Vision Science seminars

A high-resolution central fovea is a prominent design feature of human vision. But how important is the fovea for information processing and gaze guidance in everyday visual-cognitive tasks? Following on from classic findings for sentence reading, I will present key results from a series of eye-tracking experiments in which observers had to search for a target object within static or dynamic images of real-world scenes. Gaze-contingent scotomas were used to selectively deny information processing in the fovea, parafovea, or periphery. Overall, the results suggest that foveal vision is less important and peripheral vision is more important for scene perception and search than previously thought. The importance of foveal vision was found to depend on the specific requirements of the task. Moreover, the data support a central-peripheral dichotomy in which peripheral vision selects and central vision recognizes.

Research in the brain and cognitive sciences attempts to uncover the neural mechanisms underlying intelligent behavior in domains such as vision. Due to the complexities of brain processing, studies necessarily had to start with a narrow scope of experimental investigation and computational modeling. I argue that it is time for our field to take the next step: build system models that capture a range of visual intelligence behaviors along with the underlying neural mechanisms. To make progress on system models, we propose integrative benchmarking – integrating experimental results from many laboratories into suites of benchmarks that guide and constrain those models at multiple stages and scales. We show-case this approach by developing Brain-Score benchmark suites for neural (spike rates) and behavioral experiments in the primate visual ventral stream. By systematically evaluating a wide variety of model candidates, we not only identify models beginning to match a range of brain data (~50% explained variance), but also discover that models’ brain scores are predicted by their object categorization performance (up to 70% ImageNet accuracy). Using the integrative benchmarks, we develop improved state-of-the-art system models that more closely match shallow recurrent neuroanatomy and early visual processing to predict primate temporal processing and become more robust, and require fewer supervised synaptic updates. Taken together, these integrative benchmarks and system models are first steps to modeling the complexities of brain processing in an entire domain of intelligence.

In most animal species including humans, commissural axons connect neurons on the left and right side of the nervous system. In humans, abnormal axon midline crossing during development causes a whole range of neurological disorders ranging from congenital mirror movements, horizontal gaze palsy, scoliosis or binocular vision deficits. The mechanisms which guide axons across the CNS midline were thought to be evolutionary conserved but our recent results suggesting that they differ across vertebrates. I will discuss the evolution of visual projection laterality during vertebrate evolution. In most vertebrates, camera-style eyes contain retinal ganglion cell (RGC) neurons projecting to visual centers on both sides of the brain. However, in fish, RGCs are thought to only innervate the contralateral side. Using 3D imaging and tissue clearing we found that bilateral visual projections exist in non-teleost fishes. We also found that the developmental program specifying visual system laterality differs between fishes and mammals. We are currently using various strategies to discover genes controlling the development of visual projections. I will also present ongoing work using 3D imaging techniques to study the development of the visual system in human embryo.

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Quantifying the timing (duration and frequency) of brief visual events is vital to human perception, multisensory integration and action planning. For example, this allows us to follow and interact with the precise timing of speech and sports. Here we investigate how visual event timing is represented and transformed across the brain’s hierarchy: from sensory processing areas, through multisensory integration areas, to frontal action planning areas. We hypothesized that the dynamics of neural responses to sensory events in sensory processing areas allows derivation of event timing representations. This would allow higher-level processes such as multisensory integration and action planning to use sensory timing information, without the need for specialized central pacemakers or processes. Using 7T fMRI and neural model-based analyses, we found responses that monotonically increase in amplitude with visual event duration and frequency, becoming increasingly clear from primary visual cortex to lateral occipital visual field maps. Beginning in area MT/V5, we found a gradual transition from monotonic to tuned responses, with response amplitudes peaking at different event timings in different recording sites. While monotonic response components were limited to the retinotopic location of the visual stimulus, timing-tuned response components were independent of the recording sites' preferred visual field positions. These tuned responses formed a network of topographically organized timing maps in superior parietal, postcentral and frontal areas. From anterior to posterior timing maps, multiple events were increasingly integrated, response selectivity narrowed, and responses focused increasingly on the middle of the presented timing range. These results suggest that responses to event timing are transformed from the human brain’s sensory areas to the association cortices, with the event’s temporal properties being increasingly abstracted from the response dynamics and locations of early sensory processing. The resulting abstracted representation of event timing is then propagated through areas implicated in multisensory integration and action planning.

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

An object’s colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and “illusions” have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for when measuring an object’s perceived colour. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band’s lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next we systematically test the model’s ability to qualitatively predict over 35 brightness and colour phenomena, with almost complete success. This implies that contrary to high-level processing explanations, much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a basis for modelling the vision of humans and other animals.

The brain combines signals across the eyes. This process is well-characterized for the perceptual anatomical pathway through V1 that primarily codes contrast, where interocular normalization ensures that responses are approximately equal for monocular and binocular stimulation. But we have much less understanding of how luminance is combined binocularly, both in the cortex and in subcortical structures that govern pupil diameter. Here I will describe the results of experiments using a novel combined EEG and pupillometry paradigm to simultaneously index binocular combination of luminance flicker in parallel pathways. The results show evidence of a more linear process than for spatial contrast, that may reflect different operational constraints in distinct anatomical pathways.

Neural correlates of visual working memory have been found in early visual, parietal, and prefrontal regions. These findings have spurred fruitful debate over how and where in the brain memories might be represented. Here, I will present data from multiple experiments to demonstrate how a focus on behavioral requirements can unveil a more comprehensive understanding of the visual working memory system. Specifically, items in working memory must be maintained in a highly robust manner, resilient to interference. At the same time, storage mechanisms must preserve a high degree of flexibility in case of changing behavioral goals. Several examples will be explored in which visual memory representations are shown to undergo transformations, and even shift their cortical locus alongside their coding format based on specifics of the task.

The rising and setting of the sun is accompanied by changes in both the irradiance and the spectral distribution of the sky. Since the discovery of intrinsically photosensitive retinal ganglion cells (ipRGCs) 20 years ago, considerable progress has been made in understanding melanopsin's contributions to encoding irradiance. Much less is known about the cone inputs to ipRGCs and how they could encode changes in the color of the sky. I will summarize our recent connectomic investigation into the cone-opponent inputs to primate ipRGCs and the implications of this work on our understanding of circadian photoentrainment and the evolution of color vision.

Beyond vision, light triggers a variety of non-image forming responses. Amongst these is the pupillary light reflex, commonly used by ophthalmologists to gauge the function of the optic nerve head. In my talk, I will share some of our latest work on optimizing the use of the pupillary light reflex to detect functional loss in ocular diseases in clinics.

Humans, as a social species, have an increased ability to detect and perceive visual elements involved in social exchanges, such as faces and eyes. The gaze, in particular, conveys information crucial for social interactions and social cognition. Researchers have hypothesized that in order to engage in dynamic face-to-face communication in real time, our brains must quickly and automatically process the direction of another person's gaze. There is evidence that direct gaze improves face encoding and attention capture and that direct gaze is perceived and processed more quickly than averted gaze. These results are summarized as the "direct gaze effect". However, in the recent literature, there is evidence to suggest that the mode of visual information processing modulates the direct gaze effect. In this presentation, I argue that top-down processing, and specifically the relevance of eye features to the task, promotes the early preferential processing of direct versus indirect gaze. On the basis of several recent evidences, I propose that low task relevance of eye features will prevent differences in eye direction processing between gaze directions because its encoding will be superficial. Differential processing of direct and indirect gaze will only occur when the eyes are relevant to the task. To assess the implication of task relevance on the temporality of cognitive processing, we will measure event-related potentials (ERPs) in response to facial stimuli. In this project, instead of typical ERP markers such as P1, N170 or P300, we will measure lateralized ERPs (lERPS) such as lateralized N170 and N2pc, which are markers of early face encoding and attentional deployment respectively. I hypothesize that the relevance of the eye feature task is crucial in the direct gaze effect and propose to revisit previous studies, which had questioned the existence of the direct gaze effect. This claim will be illustrate with different past studies and recent preliminary data of my lab. Overall, I propose a systematic evaluation of the role of top-down processing in early direct gaze perception in order to understand the impact of context on gaze perception and, at a larger scope, on social cognition.

Do all components of the living human eye have a measurable diurnal rhythm? In this talk I will discuss methodologies and results of studies on adolescents and young adults. I will also touch upon the associations between diurnal rhythms of the eye and behavioral activities.

Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, are now approaching – and sometimes even surpassing – human accuracy on a variety of visual recognition tasks. In this talk, however, I will show that these neural networks and their recent extensions exhibit a limited ability to solve seemingly simple visual reasoning problems involving incremental grouping, similarity, and spatial relation judgments. Our group has developed a recurrent network model of classical and extra-classical receptive field circuits that is constrained by the anatomy and physiology of the visual cortex. The model was shown to account for diverse visual illusions providing computational evidence for a novel canonical circuit that is shared across visual modalities. I will show that this computational neuroscience model can be turned into a modern end-to-end trainable deep recurrent network architecture that addresses some of the shortcomings exhibited by state-of-the-art feedforward networks for solving complex visual reasoning tasks. This suggests that neuroscience may contribute powerful new ideas and approaches to computer science and artificial intelligence.

Self-motion through a visual world creates a pattern of expanding visual motion called optic flow. Heading estimation from the optic flow is accurate in rigid environments. But it becomes challenging when other humans introduce an independent motion to the scene. The biological motion of human walkers consists of translation through space and associated limb articulation. The characteristic motion pattern is regular, though complex. A world full of humans moving around is nonrigid, causing heading errors. But limb articulation alone does not perturb the global structure of the flow field, matching the rigidity assumption. For heading perception from optic flow analysis, limb articulation alone should not impair heading estimates. But we observed heading biases when participants encountered a group of point-light walkers. Our research investigates the interactions between optic flow perception and biological motion perception. We further analyze the impact of environmental information.