Annual Review of Vision Science - Volume 8, 2022

Millions of people worldwide are bilaterally blind due to corneal diseases including infectious etiologies, trauma, and chemical injuries. While corneal transplantation can successfully restore sight in many, corneal graft survival decreases in eyes with chronic inflammation and corneal vascularization. Additionally, the availability of donor cornea material can be limited, especially in underdeveloped countries where corneal blindness may also be highly prevalent. Development of methods to create and implant an artificial cornea (keratoprosthesis) may be the only option for patients whose eye disease is not suitable for corneal transplantation or who live in regions where corneal transplantation is not possible. The Boston Keratoprosthesis (B-KPro) is the most commonly implanted keratoprosthesis worldwide, having restored vision in thousands of patients. This article describes the initial design of the B-KPro and the modifications that have been made over many years. Additionally, some of the complications of surgical implantation and long-term care challenges, particularly complicating inflammation and glaucoma, are discussed.

The choriocapillaris, a dense capillary network located at the posterior pole of the eye, is essential for supporting normal vision, supplying nutrients, and removing waste products from photoreceptor cells and the retinal pigment epithelium. The anatomical location, heterogeneity, and homeostatic interactions with surrounding cell types make the choroid complex to study both in vivo and in vitro. Recent advances in single-cell RNA sequencing, in vivo imaging, and in vitro cell modeling are vastly improving our knowledge of the choroid and its role in normal health and in age-related macular degeneration (AMD). Histologically, loss of endothelial cells (ECs) of the choriocapillaris occurs early in AMD concomitant with elevated formation of the membrane attack complex of complement. Advanced imaging has allowed us to visualize early choroidal blood flow changes in AMD in living patients, supporting histological findings of loss of choroidal ECs. Single-cell RNA sequencing is being used to characterize choroidal cell types transcriptionally and discover their altered patterns of gene expression in aging and disease. Advances in induced pluripotent stem cell protocols and 3D cultures will allow us to closely mimic the in vivo microenvironment of the choroid in vitro to better understand the mechanism leading to choriocapillaris loss in AMD.

Voltage-gated Ca²⁺ (Cav) channels play pivotal roles in regulating gene transcription, neuronal excitability, and neurotransmitter release. To meet the spatial and temporal demands of visual signaling, Cav channels exhibit unusual properties in the retina compared to their counterparts in other areas of the nervous system. In this article, we review current concepts regarding the specific subtypes of Cav channels expressed in the retina, their intrinsic properties and forms of modulation, and how their dysregulation could lead to retinal disease.

The vertebrate retina is regarded as a simple part of the central nervous system (CNS) and thus amenable to investigations of the determinants of cell fate. Its five neuronal cell classes and one glial cell class all derive from a common pool of progenitors. Here we review how each cell class is generated. Retinal progenitors progress through different competence states, in each of which they generate only a small repertoire of cell classes. The intrinsic state of the progenitor is determined by the complement of transcription factors it expresses. Thus, although progenitors are multipotent, there is a bias in the types of fates they generate during any particular time window. Overlying these competence states are stochastic mechanisms that influence fate decisions. These mechanisms are determined by a weighted set of probabilities based on the abundance of a cell class in the retina. Deterministic mechanisms also operate, especially late in development, when preprogrammed progenitors solely generate specific fates.

In our tendency to discuss the objective properties of the external world, we may fail to notice that our subjective perceptions of those properties differ between individuals. Variability at all levels of the color vision system creates diversity in color perception, from discrimination to color matching, appearance, and subjective experience, such that each of us lives in a unique perceptual world. In this review, I discuss what is known about individual differences in color perception and its determinants, particularly considering genetically mediated variability in cone photopigments and the paradoxical effects of visual environments in both contributing to and counteracting individual differences. I make the case that, as well as being of interest in their own right and crucial for a complete account of color vision, individual differences can be used as a methodological tool in color science for the insights that they offer about the underlying mechanisms of perception.

Retinal circuits transform the pixel representation of photoreceptors into the feature representations of ganglion cells, whose axons transmit these representations to the brain. Functional, morphological, and transcriptomic surveys have identified more than 40 retinal ganglion cell (RGC) types in mice. RGCs extract features of varying complexity; some simply signal local differences in brightness (i.e., luminance contrast), whereas others detect specific motion trajectories. To understand the retina, we need to know how retinal circuits give rise to the diverse RGC feature representations. A catalog of the RGC feature set, in turn, is fundamental to understanding visual processing in the brain. Anterograde tracing indicates that RGCs innervate more than 50 areas in the mouse brain. Current maps connecting RGC types to brain areas are rudimentary, as is our understanding of how retinal signals are transformed downstream to guide behavior. In this article, I review the feature selectivities of mouse RGCs, how they arise, and how they are utilized downstream. Not only is knowledge of the behavioral purpose of RGC signals critical for understanding the retinal contributions to vision; it can also guide us to the most relevant areas of visual feature space.

An ultimate goal in retina science is to understand how the neural circuit of the retina processes natural visual scenes. Yet most studies in laboratories have long been performed with simple, artificial visual stimuli such as full-field illumination, spots of light, or gratings. The underlying assumption is that the features of the retina thus identified carry over to the more complex scenario of natural scenes. As the application of corresponding natural settings is becoming more commonplace in experimental investigations, this assumption is being put to the test and opportunities arise to discover processing features that are triggered by specific aspects of natural scenes. Here, we review how natural stimuli have been used to probe, refine, and complement knowledge accumulated under simplified stimuli, and we discuss challenges and opportunities along the way toward a comprehensive understanding of the encoding of natural scenes.

Good vision is important for safe driving. The impact of vision impairment associated with common eye diseases on driving performance, and the association between vision measures and driving performance, are discussed. Studies include those where participants drove a real vehicle on a closed road or on public roads. Closed-road studies include evaluation of both simulated and true vision impairment and day- and night-time driving. Collectively, the findings provide important insights into the impact of refractive conditions, cataracts, glaucoma, age-related macular degeneration, and hemianopic field loss on driving; however, study results show varying impacts on driving performance and are often limited by small sample sizes. Vision measures including motion sensitivity, contrast sensitivity, and useful field of view have stronger associations with driving performance than do visual acuity or visual fields, with studies suggesting that some drivers with field loss can compensate for their field defects through increased eye and head movements.

The quantification of vision impairments dates to the mid-nineteenth century with standardization of visual acuity and visual field measures in the eye clinic. Attempts to quantify the impact of vision impairments on patients’ lives did not receive clinical attention until the close of the twentieth century. Although formal psychometric theories and measurement instruments were well developed and commonplace in educational testing, as well as in various areas in psychology and rehabilitation medicine, the late start applying them to clinical vision research created a vacuum that invited poorly developed and poorly functioning instruments and analytic methods. Although this research is still burdened with legacy instruments, mandates by regulatory agencies to include the patients’ perspectives and preferences in the evaluation of clinical outcomes have stimulated the development and validation of self-report instruments grounded in modern psychometric theory and methods. Here I review the progress and accomplishments of applying modern psychometrics to clinical vision research.

Autism is a neurodevelopmental disorder of unknown etiology. Recently, there has been a growing interest in sensory processing in autism as a core phenotype. However, basic questions remain unanswered. Here, we review the major findings and models of perception in autism and point to methodological issues that have led to conflicting results. We show that popular models of perception in autism, such as the reduced prior hypothesis, cannot explain the many and varied findings. To resolve these issues, we point to the benefits of using rigorous psychophysical methods to study perception in autism. We advocate for perceptual models that provide a detailed explanation of behavior while also taking into account factors such as context, learning, and attention. Furthermore, we demonstrate the importance of tracking changes over the course of development to reveal the causal pathways and compensatory mechanisms. We finally propose a developmental perceptual narrowing account of the condition.

Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, we consider various types of learning (perceptual, statistical, and rule/abstract) associated with vision in the past decades and argue that they represent differently specialized versions of the fundamental learning process, which must be captured in its entirety when applied to complex visual processes. We show why the generalized version of statistical learning can provide the appropriate setup for such a unified treatment of learning in vision, what computational framework best accommodates this kind of statistical learning, and what plausible neural scheme could feasibly implement this framework. Finally, we list the challenges that the field of statistical learning faces in fulfilling the promise of being the right vehicle for advancing our understanding of vision in its entirety.

For four decades, investigations of the biological basis of critical periods in the developing mammalian visual cortex were dominated by study of the consequences of altered early visual experience in cats and nonhuman primates. The neural deficits thus revealed also provided insight into the origin and neural basis of human amblyopia that in turn motivated additional studies of humans with abnormal early visual input. Recent human studies point to deficits arising from alterations in all visual cortical areas and even in nonvisual cortical regions. As the new human data accumulated in parallel with a near-complete shift toward the use of rodent animal models for the study of neural mechanisms, it is now essential to review the human data and the earlier animal data obtained from cats and monkeys to infer general conclusions and to optimize future choice of the most appropriate animal model.

Occlusion therapy has a long history as the gold standard treatment for amblyopia. Over the past two decades, large multicenter randomized controlled trials and objective dose-monitoring studies have characterized the effects of refractive correction, patching, and atropine penalization, providing insights into the impact of factors such as age and treatment dose. More recent approaches, whose development has been accelerated by advances in technology, are designed to provide different stimulation to the amblyopic eye and the fellow eye. This review explores a variety of such dichoptic approaches, categorized according to whether they primarily feature requisite use of the amblyopic eye in the face of fellow-eye masking, integration of visual information from both eyes, or reduction of stimulus salience in the fellow eye. It is still unclear whether dichoptic treatments are superior to traditional, low-cost treatment methods or whether their therapeutic mechanisms are fundamentally different from those of established treatments.

Our brains devote substantial resources to creating a singular, coherent view from the two images in our eyes. Both anatomical and functional studies have established that the underlying fusion of monocular signals into a combined binocular response starts within the first synapses downstream from our eyes. Long-standing consensus held that the two eyes’ signals remain largely segregated until they are combined by neurons in the upper layers of the primary visual cortex. However, new experimental data challenge this classic model, suggesting that there are pronounced earlier interactions between the two eyes’ streams of activation. In this article, we review the literature and detail how these findings can be functionally interpreted in context with previously established psychophysical models of binocular vision.

Gamma oscillations (30–70 Hz) have been hypothesized to play a role in cortical function. Most of the proposed mechanisms involve rhythmic modulation of neuronal excitability at gamma frequencies, leading to modulation of spike timing relative to the rhythm. I first show that the gamma band could be more privileged than other frequencies in observing spike–field interactions even in the absence of genuine gamma rhythmicity and discuss several biases in spike–gamma phase estimation. I then discuss the expected spike–gamma phase according to several hypotheses. Inconsistent with the phase-coding hypothesis (but not with others), the spike–gamma phase does not change with changes in stimulus intensity or attentional state, with spikes preferentially occurring 2–4 ms before the trough, but with substantial variability. However, this phase relationship is expected even when gamma is a byproduct of excitatory–inhibitory interactions. Given that gamma occurs in short bursts, I argue that the debate over the role of gamma is a matter of semantics.

Visual representations of bodies, in addition to those of faces, contribute to the recognition of con- and heterospecifics, to action recognition, and to nonverbal communication. Despite its importance, the neural basis of the visual analysis of bodies has been less studied than that of faces. In this article, I review what is known about the neural processing of bodies, focusing on the macaque temporal visual cortex. Early single-unit recording work suggested that the temporal visual cortex contains representations of body parts and bodies, with the dorsal bank of the superior temporal sulcus representing bodily actions. Subsequent functional magnetic resonance imaging studies in both humans and monkeys showed several temporal cortical regions that are strongly activated by bodies. Single-unit recordings in the macaque body patches suggest that these represent mainly body shape features. More anterior patches show a greater viewpoint-tolerant selectivity for body features, which may reflect a processing principle shared with other object categories, including faces.

Voluntary attention selects behaviorally relevant signals for further processing while filtering out distracter signals. Neural correlates of voluntary visual attention have been reported across multiple areas of the primate visual processing streams, with the earliest and strongest effects isolated in the prefrontal cortex. In this article, I review evidence supporting the hypothesis that signals guiding the allocation of voluntary attention emerge in areas of the prefrontal cortex and reach upstream areas to modulate the processing of incoming visual information according to its behavioral relevance. Areas located anterior and dorsal to the arcuate sulcus and the frontal eye fields produce signals that guide the allocation of spatial attention. Areas located anterior and ventral to the arcuate sulcus produce signals for feature-based attention. Prefrontal microcircuits are particularly suited to supporting voluntary attention because of their ability to generate attentional template signals and implement signal gating and their extensive connectivity with the rest of the brain.

For over 100 years, eye movements have been studied and used as indicators of human sensory and cognitive functions. This review evaluates how eye movements contribute to our understanding of the processes that underlie decision-making. Eye movement metrics signify the visual and task contexts in which information is accumulated and weighed. They indicate the efficiency with which we evaluate the instructions for decision tasks, the timing and duration of decision formation, the expected reward associated with a decision, the accuracy of the decision outcome, and our ability to predict and feel confident about a decision. Because of their continuous nature, eye movements provide an exciting opportunity to probe decision processes noninvasively in real time.