI suggests that multisensory processing is supported by white matter connections between auditory cortex and the temporal and occipital lobe. Here, we present a combined functional MRI and probabilistic fiber tracking study that reveals multisensory processing mechanisms that remained undetected by either technique alone. Ten healthy participants passively observed visually presented lip or body movements, heard speech or body action sounds, or were exposed to a combination of both. Bimodal stimulation engaged a temporal-occipital brain network including the multisensory superior temporal sulcus (msSTS), the lateral superior temporal gyrus (lSTG), and the extrastriate body area (EBA). A region-of-interest (ROI) analysis showed multisensory interactions (e.g., subadditive responses to bimodal compared to unimodal stimuli) in the msSTS, the lSTG, and the EBA region. Moreover, sounds elicited responses in the medial occipital cortex. Probabilistic tracking revealed white matter tracts between the auditory cortex and the medial occipital cortex, the inferior occipital cortex (IOC), and the superior temporal sulcus (STS). However, STS terminations of auditory cortex tracts showed limited overlap with the msSTS region. Instead, msSTS was connected to primary sensory regions via intermediate nodes in the temporal and occipital cortex. Similarly, the lSTG and EBA regions showed limited direct white matter connections but instead were connected via intermediate nodes. Our results suggest that multisensory processing in the STS is mediated by separate brain areas that form a distinct network in the lateral temporal and inferior occipital cortex.

Talk by Rudiger von der Heydt from Johns Hopkins University.  Given to the Redwood Center for Theoretical Neuroscience at UC Berkeley.   Abstract   Image understanding is often conceived as a hierarchical process with many levels where complexity and invariance of object selectivity gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers in the inferotemporal cortex, because border-ownership signals appear well before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. This talk will review the hypothesis and neurohysiological evidence that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call “proto-objects.” This process is pre-attentive and does not rely on object recognition. The proposed mechanism consists of grouping cells that sum distributed feature signals with fixed templates and, by feedback, enhance the same feature signals. With this circuit, the system can enhance many feature signals by top-down activating a single grouping cell. The shapes and sizes of the grouping templates and the rise and persistence of grouping cell activity give rise to the Gestalt laws of object perception. The proto-object structures serve to individuate objects and provide permanence; they enable the system to track moving objects and cope with the displacements caused by eye movements, to select one object out of many and to scrutinize the selected object.

xii, 317 p. : 24 cm