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     

初级视觉皮层“简单”与“复杂”神经元动力学的计算建模

本文回顾了我们在哺乳动物视觉皮层的建模工作.利用初级视觉皮层的大规模神经元网络模型,我们解释了初级视觉皮层里“简单”与“复杂”神经元现象的网络机制.所谓的“简单”细胞对视觉刺激的反应近似线性,而“复杂”细胞对视觉刺激是非线性的.我们的模型成功地再现了简单和复杂细胞分布的实验数据.     

清醒猴纹状皮层（V1）神经元与注视位置相关的活动

用单细胞记录方法,研究了不同眼注视位置对清醒猴初级视皮层（Ｖ１）神经元自发活动的影响。实验前训练两只猴注视一个小光点,并使注视点在屏幕上顺序移动２５个位置。我们观察到：（１）５２％的初级视皮层神经元发放频率受眼位置调制,存在着一个能引起细胞最大发放的“注射野”;当注视点位于该细胞的注射野内时,发放频率明显增强。（２）大多数神经元的注视野位于感受野的外侧,多数在对侧视野范围内。（３）受眼位置影响的神     

老年猫视皮层细胞对刺激反应的对比敏感度下降伴随皮层内抑制作用减弱(英文)

对人类和动物的心理学研究证实,老年个体的视觉对比敏感度相对青年个体显著下降。为揭示其可能的神经机制,采用在体细胞外单细胞记录技术研究青、老年猫(Felis catus)初级视皮层(primary visual cortex,V1)细胞对不同视觉刺激对比度的调谐反应。结果显示,老年猫V1细胞对视觉刺激反应的平均对比敏感度比青年猫显著下降,这与灵长类报道的研究结果相一致,表明衰老影响视皮层细胞对视觉刺激反应的对比敏感度是灵长类和非灵长类哺乳动物中普遍存在的现象,并可能是介导老年性视觉对比敏感度下降的神经基础。另外,与青年猫相比,老年猫初级视皮层细胞对视觉刺激的反应性显著增强,信噪比下降,感受野显著增大,表明衰老导致的初级视皮层细胞对视觉刺激反应的对比敏感度下降伴随着皮层内抑制性作用减弱。     

视觉轮廓整合的神经机制

视觉轮廓整合是指视觉系统将视野中的离散元素组合为整体轮廓线的加工过程,是连接初级感觉加工和高级视觉物体知觉间的关键桥梁。对视觉轮廓整合神经机制的研究不仅能促进我们对人类知觉整合的理解,也有助于启发计算科学领域图形整合和分隔算法的改进。然而,轮廓整合的神经机制尚无最终定论。当前的争议主要集中在轮廓整合是基于初级视皮层固有水平连接的产物,还是基于脑区内水平连接及脑区间反馈连接共同作用的产物。本文在回顾这两种理论框架及其研究证据的基础上,对未来的研究问题和方向进行了展望。     

急性毁损猫的初级视区使高级视区细胞失去对视觉刺激的诱发反应(英文)

心理物理学研究提示,初级视区毁损后的视觉残留可能是通过外纹状皮层的神经网络重组介导的,但缺少支持这一假说的电生理实验证据。采用在体细胞外单细胞记录技术,该研究分别检测了初级视区(主要包括17和18区)急性毁损猫和正常对照猫的高级视区(包括19、20和21区)神经元对不同视觉刺激的反应性。结果显示,与对照相比,急性毁损初级视区使99.3%的高级视区神经元丧失对运动光栅刺激的诱发反应,93%的神经元丧失对闪光刺激的反应。该结果表明,急性毁损成年猫的初级视皮层可能会导致其绝大部分视觉能力丧失。在幼年期实施初级视皮层毁损后,成年猫出现的残留视觉可能主要是由于手术后皮层下神经核团与外纹状皮层之间的通路重组引起的。     

猫视皮层星形胶质细胞的老年性变化

电生理研究结果显示,在衰老过程中猫的视皮层神经元对视觉刺激的反应性出现显著的功能衰退,是否这种功能性衰退伴随胶质细胞活动的改变尚无直接的实验证据。以前期电生理实验猫为材料,用免疫形态学方法比较青年猫和老年猫初级视皮层内星形胶质细胞的活动状况。利用Nissl染色显示猫初级视皮层组织结构,用免疫组织化学方法（SABC法）显示GFAP免疫阳性（GFAP-IR）星形胶质细胞。光镜下观察、拍照,对GFAP-IR细胞计数并换算成密度,测量GFAP-IR直径取平均值。老年猫初级视皮层灰质各层及白质内的GFAP-IR细胞密度比青年猫的显著升高（p〈0.001）。与青年猫相比,老年猫视皮层灰质和白质中GFAP-IR细胞的平均直径均比青年猫的显著增大（p〈0.0001）,且老年猫视皮层内GFAP阳性免疫反应较青年猫的明显增强。老年猫初级视皮层神经元功能衰退伴随着星形胶质细胞活动的增强,胶质细胞活动增强有助于神经元之间的信息交流,因而可能对衰老过程中神经元的功能衰退起补偿作用。     

视觉中枢研究的新进展

在视觉传入通路中,各级神经元对视觉图象的传递和加工起着不同的作用。视网膜和外膝体细胞能传递图象的平均亮度,增强边缘和拐角;初级视皮层细胞能检测图象的基本特征,即线条/边缘的方位、运动方向、空间频率和深度等;高级视皮层细胞能对基本特征进行整合,从而反应复杂图形的整体特性。在视皮层内,调谐特性相同的细胞在垂直方向上排列成规则的“功能柱”结构,各种不同的功能柱组合成“超柱”,它可能是分析图象的基本功能单元.     

视觉皮层下通路与拓扑知觉

研究表明，视觉通路除了经典的视觉皮层通路外，还有一条“古老的”、快速的皮层下通路负责在有意识和无意识状态下快速处理与情绪相关的信息。皮层下视觉通路由上丘、枕核和杏仁核组成，而且不经过初级视觉皮层。我们前期研究表明，初级视觉皮层与拓扑知觉信息加工没有关系，而皮层下视觉通路负责处理视觉拓扑信息。基于这些发现，我们认为，在早期视觉中，大脑检测涉及生命攸关的信号，这些信号告诉大脑：环境中有物体出现或消失，使大脑进入警戒状态，这对物种的生存至关重要。因此，在早期视觉中，需要检测的要素只是物体的“出现”和“消失”，而不是“纹理”、“形状”等。“出现”和“消失”都是拓扑特征的变化。拓扑感知和皮层下视觉通路的存在可能是早期预警的神经基础。在灵长类动物中，视网膜外周区域主要由视杆细胞构成，该区域接收的视觉信息主要通过皮层下视觉通路进行处理；视网膜中心区域（即中央凹）主要由视锥细胞构成，视觉空间分辨率变得非常高，该区域视觉信息处理主要是由视觉皮层负责。研究表明，由视杆细胞构成的视网膜是个“古老”结构，在1亿多年前就出现了；而视锥细胞构成的视网膜类型较为“年轻”，在5 000万年前才出现。所以，我们的视网膜从“古老”结构演化到“年轻”结构至少用了5 000万年的时间，它是由一个古老结构和一个年轻结构共同组成的“嵌合体”。当我们讨论皮层下通路存在的意义时，我们也应该结合皮层通路的功能来统一考虑。     

视觉刺激对猴初级视皮层神经元眼球位置效应的影响

用细胞外记录的方法,研究了视觉刺激对清醒猴初级视皮层神经元眼球位置效应的影响,当猴注视电视屏幕上２５个不同位置的小光点时,屏蔽上分别给予两种不同形式的视觉刺激：注视点周围的闪光圆环和感受野内的移动光条。这两种刺激都能增强初级视皮层神经元的眼球位置相关活动,并相应地使受眼球位置调制的神经元的比例明显增加。     

Contour saliency in primary visual cortex

Contour integration is an important intermediate stage of object recognition, in which line segments belonging to an object boundary are perceptually linked and segmented from complex backgrounds. Contextual influences observed in primary visual cortex (V1) suggest the involvement of V1 in contour integration. Here, we provide direct evidence that, in monkeys performing a contour detection task, there was a close correlation between the responses of V1 neurons and the perceptual saliency of contours. Receiver operating characteristic analysis showed that single neuronal responses encode the presence or absence of a contour as reliably as the animal's behavioral responses. We also show that the same visual contours elicited significantly weaker neuronal responses when they were not detected in the detection task, or when they were unattended. Our results demonstrate that contextual interactions in V1 play a pivotal role in contour integration and saliency.     

Learning to link visual contours

In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about contours embedded in complex backgrounds is absent in V1 neuronal responses and is independent of the locus of spatial attention. Training animals to find embedded contours induces strong contour-related responses specific to the trained retinotopic region. These responses are most robust when animals perform the contour detection task but disappear under anesthesia. Our findings suggest that top-down influences dynamically adapt neural circuits according to specific perceptual tasks. This may serve as a general neuronal mechanism of perceptual learning and reflect top-down mediated changes in cortical states.     

Dependence of V2 illusory contour response on V1 cell properties and topographic organization

An illusory contour is an image that is perceived as a contour in the absence of typical contour characteristics, such as a change in luminance or chromaticity across the stimulus. In cats and primates, cells that respond to illusory contours are sparse in cortical area V1, but are found in greater numbers in cortical area V2. We propose a model capable of illusory contour detection that is based on a realistic topographic organization of V1 cells, which reproduces the responses of individual cell types measured experimentally. The model allows us to explain several experimentally observed properties of V2 cells including variability in orientation tuning and inducer spacing preference. As a practical application, the model can be used to estimate the relationship between the severity of a cortical injury in the primary visual cortex and the deterioration of V2 cell responses to real and illusory contours.     

A sparse object coding scheme in area V4

Sparse coding has long been recognized as a primary goal of image transformation in the visual system. Sparse coding in early visual cortex is achieved by abstracting local oriented spatial frequencies and by excitatory/inhibitory surround modulation. Object responses are thought to be sparse at subsequent processing stages, but neural mechanisms for higher-level sparsification are not known. Here, convergent results from macaque area V4 neural recording and simulated V4 populations trained on natural object contours suggest that sparse coding is achieved in midlevel visual cortex by emphasizing representation of acute convex and concave curvature. We studied 165 V4 neurons with a random, adaptive stimulus strategy to minimize bias and explore an unlimited range of contour shapes. V4 responses were strongly weighted toward contours containing acute convex or concave curvature. In contrast, the tuning distribution in nonsparse simulated V4 populations was strongly weighted toward low curvature. But as sparseness constraints increased, the simulated tuning distribution shifted progressively toward more acute convex and concave curvature, matching the neural recording results. These findings indicate a sparse object coding scheme in midlevel visual cortex based on uncommon but diagnostic regions of acute contour curvature.     

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.     

Multi-scale lines and edges in V1 and beyond: Brightness,object categorization and recognition,and consciousness

In this paper we present an improved model for line and edge detection in cortical area V1. This model is based on responses of simple and complex cells, and it is multi-scale with no free parameters. We illustrate the use of the multi-scale line/edge representation in different processes: visual reconstruction or brightness perception, automatic scale selection and object segregation. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only and final categorization on coarse plus fine scales. We also present a multi-scale object and face recognition model. Processing schemes are discussed in the framework of a complete cortical architecture. The fact that brightness perception and object recognition may be based on the same symbolic image representation is an indication that the entire (visual) cortex is involved in consciousness.     

A neural model of predictive recognition in form pathway of visual cortex

We present a functional model of form pathway in visual cortex based on predictive coding scheme, in which the prediction is compared with feedforward signals filtered by two kinds of spatial resolution maps, broad and fine resolution map. We propose here the functional role of the prediction and of the two kinds of resolution maps in perception of object form in visual system. The prediction is represented based on memory of dynamical attractors in temporal cortex, categorized by an elemental figure in posterior temporal cortex. The prediction is generated by the feedforward signals of main neurons in broad resolution maps of V(1) and V(4), and then is compared with the feedforward signals of main neurons in fine resolution map of V(1) and V(4).     

Visual event related potentials. The origin of wave P300. A computer model

This five-layered model consisting of 180 neurons is aimed at simulating some elementary functions of primary visual cortex of mammals in form detection. Its main achievements are: 1. Detection of points, lines, simple geometric figures in the V1. 2. Abstraction of 19 different qualities of geometric figures. 3. Simulation and rational explanation of processing of peripheral stimuli in the V1, explanation of mechanism of origin of visual ERPs, including P300 wave. 4. Simulation and explanation of the nature and build up of the cognitive function within V1 and its possible relation to long-term memory. 5. The model is based partly on Hebb-type synapses, illustrates the role of neuronal assemblies, sheds light on the functional relationship of excitatory and inhibitory neurons, in their conformity with special tasks of different cortical layers.     

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.