Annual Review of Vision Science最新文献

A long-term goal of visual neuroscience is to develop and test quantitative models that account for the moment-by-moment relationship between neural responses in early visual cortex and human performance in natural visual tasks. This review focuses on efforts to address this goal by measuring and perturbing the activity of primary visual cortex (V1) neurons while nonhuman primates perform demanding, well-controlled visual tasks. We start by describing a conceptual approach-the decoder linking model (DLM) framework-in which candidate decoding models take neural responses as input and generate predicted behavior as output. The ultimate goal in this framework is to find the actual decoder-the model that best predicts behavior from neural responses. We discuss key relevant properties of primate V1 and review current literature from the DLM perspective. We conclude by discussing major technological and theoretical advances that are likely to accelerate our understanding of the link between V1 activity and behavior.

Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequency-selective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains. In the higher level, the velocity map is interpreted. Although there are many motion interpretation processes, we highlight the recent progress in research on the perception of material (e.g., specular reflection, liquid viscosity) and on animacy perception. We then consider possible linking mechanisms of the two levels and propose intrinsic flow decomposition as the key problem. To provide insights into computational mechanisms of motion perception, in addition to psychophysics and neurosciences, we review machine vision studies seeking to solve similar problems.

The retina is one of the most metabolically active tissues in the body, consuming high levels of oxygen and nutrients. A well-organized ocular vascular system adapts to meet the metabolic requirements of the retina to ensure visual function. Pathological conditions affect growth of the blood vessels in the eye. Understanding the neuronal biological processes that govern retinal vascular development is of interest for translational researchers and clinicians to develop preventive and interventional therapeutics for vascular eye diseases that address early drivers of abnormal vascular growth. This review summarizes the current knowledge of the cellular and molecular processes governing both physiological and pathological retinal vascular development, which is dependent on the interaction among retinal cell populations, including neurons, glia, immune cells, and vascular endothelial cells. We also review animal models currently used for studying retinal vascular development.

Motion in the visual world provides critical information to guide the behavior of sighted animals. Furthermore, as visual motion estimation requires comparisons of signals across inputs and over time, it represents a paradigmatic and generalizable neural computation. Focusing on the Drosophila visual system, where an explosion of technological advances has recently accelerated experimental progress, we review our understanding of how, algorithmically and mechanistically, motion signals are first computed.

Inferior temporal cortex (IT) is a key part of the ventral visual pathway implicated in object, face, and scene perception. But how does IT work? Here, I describe an organizational scheme that marries form and function and provides a framework for future research. The scheme consists of a series of stages arranged along the posterior-anterior axis of IT, defined by anatomical connections and functional responses. Each stage comprises a complement of subregions that have a systematic spatial relationship. The organization of each stage is governed by an eccentricity template, and corresponding eccentricity representations across stages are interconnected. Foveal representations take on a role in high-acuity object vision (including face recognition); intermediate representations compute other aspects of object vision such as behavioral valence (using color and surface cues); and peripheral representations encode information about scenes. This multistage, parallel-processing model invokes an innately determined organization refined by visual experience that is consistent with principles of cortical development. The model is also consistent with principles of evolution, which suggest that visual cortex expanded through replication of retinotopic areas. Finally, the model predicts that the most extensively studied network within IT-the face patches-is not unique but rather one manifestation of a canonical set of operations that reveal general principles of how IT works.

Visual motion on the retina activates a cohort of retinal ganglion cells (RGCs). This population activity encodes multiple streams of information extracted by parallel retinal circuits. Motion processing in the retina is best studied in the direction-selective circuit. The main focus of this review is the neural basis of direction selectivity, which has been investigated in unprecedented detail using state-of-the-art functional, connectomic, and modeling methods. Mechanisms underlying the encoding of other motion features by broader RGC populations are also discussed. Recent discoveries at both single-cell and population levels highlight the dynamic and stimulus-dependent engagement of multiple mechanisms that collectively implement robust motion detection under diverse visual conditions.

Receptive fields are a core property of cortical organization. Modern neuroimaging allows routine access to visual population receptive fields (pRFs), enabling investigations of clinical disorders. Yet how the underlying neural circuitry operates is controversial. The controversy surrounds observations that measurements of pRFs can change in healthy adults as well as in patients with a range of ophthalmological and neurological disorders. The debate relates to the balance between plasticity and stability of the underlying neural circuitry. We propose that to move the debate forward, the field needs to define the implied mechanism. First, we review the pRF changes in both healthy subjects and those with clinical disorders. Then, we propose a computational model that describes how pRFs can change in healthy humans. We assert that we can correctly interpret the pRF changes in clinical disorders only if we establish the capabilities and limitations of pRF dynamics in healthy humans with mechanistic models that provide quantitative predictions.

The human visual system reliably extracts shape information from complex natural scenes in spite of noise and fragmentation caused by clutter and occlusions. A fast, feedforward sweep through ventral stream involving mechanisms tuned for orientation, curvature, and local Gestalt principles produces partial shape representations sufficient for simpler discriminative tasks. More complete shape representations may involve recurrent processes that integrate local and global cues. While feedforward discriminative deep neural network models currently produce the best predictions of object selectivity in higher areas of the object pathway, a generative model may be required to account for all aspects of shape perception. Research suggests that a successful model will account for our acute sensitivity to four key perceptual dimensions of shape: topology, symmetry, composition, and deformation.

I was drawn into research in George Wald's laboratory at Harvard, where as an undergraduate and graduate student, I studied vitamin A deficiency and dark adaptation. A chance observation while an assistant professor at Harvard led to the major research of my career-to understand the functional organization of vertebrate retinas. I started with a retinal circuit analysis of the primate retina with Brian Boycott and intracellular retinal cell recordings in mudpuppies with Frank Werblin. Subsequent pharmacology studies with Berndt Ehinger primarily with fish focused on dopamine and neuromodulation. Using zebrafish, we studied retinal development, neuronal connectivity, and the effects of genetic mutations on retinal structure and function. Now semi-retired, I have returned to primate retinal circuitry, undertaking a connectomic analysis of the human fovea in Jeffrey Lichtman's laboratory.

The perceptual consequences of eye movements are manifold: Each large saccade is accompanied by a drop of sensitivity to luminance-contrast, low-frequency stimuli, impacting both conscious vision and involuntary responses, including pupillary constrictions. They also produce transient distortions of space, time, and number, which cannot be attributed to the mere motion on the retinae. All these are signs that the visual system evokes active processes to predict and counteract the consequences of saccades. We propose that a key mechanism is the reorganization of spatiotemporal visual fields, which transiently increases the temporal and spatial uncertainty of visual representations just before and during saccades. On one hand, this accounts for the spatiotemporal distortions of visual perception; on the other hand, it implements a mechanism for fusing pre- and postsaccadic stimuli. This, together with the active suppression of motion signals, ensures the stability and continuity of our visual experience.