Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics.
Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics.
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DOI：
10.1371/journal.pcbi.1002405
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发表时间：
2012
影响因子：
4.3
通讯作者：
Schwartz O
中科院分区：
文献类型：
--
作者：
Coen-Cagli R;Dayan P;Schwartz O
图像中的空间背景诱导与突显相关的知觉现象，并调节初级视觉皮质(V1)神经元的反应。然而，背景效应背后的计算和生态原理还没有完全被理解。我们介绍了一种自然图像模型，该模型包括基于联合统计量的相邻特征的分组和分割，并将V1神经元的放电率解释为在该模型中执行最优识别。我们表明，这导致了分裂归一化的实质性推广，这是一种在许多神经领域和系统中普遍存在的计算。我们模型的一个主要新奇之处在于，背景对目标刺激的影响取决于它们的统计依赖程度。我们对自然图像块上的模型参数进行了优化，然后模拟了经典实验中使用的刺激的神经和知觉反应。该模型再现了在V1中观察到的一些丰富而复杂的反应模式，如对比度依赖、方位调节和环绕抑制的空间不对称，同时也允许在弱刺激条件下的环绕促进。它还模仿了简单显示产生的感知突显，并导致易于测试的预测。我们的结果对早期视觉中基于方位的语境调节及其对输入的同质性和空间排列的敏感性提供了原则性的解释，并为V1计算视觉显著的理论提供了统计支持。关于哺乳动物大脑处理感官信息的方式，最重要和最持久的假设之一是，它们与自然界的统计结构微妙地协调一致。这允许他们在开发过程中，以一种反映环境中负责的方面的方式来表示投入。我们专注于关于视觉输入的局部取向的信息的情况，这是一种基本的水平特征，对于该特征，可以使用丰富的现象学观察来约束和验证计算模型。我们提出了一个新的帐户，专注于视觉空间中附近位置的方位统计，并捕捉到关于这种上下文信息如何调节初级视觉皮质神经元的反应以及相应的心理物理知觉的数据。因此，我们的方法有助于阐明早期视觉中潜在的上下文加工的计算和生态学原理；提供了一些可以用现有实验方法容易检验的预测；并表明了一条可能的路线，用于检验类似的计算原理和操作是否也支持更高水平的视觉功能。
Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience. One of the most important and enduring hypotheses about the way that mammalian brains process sensory information is that they are exquisitely attuned to the statistical structure of the natural world. This allows them to come, over the course of development, to represent inputs in a way that reflects the facets of the environment that were responsible. We focus on the case of information about the local orientation of visual input, a basic level feature for which a wealth of phenomenological observations are available to constrain and validate computational models. We suggest a new account which focuses on the statistics of orientations at nearby locations in visual space, and captures data on how such contextual information modulates both the responses of neurons in the primary visual cortex, and the corresponding psychophysical percepts. Our approach thus helps elucidate the computational and ecological principles underlying contextual processing in early vision; provides a number of predictions that are readily testable with existing experimental approaches; and indicates a possible route for examining whether similar computational principles and operations also support higher-level visual functions.
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