Visual Neuroscience Research Articles

Correcting for physical distortions in visual stimuli improves reproducibility in zebrafish neuroscience.

Optical refraction causes light to bend at interfaces between optical media. This phenomenon can significantly distort visual stimuli presented to aquatic animals in water, yet refraction has often been ignored in the design and interpretation of visual neuroscience experiments. Here we provide a computational tool that transforms between projected and received stimuli in order to detect and control these distortions. The tool considers the most commonly encountered interface geometry, and we show that this and other common configurations produce stereotyped distortions. By correcting these distortions, we reduced discrepancies in the literature concerning stimuli that evoke escape behavior, and we expect this tool will help reconcile other confusing aspects of the literature. This tool also aids experimental design, and we illustrate the dangers that uncorrected stimuli pose to receptive field mapping experiments.

The visual psychology of European Upper Palaeolithic figurative art: using Bubbles to understand outline depictions

ABSTRACT How have our visual brains evolved, and exactly how did this constrain the specific way that animals were depicted in Upper Palaeolithic art? Here, we test predictions derived from visual neuroscience in this field. Using the example of open-air Upper Palaeolithic rock art of Portugal’s Côa Valley, we point out the frequently recurring outline strategies that past artists utilized to depict the prey animals upon which they were dependent for survival. Their depictional tendency can be mirrored onto the most visually salient anatomical aspects of these species, a finding that results from our use of a visual psychological experimental programme, called Bubbles. We find a remarkable correspondence between the aspects of the anatomy of horses and bison that modern participants found most helpful in successfully discriminating between the two, and those same aspects that are elaborated most in Upper Palaeolithic art. This leads us to conclude that the visual system of Homo sapiens drove the way that important prey species were depicted, and hence, the form of their art.

The development of vision between nature and nurture: clinical implications from visual neuroscience.

Vision is an adaptive function and should be considered a prerequisite for neurodevelopment because it permits the organization and the comprehension of the sensory data collected by the visual system during daily life. For this reason, the influence of visual functions on neuromotor, cognitive, and emotional development has been investigated by several studies that have highlighted how visual functions can drive the organization and maturation of human behavior. Recent studies on animals and human models have indicated that visual functions mature gradually during post-natal life, and its development is closely linked to environment and experience. The role of vision in early brain development and some of the neuroplasticity mechanisms that have been described in the presence of cerebral damage during childhood are analyzed in this review, according to a neurorehabilitation prospective.

Causal importance of low-level feature selectivity for generalization in image recognition

Although our brain and deep neural networks (DNNs) can perform high-level sensory-perception tasks, such as image or speech recognition, the inner mechanism of these hierarchical information-processing systems is poorly understood in both neuroscience and machine learning. Recently, Morcos et al. (2018) examined the effect of class-selective units in DNNs, i.e., units with high-level selectivity, on network generalization, concluding that hidden units that are selectively activated by specific input patterns may harm the network’s performance. In this study, we revisited their hypothesis, considering units with selectivity for lower-level features, and argue that selective units are not always harmful to the network performance. Specifically, by using DNNs trained for image classification, we analyzed the orientation selectivity of individual units, a low-level selectivity widely studied in visual neuroscience. We found that orientation-selective units exist in both lower and higher layers of these DNNs, as in our brain. In particular, units in lower layers became more orientation-selective as the generalization performance improved during the course of training. Consistently, networks that generalized better were more orientation-selective in the lower layers. We finally revealed that ablating these selective units in the lower layers substantially degraded the generalization performance of the networks, at least by disrupting the shift-invariance of the higher layers. These results suggest that orientation selectivity can play a causally important role in object recognition, and that, contrary to the triviality of units with high-level selectivity, lower-layer units with selectivity for low-level features may be indispensable for generalization, at least for the several network architectures.

The foundations of visual neuroscience in Australia

The passing of Jack Pettigrew (University of Queensland) and Bogdan Dreher (University of Sydney) within 2 weeks of each other in May 2019 provided the catalyst for documenting the roles that they and their colleagues from the Peter Bishop School played in establishing vision research as a major strength in Australian neuroscience in the second half of the 20th century.

Radiation-induced impairment of optic nerve axonal transport in tree shrews and rats monitored by longitudinal manganese-enhanced MRI

PurposeRadiation-induced optic neuropathy (RION) is a serious complication that occurs after radiation therapy of tumors in the vicinity of the optic nerve, yet its mechanism and imaging features are poorly understood. In this study, we employed manganese-enhanced MRI (MEMRI) to assess optic nerve axonal transport in tree shrews and rats after irradiation. Materials and methodsA comparison of normal visual projections in tree shrews and rats was conducted by intravitreal MnCl2 injection followed by MRI. Adult male tree shrews and rats received a total dose of 20 Gy delivered in two fractions (10 Gy per fraction) within 5 days. Longitudinal MEMRI was conducted 5, 10, 20 and 30 weeks after radiation. At the end of observation, motor proteins involved in axonal transport were detected by western blotting, and the axon cytoskeleton was assessed by immunofluorescence. ResultsThe eyeballs, lens sizes, vitreous volumes, optic nerves and superior colliculi of tree shrews were significantly larger than those of rats on MEMRI (P < 0.05). The Mn2+-enhancement of the optic nerve showed no significant changes at 5 and 10 weeks (P > 0.05) but decreased gradually from 20 to 30 weeks postirradiation (P < 0.05). The enhancement of the superior colliculus gradually decreased from 5 weeks to 30 weeks, and the decrease was most significant at 30 weeks (P < 0.05). The levels of the motor proteins cytoplasmic dynein-1, kinesin-1 and kinesin-2 in the experimental group were significantly decreased (P < 0.05). The immunofluorescence results showed that the α-tubulin, β-tubulin and SMI 31 levels in the experimental groups and control groups were not significantly different (P > 0.05). ConclusionTree shrews show great advantages in visual neuroscience research involving MEMRI. The main cause of the decline in axonal transport in RION is an insufficient level of motor protein rather than damage to the axonal cytoskeletal structure. Longitudinal MEMRI can be used to detect changes in axonal transport function and to observe the relatively intact axon structure from the early to late stages after radiation administration.

An Annotated Journey through Modern Visual Neuroscience

Recent advances in microscopy, genetics, physiology, and data processing have expanded the scope and accelerated the pace of discovery in visual neuroscience. However, the pace of discovery and the ever increasing number of published articles can present a serious issue for both trainees and senior scientists alike: with each passing year the fog of progress thickens, making it easy to lose sight of important earlier advances. As part of this special issue of the Journal of Neuroscience commemorating the 50th anniversary of SfN, here, we provide a variation on Stephen Kuffler's Oldies but Goodies classic reading list, with the hope that by looking back at highlights in the field of visual neuroscience we can better define remaining gaps in our knowledge and thus guide future work. We also hope that this article can serve as a resource that will aid those new to the field to find their bearings.

Education and visual neuroscience: A mini-review.

Neuroscience, especially visual neuroscience, is a burgeoning field that has greatly shaped the format and efficacy of education. Moreover, findings from visual neuroscience are an ongoing source of great progress in pedagogy. In this mini-review, I review existing evidence and areas of active research to describe the fundamental questions and general applications for visual neuroscience as it applies to education. First, I categorize the research questions and future directions for the role of visual neuroscience in education. Second, I juxtapose opposing views on the roles of neuroscience in education and reveal the "neuromyths" propagated under the guise of educational neuroscience. Third, I summarize the policies and practices applied in different countries and for different age ranges. Fourth, I address and discuss the merits of visual neuroscience in art education and of visual perception theories (e.g., those concerned with perceptual organization with respect to space and time) in reading education. I consider how vision-deprived students could benefit from current knowledge of brain plasticity and visual rehabilitation methods involving compensation from other sensory systems. I also consider the potential educational value of instructional methods based on statistical learning in the visual domain. Finally, I outline the accepted translational framework for applying findings from educational neuroscience to pedagogical theory.

Predicting the Partition of Behavioral Variability in Speed Perception with Naturalistic Stimuli.

A core goal of visual neuroscience is to predict human perceptual performance from natural signals. Performance in any natural task can be limited by at least three sources of uncertainty: stimulus variability, internal noise, and suboptimal computations. Determining the relative importance of these factors has been a focus of interest for decades but requires methods for predicting the fundamental limits imposed by stimulus variability on sensory-perceptual precision. Most successes have been limited to simple stimuli and simple tasks. But perception science ultimately aims to understand how vision works with natural stimuli. Successes in this domain have proven elusive. Here, we develop a model of humans based on an image-computable (images in, estimates out) Bayesian ideal observer. Given biological constraints, the ideal optimally uses the statistics relating local intensity patterns in moving images to speed, specifying the fundamental limits imposed by natural stimuli. Next, we propose a theoretical link between two key decision-theoretic quantities that suggests how to experimentally disentangle the impacts of internal noise and deterministic suboptimal computations. In several interlocking discrimination experiments with three male observers, we confirm this link and determine the quantitative impact of each candidate performance-limiting factor. Human performance is near-exclusively limited by natural stimulus variability and internal noise, and humans use near-optimal computations to estimate speed from naturalistic image movies. The findings indicate that the partition of behavioral variability can be predicted from a principled analysis of natural images and scenes. The approach should be extendable to studies of neural variability with natural signals.SIGNIFICANCE STATEMENT Accurate estimation of speed is critical for determining motion in the environment, but humans cannot perform this task without error. Different objects moving at the same speed cast different images on the eyes. This stimulus variability imposes fundamental external limits on the human ability to estimate speed. Predicting these limits has proven difficult. Here, by analyzing natural signals, we predict the quantitative impact of natural stimulus variability on human performance given biological constraints. With integrated experiments, we compare its impact to well-studied performance-limiting factors internal to the visual system. The results suggest that the deterministic computations humans perform are near optimal, and that behavioral responses to natural stimuli can be studied with the rigor and interpretability defining work with simpler stimuli.

Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches.

Unsolved questions in computational visual neuroscience research are whether and how neurons and their connecting cortical networks can adapt when normal vision is compromised by a neurodevelopmental disorder or damage to the visual system. This question on neuroplasticity is particularly relevant in the context of rehabilitation therapies that attempt to overcome limitations or damage, through either perceptual training or retinal and cortical implants. Studies on cortical neuroplasticity have generally made the assumption that neuronal population properties and the resulting visual field maps are stable in healthy observers. Consequently, differences in the estimates of these properties between patients and healthy observers have been taken as a straightforward indication for neuroplasticity. However, recent studies imply that the modeled neuronal properties and the cortical visual maps vary substantially within healthy participants, e.g., in response to specific stimuli or under the influence of cognitive factors such as attention. Although notable advances have been made to improve the reliability of stimulus-driven approaches, the reliance on the visual input remains a challenge for the interpretability of the obtained results. Therefore, we argue that there is an important role in the study of cortical neuroplasticity for approaches that assess intracortical signal processing and circuitry models that can link visual cortex anatomy, function, and dynamics.

The neuroscience of vision and pain: evolution of two disciplines.

Research in the neuroscience of pain perception and visual perception has taken contrasting paths. The contextual and the social aspects of pain judgements predisposed pain researchers to develop computational and functional accounts early, while vision researchers tended to simple localizationist or descriptive approaches first. Evolutionary thought was applied to distinct domains, such as game-theoretic approaches to cheater detection in pain research, versus vision scientists' studies of comparative visual ecologies. Both fields now contemplate current motor or decision-based accounts of perception, particularly predictive coding. Vision researchers do so without the benefit of earlier attention to social and motivational aspects of vision, while pain researchers lack a comparative behavioural ecology of pain, the normal incidence and utility of responses to tissue damage. Hybrid hypotheses arising from predictive coding as used in both domains are applied to some perplexing phenomena in pain perception to suggest future directions. The contingent and predictive interpretation of complex sensations, in such domains as 'runner's high', multiple cosmetic procedures, self-harm and circadian rhythms in pain sensitivity is one example. The second, in an evolutionary time frame, considers enhancement of primary perception and expression of pain in social species, when expressions of pain might reliably elicit useful help. This article is part of the Theo Murphy meeting issue 'Evolution of mechanisms and behaviour important for pain'.

An arbitrary-spectrum spatial visual stimulator for vision research.

Visual neuroscientists require accurate control of visual stimulation. However, few stimulator solutions simultaneously offer high spatio-temporal resolution and free control over the spectra of the light sources, because they rely on off-the-shelf technology developed for human trichromatic vision. Importantly, consumer displays fail to drive UV-shifted short wavelength-sensitive photoreceptors, which strongly contribute to visual behaviour in many animals, including mice, zebrafish and fruit flies. Moreover, many non-mammalian species feature more than three spectral photoreceptor types. Here, we present a flexible, spatial visual stimulator with up to six arbitrary spectrum chromatic channels. It combines a standard digital light processing engine with open source hard- and software that can be easily adapted to the experimentalist's needs. We demonstrate the capability of this general visual stimulator experimentally in the in vitro mouse retinal whole-mount and the in vivo zebrafish. With this work, we intend to start a community effort of sharing and developing a common stimulator design for vision research.

Sensory processing and categorization in cortical and deep neural networks

Many recent advances in artificial intelligence (AI) are rooted in visual neuroscience. However, ideas from more complicated paradigms like decision-making are less used. Although automated decision-making systems are ubiquitous (driverless cars, pilot support systems, medical diagnosis algorithms etc.), achieving human-level performance in decision making tasks is still a challenge. At the same time, these tasks that are hard for AI are easy for humans. Thus, understanding human brain dynamics during these decision-making tasks and modeling them using deep neural networks could improve AI performance. Here we modelled some of the complex neural interactions during a sensorimotor decision making task. We investigated how brain dynamics flexibly represented and distinguished between sensory processing and categorization in two sensory domains: motion direction and color. We used two different approaches for understanding neural representations. We compared brain responses to 1) the geometry of a sensory or category domain (domain selectivity) and 2) predictions from deep neural networks (computation selectivity). Both approaches gave us similar results. This confirmed the validity of our analyses. Using the first approach, we found that neural representations changed depending on context. We then trained deep recurrent neural networks to perform the same tasks as the animals. Using the second approach, we found that computations in different brain areas also changed flexibly depending on context. Color computations appeared to rely more on sensory processing, while motion computations more on abstract categories. Overall, our results shed light to the biological basis of categorization and differences in selectivity and computations in different brain areas. They also suggest a way for studying sensory and categorical representations in the brain: compare brain responses to both a behavioral model and a deep neural network and test if they give similar results.

Monovision and the Misperception of Motion

Monovision is a common prescription lens correction for presbyopia [1]. Each eye is corrected for a different distance, causing one image to be blurrier than the other. Millions of people have monovision corrections, but little is known about how interocular blur differences affect motion perception. Here, we report that blur differences cause a previously unknown motion illusion that makes people dramatically misperceive the distance and three-dimensional direction of moving objects. The effect occurs because the blurry and sharp images are processed at different speeds. For moving objects, the mismatch in processing speed causes a neural disparity, which results in the misperceptions. A variant of a 100-year-old stereo-motion phenomenon called the Pulfrich effect [2], the illusion poses an apparent paradox: blur reduces contrast, and contrast reductions are known to cause neural processing delays [3-6], but our results indicate that blurry images are processed milliseconds more quickly. We resolve the paradox with known properties of the early visual system, show that the misperceptions can be severe enough to impact public safety, and demonstrate that the misperceptions can be eliminated with novel combinations of non-invasive ophthalmic interventions. The fact that substantial perceptual errors are caused by millisecond differences in processing speed highlights the exquisite temporal calibration required for accurate perceptual estimation. The motion illusion-the reverse Pulfrich effect-and the paradigm we use to measure it should help reveal how optical and image properties impact temporal processing, an important but understudied issue in vision and visual neuroscience.

Applications of Manganese-Enhanced Magnetic Resonance Imaging in Ophthalmology and Visual Neuroscience.

Understanding the mechanisms of vision in health and disease requires knowledge of the anatomy and physiology of the eye and the neural pathways relevant to visual perception. As such, development of imaging techniques for the visual system is crucial for unveiling the neural basis of visual function or impairment. Magnetic resonance imaging (MRI) offers non-invasive probing of the structure and function of the neural circuits without depth limitation, and can help identify abnormalities in brain tissues in vivo. Among the advanced MRI techniques, manganese-enhanced MRI (MEMRI) involves the use of active manganese contrast agents that positively enhance brain tissue signals in T1-weighted imaging with respect to the levels of connectivity and activity. Depending on the routes of administration, accumulation of manganese ions in the eye and the visual pathways can be attributed to systemic distribution or their local transport across axons in an anterograde fashion, entering the neurons through voltage-gated calcium channels. The use of the paramagnetic manganese contrast in MRI has a wide range of applications in the visual system from imaging neurodevelopment to assessing and monitoring neurodegeneration, neuroplasticity, neuroprotection, and neuroregeneration. In this review, we present four major domains of scientific inquiry where MEMRI can be put to imperative use — deciphering neuroarchitecture, tracing neuronal tracts, detecting neuronal activity, and identifying or differentiating glial activity. We deliberate upon each category studies that have successfully employed MEMRI to examine the visual system, including the delivery protocols, spatiotemporal characteristics, and biophysical interpretation. Based on this literature, we have identified some critical challenges in the field in terms of toxicity, and sensitivity and specificity of manganese enhancement. We also discuss the pitfalls and alternatives of MEMRI which will provide new avenues to explore in the future.

Electroretinogram Recording in Larval Zebrafish using A Novel Cone-Shaped Sponge-tip Electrode.

The zebrafish (Danio rerio) is commonly used as a vertebrate model in developmental studies and is particularly suitable for visual neuroscience. For functional measurements of visual performance, electroretinography (ERG) is an ideal non-invasive method, which has been well established in higher vertebrate species. This approach is increasingly being used for examining the visual function in zebrafish, including during the early developmental larval stages. However, the most commonly used recording electrode for larval zebrafish ERG to date is the glass micropipette electrode, which requires specialized equipment for its manufacture, presenting a challenge for laboratories with limited resources. Here, we present a larval zebrafish ERG protocol using a cone-shaped sponge-tip electrode. The novel electrode is easier to manufacture and handle, more economical, and less likely to damage the larval eye than the glass micropipette. Like previously published ERG methods, the current protocol can assess outer retinal function through photoreceptor and bipolar cell responses, the a- and b-wave, respectively. The protocol can clearly illustrate the refinement of visual function throughout the early development of zebrafish larvae, supporting the utility, sensitivity, and reliability of the novel electrode. The simplified electrode is particularly useful when establishing a new ERG system or modifying existing small-animal ERG apparatus for zebrafish measurement, aiding researchers in the visual neurosciences to use the zebrafish model organism.

Bayesian analysis of retinotopic maps.

Human visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation-a subject's retinotopic measurements from small amounts of fMRI time-with a prior-a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.

The Neural Dynamics of Seeing-In

Philosophers have suggested that, in order to understand the particular visual state we are in during picture perception, we should focus on experimental results from vision neuroscience—in particular, on the most rigorous account of the functioning of the visual system that we have from vision neuroscience, namely, the ‘Two Visual Systems Model’. According to the initial version of this model, our visual system can be dissociated, from an anatomo-functional point of view, into two streams: a ventral stream subserving visual recognition, and a dorsal stream subserving the visual guidance of action. Following this model, philosophers have suggested that, since the two streams have different functions, they represent different properties of a picture. However, the original view proposed by the ‘Two Visual Systems Model’ about the presence of a strong anatomo-functional dissociation between the two streams has recently been questioned on both philosophical and experimental grounds. Indeed, the analysis of several new pieces of evidence seems to suggest that many visual representations in our visual system, related to different tasks, are the result of a deep functional interaction between the streams. In the light of the renewed status of the ‘Two Visual Systems Model’, also our best philosophical model of picture perception should be renewed, in order to take into account a view of the process of picture perception informed by the new evidence about such interaction. Despite this, no account fulfilling this role has been offered yet. The aim of the present paper is precisely to offer such an account. It does this by suggesting that the peculiar visual state we are in during picture perception is subserved by interstream interaction. This proposal allows us to rely on a rigorous philosophical account of picture perception that is, however, also based on the most recent results from neuroscience. Unless the explanation offered in this paper is endorsed, all the recent evidence from vision neuroscience will remain unexplained under our best empirically informed philosophical theory of picture perception.

Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data.

Many research questions in visual perception involve determining whether stimulus properties are represented and processed independently. In visual neuroscience, there is great interest in determining whether important object dimensions are represented independently in the brain. For example, theories of face recognition have proposed either completely or partially independent processing of identity and emotional expression. Unfortunately, most previous research has only vaguely defined what is meant by “independence,” which hinders its precise quantification and testing. This article develops a new quantitative framework that links signal detection theory from psychophysics and encoding models from computational neuroscience, focusing on a special form of independence defined in the psychophysics literature: perceptual separability. The new theory allowed us, for the first time, to precisely define separability of neural representations and to theoretically link behavioral and brain measures of separability. The framework formally specifies the relation between these different levels of perceptual and brain representation, providing the tools for a truly integrative research approach. In particular, the theory identifies exactly what valid inferences can be made about independent encoding of stimulus dimensions from the results of multivariate analyses of neuroimaging data and psychophysical studies. In addition, commonly used operational tests of independence are re-interpreted within this new theoretical framework, providing insights on their correct use and interpretation. Finally, we apply this new framework to the study of separability of brain representations of face identity and emotional expression (neutral/sad) in a human fMRI study with male and female participants.

An adaptive scale Gaussian filter to explain White's illusion from the viewpoint of lightness assimilation for a large range of variation in spatial frequency of the grating and aspect ratio of the targets.

The variation between the actual and perceived lightness of a stimulus has strong dependency on its background, a phenomena commonly known as lightness induction in the literature of visual neuroscience and psychology. For instance, a gray patch may perceptually appear to be darker in a background while it looks brighter when the background is reversed. In the literature it is further reported that such variation can take place in two possible ways. In case of stimulus like the Simultaneous Brightness Contrast (SBC), the apparent lightness changes in the direction opposite to that of the background lightness, a phenomenon often referred to as lightness contrast, while in the others like neon colour spreading or checkerboard illusion it occurs opposite to that, and known as lightness assimilation. The White’s illusion is a typical one which according to many, does not completely conform to any of these two processes. This paper presents the result of quantification of the perceptual strength of the White’s illusion as a function of the width of the background square grating as well as the length of the gray patch. A linear filter model is further proposed to simulate the possible neurophysiological phenomena responsible for this particular visual experience. The model assumes that for the White’s illusion, where the edges are strong and quite a few, i.e., the spectrum is rich in high frequency components, the inhibitory surround in the classical Difference-of-Gaussians (DoG) filter gets suppressed, and the filter essentially reduces to an adaptive scale Gaussian kernel that brings about lightness assimilation. The linear filter model with a Gaussian kernel is used to simulate the White’s illusion phenomena with wide variation of spatial frequency of the background grating as well as the length of the gray patch. The appropriateness of the model is presented through simulation results, which are highly tuned to the present as well as earlier psychometric results.