Table of Contents

Overview of Research Interests

Research Setup

Spatial Processing

Background Information for Spatial Processing 

Multi-sensory Integration

  1. Estimation of distance traveled during self-motion
  2. Estimation of speed during self-motion
  3. Estimation of visual target distance and locomotor distance in large open space

Spatial Representation

  1. Orientation Specificity following spatial learning of a large-scale space
  2. Viewpoint dependency of multi-object room layout
  3. Categorical and coordinate spatial representations 
  4. Egocentric update vs allocentric map

Visual Motion Processing

Human Behavioural Studies

  1. Object motion vs self-motion
  2. Processing of time-to-collision
  3. Processing of heading


Neurophysiological and Modeling Studies

  1. Looming detectors  
  2. Centre-surround mechanisms
  3. Parallel processing of motion and colour

Social Interaction and Risk Taking Behaviors

1.      Effect of passenger attributes on risk taking behaviors during driving



  1. Sue Becker (McMaster) & Neil Burgess (Univ College London),

        Egocentric and allocentric processing in spatial navigation and

        Viewpoint dependency of multi-object room layout

  1. Margo Wilson (McMaster), Social interaction and risk taking behaviors
  2. Colin Ellard (Univ of Waterloo)

        Neural substrate of optic flow processing in gerbils using cfos labeling

        Visual and Locomotor estimation of distance

  1. Barrie Frost (Queen’s Univ), Neural mechanisms of looming detectors


Potential Applications

Overview of Research Interests

Our laboratory studies the mechanisms of visual motion processing, visuomotor control, and spatial memory, using behavioural, neurophysiological, and computational modelling techniques.

We are undertaking behavioural studies to explore fundamental perceptual and cognitive principles using Virtual Reality (VR) Technology. This research program explores how the brain extracts dynamic visual information generated by object motion (e.g., an incoming car) and motion of the visual environment experienced by an observer's motion (e.g., during walking or driving). We are interested in how the brain uses multiple sources of sensory information to control locomotion (e.g., visual factors in collision avoidance), and what kinds of strategies humans use in spatial route learning.  Our behavioral work has potential applications in a number of fields such as the design of better standardized tests for driver/pilot licences, the design of driving simulators, design of robots and automated navigation vehicles, entertainment industry (e.g. IMAX display).

In another line of our research (neurophysiological studies), we make electrical recording from single cells of animal's brain while presenting computer-generated visual stimuli to the animal. We are studying neural mechanisms of processing of object motion in 3-dimensional space. This research program has produced many discoveries including specialized structures in the brain that compute "time to collision" with looming objects and structures that compute movement of an object relative to its background. Computational models are also being developed to account for the physiological and behavioral results.

We are also exploring a new FM telemetry technique to record neuronal activity from awake and behaving animals. Single unit activity will be telemetered via a miniature head mounted FM transmitter. We will make neuroethological investigations of a number of important perceptual phenomenon which are not possible on an anaesthetized preparation.


Research Setup

Virtual Reality Setup

Human Setup

Sun Lab Virtual Tour Video

Computer systems (SGI Onyx2, O2 & IRIX 4D/310GTX)

Helmet Mounted Display (HMD) [full image], Eye Piece

Movement Sensors

Walking paradigm

  • head movement sensor: flock of bird (with 6 degree of freedom), see transmitter and sensor.

Cycling paradigm (see picture 1 [full image], picture 2 [full image], picture 3 [full image])

Driving simulator


Animal Setup (in development)


Human Psychophysics Setup

Single Cell Recording

new lab space


Background Information for Spatial Navigation

Research in spatial ability has experienced increasing interest over the past few decades, perhaps as a consequence of the extraordinary progress made in studying the behavioural and neural mechanisms of animal navigation; most notably the discovery of place cells in the rat hippocampus. Researchers (e.g. O’Keefe) have demonstrated that once a rat familiarizes itself within a particular environment, hippocampal neurons establish a place field, such that each neuron fires only when the rat remains in a particular space in that environment.
Although an extremely successful paradigm in its own right, it has proven to be a challenge to implement such a paradigm in humans. However, more recently, the study of spatial navigation in humans has seen great success with the adoption of virtual reality (VR) technologies, and consequently this type of technology is the one we are currently working with in our laboratory.
VR provides participants with an immersive environment within which they can navigate, manipulate and interact with in real-time. Realistic VR display (through head mounted displays) combined with high-speed, ultra-high resolution graphics engines, make possible a radically different level of investigation. Not only are participants fully immersed in their environment, unlike traditional pen and paper tasks (map viewing) or computer game-like tasks using a desktop interfaces (monitor + mouse), but they can actually physically move (by walking or riding a stationary bike), to obtain vestibular and proprioceptive feedback. Virtual reality is the best tool currently available to provide psychologists experimental control over three-dimensional, dynamic, ECOLOGICALLY VALID, stimulus presentations.


Multisensory Integration in the Estimation of Distance Travelled

One of the fundamental requirements for successful navigation through an environment is the continuous monitoring of distance travelled. To do so, humans normally use one or a combination of visual, proprioceptive/efferent, vestibular, and temporal cues. In the real world, information from one sensory modality is normally congruent with information from other modalities, hence, studying the nature of sensory interactions is often difficult.

In order to decouple the natural covariation between different sensory cues, we use virtual reality technology to vary the relation between the information generated from visual sources and the information generated from proprioceptive sources. When we manipulate the stimuli, such that the visual information is coupled in various ways to the proprioceptive information, humans predominantly use visual information to estimate the ratio of two traversed path lengths. Although proprioceptive information is not used directly, the mere availability of proprioceptive information increased the accuracy of relative path length estimation based on visual cues, even though the proprioceptive information was inconsistent with the visual information. These results convincingly demonstrate that active movement (locomotion) facilitates visual perception of path length travelled.


Sun, H.-J., Campos, J. L., & Chan, G. S. W. (in press). Multisensory integration in the estimation of relative path length, Experimental Brain Research.





Multisensory Integration in the Estimation of Speed

Information that is particularly important for monitoring self-motion is movement speed. While much has been discovered about the contributions of vision in speed perception, less is understood about the relative contributions of visual and nonvisual information when both are available. Although vision and proprioception are suspected to play a central role in assessing speed information, it is not clear which modality is more important for monitoring speed of self-motion. While visual information is often considered to be dominant as compared to other sensory information in most spatial tasks, studies examining human self-motion has called this assumption into question.

This series of studies assess the relative contributions of visual and proprioceptive information during self-motion in a virtual environment using a speed discrimination task. Subjects wear a head-mounted display (HMD) and ride a stationary bicycle along a straight path in an empty, seemingly infinite hallway with random surface texture. For each trial, subjects are required to pedal the bicycle along two paths at two different speeds (a standard speed and a comparison speed) and subsequently report whether the second speed travelled is faster than the first. The standard speed remains the same while the comparison speed is varied between trials according to the method of constant stimuli. When visual and proprioceptive cues are provided separately or in combination, the speed discrimination thresholds are comparable, suggesting that either cue alone is sufficient.

When the relation between visual and proprioceptive information is made inconsistent by varying optic flow gain, the resulting psychometric functions shift along the horizontal axis. The degree of separation between these functions indicates that both optic flow and proprioceptive cues contribute to speed estimation, with proprioceptive cues being dominant. These results suggest an important role for proprioceptive information in speed estimation during self-motion.


Sun, H.-J., Lee, A, Campos, J. L., Chan, G. S. W. & Zhang, D.-H. (in press). Multisensory integration in speed estimation during self-motion in a virtual environment, CyberPsychology and Behaviour.






Examining the Contribution of Visual and Nonvisual Cues to Distance Estimation by Manipulating Cue Availability

Developing a mental representation of one’s location in space requires both the visual assessment of static egocentric distance between oneself and environmental landmarks, and the continuous monitoring of dynamic distance information when traversing from one location to another.  Both visual and nonvisual sources of information can potentially be used for distance processing. 

Static visual cues may include familiar retinal image size, texture gradient, accommodation, convergence, and binocular disparity etc. Whereas, the spatial-temporal relation between the observer and environmental landmarks is provided by dynamic retinal information generated by the observer’s self-motion (optic flow). Egocentric distance information is also available via nonvisual cues that are internally generated as a result of one’s body movements in space.  This source of information, often referred to as “idiothetic information”, is provided by muscles and joints ("inflow" or proprioceptive input), motor efferent signals ("outflow"), and vestibular information generated as a result of changes in linear or rotational movement velocities.

By systematically varying cue availability we examine the contributions of static visual information, idiothetic information, and optic flow information in a real world distance estimation task.  This experiment is conducted in a large-scale, open, outdoor environment.  Subjects are presented with information about a particular distance and are then required to turn 180 degrees and produce a distance estimate.  Distance encoding and responding occur via: (1) visually perceived static target distance and 2) traversed distance through either: 2a) blindfolded locomotion or 2b) sighted locomotion with the presence of optic flow. 

The results demonstrate that humans can perform with similar accuracy with or without optic flow information in all conditions.  In conditions in which the stimulus and the response are delivered in the same mode, constant error is minimal when optic flow is absent, whereas when optic flow is present, overestimation is observed.  In conditions in which the stimulus and response modes differ, a consistent error pattern is observed. By systematically comparing complementary conditions, the results show that the availability of optic flow leads to an “under-perception” of movement relative to conditions in which optic flow was absent. 


Sun, H.-J., Campos, J. L., Chan, G. S. W. Young, M., and Ellard, C.  The contributions of static visual cues, nonvisual cues, and optic flow in distance estimation.  Submitted to Perception.








Spatial Representation Revealed Through Different Modes of Learning

Humans are able to learn and remember information about environmental spatial layouts through direct means (e.g., by navigating through the environment) or indirect means (e.g., by viewing a map or by encoding verbal descriptions). Theoretical and empirical work indicates that there may be multiple ways to learn spatial information, each of which results in different spatial representations. To understand the nature of these representations, it is important to identify the functional distinctions between different ways humans represent spatial information. One such distinction involves the degree to which ones' spatial representation is orientation-specific, as identified by whether or not the spatial memory is dependent on the original orientation in which the spatial layout was learned.

Past studies have demonstrated that during navigation, individuals often develop orientation-free representations of the areas within which they travel.  In contrast, learning from a map typically leads to an orientation-specific representation, resulting in better performance should subjects be positioned in the original orientation from which they encoded the environment. 

This series of studies first examined the spatial representations of human participants after learning the spatial layout of a single floor of a complex building: via map learning, via navigating within a real environment, or via navigating through a virtual simulation of that environment. Navigational learning was then compared across situations in which participants: 1) assumed multiple vs. a single body orientation, 2) experienced active vs. passive learning, and 3) received high vs. low levels of proprioceptive information.

Following learning, participants were required to produce directional judgments to target landmarks. Results show that humans typically develop orientation-specific spatial representations only following map learning and passive learning as indicated by better performance when tested from the initial learning orientation. These results suggest that neither the number of vantage points nor the level of proprioceptive information experienced is the determining factor, rather it is the active aspect of direct navigation that leads to the development of orientation-free representations.


Sun, H.-J., Chan, G. S. W., & Campos, J. L.. (in press) Active navigation and orientation-free spatial representations, Memory and Cognition.



View point dependency

Humans are capable of recognizing learned objects and scenes from viewpoints that differ from the originally experienced viewpoint. However, response time and accuracy are dependent on the angular difference between the novel view and the original view. This study explored viewpoint dependency by presenting subjects with a five-object configuration within a circular virtual room from a first-person perspective. For each trial, subjects responded by comparing a standard room (SR) to a comparison room (CR) and making a same/different judgement. For half of the trials, objects in the CRs were in the same configuration as objects in the SRs, but were presented from different viewpoints (ranging from 9 to 180). For the remaining trials, objects in the CRs were in a different configuration than those in the SRs and were again viewed from different viewpoints. Results demonstrated that reaction time and error rate increased as angular difference increased from 9 to 90, and decreased as angular difference increased from 90 to 180. Further, the results confirmed a previously well-documented male-advantage in single-object “mental rotation” tasks. This paradigm maintains the potential to explore the effects of dynamic visual and nonvisual updating via locomotion on viewpoint dependency.  We next examine the effects of dynamic visual and nonvisual updating via locomotion-induced changes in viewpoint and compare this to conditions in which viewpoint changes are not initiated by the observer themselves (similar to classical mental rotation task). 




Object Identification and Location Experiment

      A variety of information is required in order to navigate routes or maps successfully: the number of paths and their respective lengths, number of turns, degree of angles, as well as the position and identity of objects or landmarks that may be present along the route.  When examining studies requiring the performance of various spatial tasks, sex differences are often reported. However, within this broad category of “spatial ability” there are categories of spatial skills that do not reliably and consistently demonstrate sex biases (see Linn and Peterson, 1985 for a review). In the past, spatial memory has been looked at as consisting of two elements; location information and object identity information (Postma, 1998). The results of such studies seem to go against the assumed male superiority for spatial tasks that are often reported, suggesting that perhaps sex differences vary directly as a function of the requirements of the spatial task itself (males performing better than females at some task and vice versa for others). Many of these experiments have examined subjects performances by having them report object location and/or object identity by means of a two-dimensional map. However, in real world scenarios humans are rarely presented with a birds-eye view map (or allocentric map)of an area through which they had previously traversed. Typically we navigate egocentrically and encounter routes and the objects within them in a particular order and over a particular duration.
      By using virtual reality technology we are now able to further examine these two categories of spatial navigation (object identity and object location) by requiring subjects to actively navigate through an immersive, three-dimensional, virtual environment. By having subjects respond by actually travelling through a maze, we are able to compare the performance in a three-dimensional response task to a two-dimensional response task. It is expected that there will be differential sex differences for the different task requirements (i.e. naming objects versus naming locations versus naming both).

  • Some pictures of our testing environment (screen capture): 1, 2, 3, 4
  • Reference: Postma, A., Izendoorn. R. & De Hann, E. (1998). Sex Differences in Object Location Memory. Brain and Cognition, 36, 334-345. [pdf full text available]



Egocentric vs Allocentric Processing Experiment

It has been proposed that humans can form and maintain “cognitive maps” of their environment and as they navigate, they continually update a representation of their own allocentric position. An alternative theory suggests that humans navigate using egocentric representations of space (Wang and Spelke, 2000). During a recent examination of this theory we have, through the use of virtual reality, created a battery of testing environments, with different layouts, in a variety of different sizes, including a similar version of the radial arm mazes typically used in the study of rat hippocampal place cells. Past research has suggested that humans may encode or perceive moveable objects (i.e. a chair or book) as being different than stable objects (i.e. a doorway or wall). In virtual reality we have the option of moving an “immovable” object and examining the effects this might have on an individual’s spatial memory. We have hypothesized that subjects will tend to have an allocentric representation of stable landmarks, which could potentially be useful for navigation, while subjects tend to process moveable objects in a more egocentric manner.

         Some pictures of the testing environment:

  • Reference: Wang, R. F. & Spelke, E. S., (2000) Updating Egocentric Representations in Human Navigation. Cognition, 77, 215 - 250. [pdf full text available]



Object vs Self-Motion



Processing Time-to-Collision

  When a humann observer moves through the environment, in addition to the “traditional” distance cues (stereopsis, etc.), the continuous transformation of the optic array of the environment (optic flow) provides information about the spatial and temporal relationships between the observer and theirhis surroundings.  Such visual input is critical for the observer to control theirhis movement.  There has been great interest in behavioural studies on how humans use visual information to interact with their environment (especially in scenarios involving the potential collision between the observer and objects in the environment).  Lee (1980) argued that optical variable ttau provides the reliable information processing ofaboutthe time-to-collision, provided by J, which can then be used for visual motor control, such as modulating an observer’s speed of locomotion to arrive at an intended target.  Moreover, neither, information about the object’s distance, nor the observer’s movement velocity is required. 

Indeed, research on the control of some naturalistic visual motor behaviours has provided evidence that is consistent with the J strategy.  TThe use of the tFollowingSince Lee’s (1976) proposed  tau strategy for computing providing the observer with "time-to-collision" information, the use of such athis strategy in visual motor control, however, has received both support and criticism.  One criticism is based on the fact that such previous experiments fail to the lack of eexperimentally manipulateion of potentially critical variables.  With the eException of a few attempts, tTThe tau information has not been manipulated independently offrom other cues, such as distance information (perhaps due to the difficulty in manipulating environmental information dynamically in a natural settings).  , with the exception ofexcept a few attempts (Savelsbergh, Whiting and Bootsma, 1991; Sun, Carey and Goodale, 1992, Ellard, 2001).

IIn order to both, simulate the visual informationenvironment of a real world task requiring target-directed movement and sselectively manipulate the visual environment dynamically, in real time during movement, we have used a special virtual reality testing paradigm.  We selectively manipulated the time-to-collision information during subjects’ approach to a visual target without affecting other static distance information, which is often impossible in a real world situation.  This enables us to perform controlled experiments to test the role of vision in human motor behaviour rather than relying solely on the observation of natural behaviours, which is a typical approach in this kind of research. 


Using Virtual Reality to Explore Risk Taking Behavior in Response to Social Interactions

Driving is one of the most common forms of sensation-seeking that young men participate in within modern societies.  During driving, young males have been shown to be more likely to tailgate, speed, make unsafe lane changes, fail to yield, and disobey traffic signals, when compared to females and older males.  When examining potential risk factors involved in fatal automobile crashes, it was found that younger, male drivers, with a high number of passengers (i.e. 3 or more), were shown to account for the highest death rates. 

            In order to test this phenomenon empirically, we are currently designing a highly controlled driving task in which various aspects of both the driving context (e.g. sex, age and attractiveness of passengers) and the task itself (e.g. stopping at lights, yielding to pedestrians), can be manipulated systematically. This system allows us to explicitly measure every aspect of subjects’ responding, from driving speed to braking performance.  By manipulating various components independently of each other, we may be able to gain a better understanding of the causal relations that exist between particular factors and level of risk-taking. 

            We have developed a paradigm by which to explore how passenger attributes (i.e., sex, age, attractiveness, etc.) impact risk-taking behaviours during a simulated driving task.  The task will involve navigating a virtual car through virtual city streets, responding as necessary to traffic signals, other vehicle traffic, and pedestrians.  Some conditions will include passengers differing in age, sex, and level of attractiveness, and other conditions will involve solitary driving.  The VR interface consists of a head-mounted display equipped with a head-tracking device, coupled with an input device comprised of a steering wheel and a gas pedal.  Risk-taking behavior will be assessed by measuring speed, driving distance behind other vehicles (tailgating), (dis)obeying traffic signals, merging behaviours, driving in the appropriate lane, and braking behaviours. 

         Based on previous literature, it is predicted that when driving alone, overall younger males will engage in the highest level of risk-taking behaviour, with no significant difference being observed between older males and females.  It is also predicted that male’s risk-taking behaviour will increase to some degree with the presence of either a same-sex peer or opposite-sex peer, but will be the highest in the company of an attractive female.


Pictures (the process of creating 3D computer model from TWO 2d pictures):









         movie in RealPlayer format

         movie in mpg format


3D Motion

Using standard single unit recording techniques combined with computer-generated, complex visual motion stimuli, we have found a group of neurons in the pigeon nucleus rotundus (nRt) (equivalent to the mammalian pulvinar) of pigeons that selectively responds to a looming objects approaching on a collision course towards the animal, (but does not respond to a to a simulated self-motionapproach towards a stationary objects).  We have identified three types of looming-sensitive neurons, each computing a different optical variable generated from the image expansion of the approaching objects.  One group of neurons signals relative rate of expansion (taut)J, a secondproaching objects (Sun and Frost, 1998).  One type of neurons signals relative rate of expansion, tau.   group signals absolute rate of expansion (r) D , and a third group signals yet another optical variable (etah) 0.  The rroeD parameter is required for the computation of both ttauJ and heta0, whose respective ecological functions probablyseem to provide precise "time-to-collision" information, and "early warning" for approaching objects with a large visual angle substense (see also a commentary on our work written by Laurent and Gabbiani, 1998). 

            WIn addition to thise neurophysiological finding, we have also developed quantitative models to explain the physiological response properties of theose looming-sensitive neuronsSun and Frost, 2002.  These models take into account the physiological response properties and anatomical connections of the optic tectum, which sends a major input to nRt.  These models explain a variety of many response propertiescharacteristics, including why these looming sensitive neurons would only respond to object motion in depth but do not respond to self-motion.

        Sun, H.-J., & Frost, B. J. Looming detectors in nucleus of rotundus of the pigeons: Neuronal responses and models.  Submitted to Journal of Neuroscience.

        Frost, B. J. & Sun, H.-J. (2003) The biological basis of time to collision computation. In H. Hecht & G.J.P. Savelsbergh (Eds.), Time-to-contact (pp. 13-37), Advances in Psychology Series, Amsterdam: Elsevier - North-Holland.


Center Surround Mechanisms

In the real world, motion of an object rarely occurs in isolation, and quite often something else in the visual scene moves as well.  We have systematically investigated the effects of contextual cues on the response of tectal neurons in pigeonsSun, Zhao, Southall & Xu, 2002.  We found Our research showed that some neurons process relative motion information (in terms of both direction and velocity) between acrossthe regions that fall both within and outside the receptive field, rather than encoding only the absolute motion of objectsinformation that fallings within the receptive field.  We also discovered new types of neurons that exhibit unique ways to integrate visual motion information from within and outside the beyond classical receptive fields.  These results challenges the traditional notion of the receptive field, which has typically been was considered to be limited in spatial extent.  .  Further, these results, and should may also help us to explain how the brain distinguishes object motion from self-induced motion.  Additionally,ditionally these findings further It should also add to our understanding of  and segregates (differentiates?) ffigure/ from ground segregation. 


  • Sun, H.-J., Zhao, J., Southall, T. L, & Xu, B. (2002). Contextual influences on the directional responses of tectal cells in pigeons. Visual Neuroscience, 19, 133-144.


Parallel Processing of Motion and Colour

  • Sun, H.-J., & Frost, B. J. (1997). Motion processing in pigeon tectum: equiluminant chromatic mechanisms. Experimental Brain Research, 116: 434-444.


Potential Applications

Our research has considerable potential for application in the following fields.

The algorithm and model generated from our studies that work so effectively to explain the neural computation of impending collision can be implemented in robotic design and in prototyping new vehicular systems with automatic navigation capacities. The visual information generated from such device about the direction of the movement and time to collision with external objects will complement the information calculated through stereoscopic video cameras, which are typically used in modern robotic design. Fewer computational resources are required than for the calculation of absolute distance information from stereoscopic cameras.

Unlike autonomous robotics, remotely controlled systems (telerobotics) still depend on human intelligence and perception. It is important to ensure that the human-machine interface is adequate for the task. As behavioural scientists, we can determine how such technologies should be developed to best match the perceptual and motor abilities of human users.
Our research on virtual reality will touch some of the important issues related to this field. For example, critical visual information should be presented to the human operator in a rather natural display to facilitate human-machine interactions. We can evaluate the effectiveness of different kinds of display systems (e.g., monoscopic vs. stereoscopic viewing). We will also evaluate the effect of temporal delay in communication between a human operator and robotic end-effectors in the remote site. With the time delay, operators will not be able to use real time visual information; instead, visual information that is "remembered" or "predicted" will be used to control their motor action.

Flight simulators, which produce a profound illusion of self-motion, are often used for the training of pilots. Our research will provide important insights as to what components of the visual display are critical. For example, most flight simulators today simulate the approaching movement through presentation of image expansion of the larger objects (such as a terrain) but do not simulate the size increase of the individual texture elements inside. Whether this mismatch of the image expansion will create a misjudgement of time to collision will be one of our research projects.



Psychophysical research has shown that people can be blind for motion-in-depth in certain parts of their visual field, while their static stereo vision remains intact. This demonstrates the existence of independent visual systems for motion-in-depth. While we know a lot about the visual processing of static distance, we know very little about the visual processing of motion in 3D, which is critical for action in our daily life, such as avoiding obstacles, walking, driving, and navigating through the environment. These specialised functions of the visual system are not normally evaluated by the conventional examinations of visual function. Research in this field will certainly help us develop a set of standardised tests, to screen visual motion deficits and ultimately reduce accidents among drivers or pilots who lack acuity for visual motion in depth or are impaired in certain parts of their visual field.

What we learn through our research can also be used to train human observers to use visual information more effectively. Children, for example, could be trained to be better observers in high traffic situations (in fact, this has been done in England where children are trained to use time-to-collision as a cue when crossing the road). Similarly, pilots and athletes could benefit from training in time-to-collision assessment, and motion blind or impaired individuals could be trained to overcome their deficits by actively using the part of the visual field that is intact.

Research has also identified the involvement of the visual motion system in various perceptual and cognitive deficits, such as dyslexia. A deeper understanding of visual motion processing will increase our knowledge and eventually facilitate diagnosis and the development of effective rehabilitation techniques.

Research Funding

  • NSERC Operating Grant, "Neural Computation of Visual Motion in 3-Dimensional Space"
  • NSERC Equipment Grant, "Neural Computation of Visual Motion in 3-Dimensional Space (equipment)"
  • Canadian Foundation for Innovation, New Opportunities Award, "A Physiology and Behaviour Lab for the Study of Visual Processing and Visual Motor Control"
  • Ontario Innovation Trust, "A Physiology and Behaviour Lab for the Study of Visual Processing and Visual Motor Control"