Lateral connectivity and contextual interactions in macaque primary visual cortex

Two components of cortical circuits could mediate contour integration in primary visual cortex (V1): intrinsic horizontal connections and feedback from higher cortical areas. To distinguish between these, we combined functional mapping with a new technique for labeling axons, a recombinant adenovirus bearing the gene for green fluorescent protein (GFP), to determine the extent, density, and orientation specificity of V1 intrinsic connections and V2 to V1 feedback. Both connections cover portions of V1 representing regions of visual space up to eight times larger than receptive fields as classically defined, though the intrinsic connections are an order of magnitude denser than the feedback. Whereas the intrinsic connections link similarly oriented domains in V1, V2 to V1 feedback displays no such specificity. These findings suggest that V1 intrinsic horizontal connections provide a more likely substrate for contour integration.     

Contour integration and segmentation with self-organized lateral connections

Contour integration in low-level vision is believed to occur based on lateral interaction between neurons with similar orientation tuning. How such interactions could arise in the brain has been an open question. Our model suggests that the interactions can be learned through input-driven self-organization, i.e., through the same mechanism that underlies many other developmental and functional phenomena in the visual cortex. The model also shows how synchronized firing mediated by these lateral connections can represent the percept of a contour, resulting in performance similar to that of human contour integration. The model further demonstrates that contour integration performance can differ in different parts of the visual field, depending on what kinds of input distributions they receive during development. The model thus grounds an important perceptual phenomenon onto detailed neural mechanisms so that various structural and functional properties can be measured and predictions can be made to guide future experiments.     

Visual shape recognition with contour propagation

A neural architecture is presented that encodes the visual space inside and outside of a shape. The contours of a shape are propagated across an excitable neuronal map and fed through a set of orientation columns, thus creating a pattern which can be viewed as a vector field. This vector field is then burned as synaptic, directional connections into a propagation map, which will serve as a “shape map”. The shape map identifies its own, preferred input when it is translated, deformed, scaled and fragmented, and discriminates other shapes very distinctively. Encoding visual space is much more efficient for shape recognition than determining contour geometry only.     

基于初级视觉皮层的同步振荡目标检测模型

提出一种基于初级视觉皮层的目标检测模型,该模型只采用方位选择性细胞和皮层内水平连接等Ｖ１基本单元,它以链码表示的目标轮廓作为知识,允许该知识以时间脉冲的形式控制Ｖ１区内神经细胞的动态活动,使与知识轮廓形状相符合的轮廓内的细胞进入同步振荡状态,实现对视野中特定目标轮廓的识别。计算机仿真结果表明,在较高级皮层的“知识”控制之下,初级视觉皮层结构上实现简单的目标检测是可行的。     

The functional geometry of local and horizontal connections in a model of V1.

A mathematical model of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the geometry of local and long-range horizontal connections. Each hypercolumn is modeled as a network of interacting excitatory and inhibitory neural populations with orientation and spatial frequency preferences organized around a pair of pinwheels. The pinwheels are arranged on a planar lattice, reflecting the crystalline-like structure of cortex. Local interactions within a hypercolumn generate orientation and spatial frequency tuning curves, which are modulated by horizontal connections between different hypercolumns on the lattice. The symmetry properties of the local and long-range connections play an important role in determining the types of spontaneous activity patterns that can arise in cortex.     

基于初级视觉皮层的图像匹配模型

提出一种基于初级视觉皮层的图像匹配模型。该模型只采用方位选择性细胞和皮层内有限范围水平连接等Ｖ１基本单元,它以链码表示的目标轮廓作为知识,允许该知识以时间脉冲的形式控制Ｖ１区内神经细胞的动态活动,使与知识轮廓形状相符合的轮廓内的细胞,逐步进入并维持在兴奋状态,最终实现对视野中特定目标轮廓的提取     

Adult visual cortical plasticity

The visual cortex has the capacity for experience-dependent change, or cortical plasticity, that is retained throughout life. Plasticity is invoked for encoding information during perceptual learning, by internally representing the regularities of the visual environment, which is useful for facilitating intermediate-level vision-contour integration and surface segmentation. The same mechanisms have adaptive value for functional recovery after CNS damage, such as that associated with stroke or neurodegenerative disease. A common feature to plasticity in primary visual cortex (V1) is an association field that links contour elements across the visual field. The circuitry underlying the association field includes a plexus of long-range horizontal connections formed by cortical pyramidal cells. These connections undergo rapid and exuberant sprouting and pruning in response to removal of sensory input, which can account for the topographic reorganization following retinal lesions. Similar alterations in cortical circuitry may be involved in perceptual learning, and the changes observed in V1 may be representative of how learned information is encoded throughout the cerebral cortex.     

Computational modeling and exploration of contour integration for visual saliency

We propose a computational model of contour integration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned collinearly along a contour in an image are enhanced. Our model adds such devices as a dopamine-like fast plasticity, local GABAergic inhibition and multi-scale processing of images. The fast plasticity addresses the problem of how neurons in visual cortex seem to be able to influence neurons they are not directly connected to, for instance, as observed in contour closure effect. Local GABAergic inhibition is used to control gain in the system without using global mechanisms which may be non-plausible given the limited reach of axonal arbors in visual cortex. The model is then used to explore not only its validity in real and artificial images, but to discover some of the mechanisms involved in processing of complex visual features such as junctions and end-stops as well as contours. We present evidence for the validity of our model in several phases, starting with local enhancement of only a few collinear elements. We then test our model on more complex contour integration images with a large number of Gabor elements. Sections of the model are also extracted and used to discover how the model might relate contour integration neurons to neurons that process end-stops and junctions. Finally, we present results from real world images. Results from the model suggest that it is a good current approximation of contour integration in human vision. As well, it suggests that contour integration mechanisms may be strongly related to mechanisms for detecting end-stops and junction points. Additionally, a contour integration mechanism may be involved in finding features for objects such as faces. This suggests that visual cortex may be more information efficient and that neural regions may have multiple roles.     

Contour integration and cortical processing.

Our understanding of visual processing in general, and contour integration in particular, has undergone great change over the last 10 years. There is now an accumulation of psychophysical and neurophysiological evidence that the outputs of cells with conjoint orientation preference and spatial position are integrated in the process of explication of rudimentary contours. Recent neuroanatomical and neurophysiological results suggest that this process takes place at the cortical level V1. The code for contour integration may be a temporal one in that it may only manifest itself in the latter part of the spike train as a result of feedback and lateral interactions. Here we review some of the properties of contour integration from a psychophysical perspective and we speculate on their underlying neurophysiological substrate.     

Traveling waves in visual cortex

Electrode recordings and imaging studies have revealed that localized visual stimuli elicit waves of activity that travel across primary visual cortex. Traveling waves are present also during spontaneous activity, but they can be greatly reduced by widespread and intensive visual stimulation. In this Review, we summarize the evidence in favor of these traveling waves. We suggest that their substrate may lie in long-range horizontal connections and that their functional role may involve the integration of information over large regions of space.     

Context modulates the ERP signature of contour integration

We investigated how the electrophysiological signature of contour integration is changed by the context in which a contour is embedded. Specifically, we manipulated the orientations of Gabor elements surrounding an embedded shape outline. The amplitudes of early visual components over posterior scalp regions were changed by the presence of a contour, and by the orientation of elements surrounding the contour. Differences in context type had an effect on the early P1 and N1 components, but not on the later P2 component. The presence of a contour had an effect on the N1 and P2 components, but not on the earlier P1 component. A modulatory effect of context on contour integration was observed on the N1 component. These results highlight the importance of the context in which contour integration takes place.     

Specificity and randomness: structure-function relationships in neural circuits

A fundamental but unsolved problem in neuroscience is how connections between neurons might underlie information processing in central circuits. Building wiring diagrams of neural networks may accelerate our understanding of how they compute. But even if we had wiring diagrams, it is critical to know what neurons in a circuit are doing: their physiology. In both the retina and cerebral cortex, a great deal is known about topographic specificity, such as lamination and cell-type specificity of connections. Little, however, is known about connections as they relate to function. Here, we review how advances in functional imaging and electron microscopy have recently allowed the examination of relationships between sensory physiology and synaptic connections in cortical and retinal circuits.     

Interhemispheric connections shape subjective experience of bistable motion

The right and left visual hemifields are represented in different cerebral hemispheres and are bound together by connections through the corpus callosum. Much has been learned on the functions of these connections from split-brain patients [1-4], but little is known about their contribution to conscious visual perception in healthy humans. We used diffusion tensor imaging and functional magnetic resonance imaging to investigate which callosal connections contribute to the subjective experience of a visual motion stimulus that requires interhemispheric integration. The "motion quartet" is an ambiguous version of apparent motion that leads to perceptions of either horizontal or vertical motion [5]. Interestingly, observers are more likely to perceive vertical than horizontal motion when the stimulus is presented centrally in the visual field [6]. This asymmetry has been attributed to the fact that, with central fixation, perception of horizontal motion requires integration across hemispheres whereas perception of vertical motion requires only intrahemispheric processing [7]. We are able to show that the microstructure of individually tracked callosal segments connecting motion-sensitive areas of the human MT/V5 complex (hMT/V5+; [8]) can predict the conscious perception of observers. Neither connections between primary visual cortex (V1) nor other surrounding callosal regions exhibit a similar relationship.     

End-stopping and the aperture problem: two-dimensional motion signals in macaque V1

Our perception of fine visual detail relies on small receptive fields at early stages of visual processing. However, small receptive fields tend to confound the orientation and velocity of moving edges, leading to ambiguous or inaccurate motion measurements (the aperture problem). Thus, it is often assumed that neurons in primary visual cortex (V1) carry only ambiguous motion information. Here we show that a subpopulation of V1 neurons is capable of signaling motion direction in a manner that is independent of contour orientation. Specifically, end-stopped V1 neurons obtain accurate motion measurements by responding only to the endpoints of long contours, a strategy which renders them largely immune to the aperture problem. Furthermore, the time course of end-stopping is similar to the time course of motion integration by MT neurons. These results suggest that cortical neurons might represent object motion by responding selectively to two-dimensional discontinuities in the visual scene.     

The neurogeometry of pinwheels as a sub-Riemannian contact structure.

We present a geometrical model of the functional architecture of the primary visual cortex (V1) and, more precisely, of its pinwheel structure. The problem is to understand from within how the internal "imminent" geometry of the visual cortex can produce the "transcendent" geometry of the external space. We use first the concept of blowing up to model V1 as a discrete approximation of a continuous fibration pi: R x P --> P with base space the space of the retina R and fiber the projective line P of the orientations of the plane. The core of the paper consists first in showing that the horizontal cortico-cortical connections of V1 implement what the geometers call the contact structure of the fibration pi, and secondly in introducing an integrability condition and the integral curves associated with it. The paper develops then three applications: (i) to Field's, Hayes', and Hess' psychophysical concept of association field, (ii) to a variational model of curved modal illusory contours (in the spirit of previous models due to Ullman, Horn, and Mumford), (iii) to Ermentrout's, Cowan's, Bressloff's, Golubitsky's models of visual hallucinations.     

Geometry and the visual brain.

Receptive fields structure of neurons in primary visual cortex suggests that they process visual stimuli in the frequency domain, in a way similar to the frequency analysis performed in the auditory system. As a consequence, both psychophysicists and electrophysiologists have long probed the visual system using extended sine wave gratings that are well localized in the frequency domain but poorly defined in visual space. Meanwhile, how the brain processes the geometrical properties and the spatial and temporal relationships between stimulus parts has received less attention. Recent progress in visual neuroscience that uncovered long-range horizontal connections between cortical neurons and revealed the complex architecture of primary visual cortex and feedback connectivity led to new insights concerned with the processing of geometrical properties of visual stimuli in V1. This paper presents a short historical perspective of the emergence of new issues related to the cortical architecture and its functional consequences on the processing of geometrical properties.     

The nature of illusory contour computation

Neural correlates of illusory contour perception have been found in both the early and the higher visual areas. But the locus and the mechanism for its computation remain elusive. Psychophysical evidence provided in this issue of Neuron shows that perceptual contour completion is likely done in the early visual cortex in a cascade manner using horizontal connections.     

Reduced Crowding and Poor Contour Detection in Schizophrenia Are Consistent with Weak Surround Inhibition

Background

Detection of visual contours (strings of small oriented elements) is markedly poor in schizophrenia. This has previously been attributed to an inability to group local information across space into a global percept. Here, we show that this failure actually originates from a combination of poor encoding of local orientation and abnormal processing of visual context.

Methods

We measured the ability of observers with schizophrenia to localise contours embedded in backgrounds of differently oriented elements (either randomly oriented, near-parallel or near-perpendicular to the contour). In addition, we measured patients’ ability to process local orientation information (i.e., report the orientation of an individual element) for both isolated and crowded elements (i.e., presented with nearby distractors).

Results

While patients are poor at detecting contours amongst randomly oriented elements, they are proportionally less disrupted (compared to unaffected controls) when contour and surrounding elements have similar orientations (near-parallel condition). In addition, patients are poor at reporting the orientation of an individual element but, again, are less prone to interference from nearby distractors, a phenomenon known as visual crowding.

Conclusions

We suggest that patients’ poor performance at contour perception arises not as a consequence of an “integration deficit” but from a combination of reduced sensitivity to local orientation and abnormalities in contextual processing. We propose that this is a consequence of abnormal gain control, a phenomenon that has been implicated in orientation-selectivity as well as surround suppression.     

克隆植物的水分生理整合及其生态效应

水分生理整合是克隆植物生理整合过程中非常重要的一部分,是克隆植物生长发育和生态适应过程中的重要机制之一。本文主要从理论上对克隆植物水分生理整合的存在性、方向性、整合的程度、范围及其与克隆植物的功能分工、表型可塑性和觅养行为、风险分摊等行为表现的关系进行了深入分析,并对迄今有关克隆植物水分整合的最新研究进展和研究方法进行了系统总结和评述。提出克隆植物的水分生理整合包括水平和垂直两个方向,而水力提降为垂直方向的水分生理整合提供了一个重要途径。认为在今后,应加强对克隆植物水分生理整合的精确定量化研究,同时,应运用生态学、生理学、生物化学及分子生物学等方法,综合深入地研究克隆植物水分整合的机理。