NEURAL CORRELATES OF MOTION PERCEPTION

本研究旨在建立前注意视觉运动的神经模型。 感知力。更深入地了解 生物视觉与感觉神经描述的统一性 现象转化为共同的理论语言，具有少量的动态化 法律和组织原则预计将是这种情况的长期结果 研究项目。由于各种因素的影响--例如 眼睛和外部物体的运动，积分时间， 收敛、适应和非均匀采样视网膜图像是 非常短暂的、模糊的和扭曲的。然而，这个问题受到了非常多的关注 很少有人关注，因为文献中提出的大多数模型都是 围绕静态(或稳定状态)分析构建，并统一在 聚焦图像。因此，视觉中的一个根本问题包括 分析图像瞬变以实现动态而敏锐的感知，尽管 这些模糊的效果。在这项建议中，我们将通过以下方式解决这一问题 开发连续时间形式和运动通道模型。我们会带着 运用非线性分析技术和计算机进行理论研究 用模拟来检验和扩展专门神经的预测 我们建议用来解释各种数据的网络体系结构 无脊椎动物和脊椎动物的运动和形状感知。这个 作品一方面会考虑没有复杂形式的运动知觉 无脊椎动物的知觉，另一方面，运动知觉 脊椎动物的复杂形状知觉。对前遗嘱的研究 包括通过分析最近的数据和分析对我们早期工作的改进 尤其是关于通过运动提示进行对象跟踪的数据。对中国传统文化的研究 后者将由运动通道和形式通道组成。支持这项动议 渠道我们将扩展，通过适当的修改，我们的无脊椎动物模型 对脊椎动物来说。我们的模型的基本性质，即非线性 前处理、暂时性行为和习惯化-敏感化 通过考虑探索这些属性的实验范式进行研究， 即傅立叶和非傅立叶运动、表观运动和由 运动对比度分别为。对于表单通道，我们将测试 通过研究相关实验数据对模型的预测：掩蔽 测试动态形式的瞬变-持续交互作用的数据 感知和去模糊数据，以测试建议的时间阶段和 它们的神经相互关联。我们还将进行分支分析，以 建立一类更一般的视网膜外阳性的性质 模型的反馈交互作用。建模和测试将基于 从单细胞记录到心理物理记录的广泛数据 来自不同物种的实验。

This research aims to develop neural model of preattentive visual motion perception. A deeper understanding of design principles involved in biological vision and unification of the description of perceptual neural phenomena into a common theoretical language with a small number of dynamic laws and organizational principles are expected long-range outcomes of this research project. As a result of a variety of factors-such as the movements of the eyes and that of external objects, integration time, vergence, accommodation, and non-uniform sampling the retinal image is highly transient, blurred, and distorted. Yet, this problem received very little attention, for most of the models proposed in the literature axe built around the analysis of static (or steady-state) and uniformly in focus images. Thus, a fundamental problem in vision consists of the analysis of image transients to achieve dynamic yet sharp percepts despite these blurring effects. In this proposal, we will address this question by developing continuous-time form and motion channel models. We will carry out theoretical studies by using nonlinear analysis techniques and computer simulations to test and extend the predictions of specialized neural network architectures that we proposed to explain a wide range of data on motion and form perception in invertebrate and vertebrate species. The work will consider on the one hand motion perception without complex form perception in invertebrates and on the other hand motion perception with complex form perception in vertebrates. The study of the former will consist of the refinement of our earlier work by analyzing recent data and in particular, data on object tracking by motion cues. The study of the latter will consist of a motion channel and a form channel. For the motion channel we will extend, with suitable modifications, our invertebrate model to vertebrates. The fundamental properties of our model, namely nonlinear preprocessing, transient behavior, and habituation-sensitization will be studied by considering experimental paradigms probing these properties, i.e. Fourier & non-Fourier motion, apparent motion, and segregation by motion contrast respectively. For the form channel, we will test the predictions of the model by studying related experimental data: masking data to test the role of transient-sustained interactions in dynamic form perception and deblurring data to test the proposed temporal phases and their neural correlates. We will also carry out a bifurcation analysis to establish the properties of a more general class of extraretinal positive feedback interactions of the model. Modeling and testing will be based on extensive data ranging from single cell recordings to psychophysical experiments from a variety of species.