NEURAL CORRELATES OF MOTION PERCEPTION

运动感知的神经关联

• 批准号: 3475970
• 负责人: HALUK OGMEN
• 金额: $ 8.68万
• 依托单位: UNIVERSITY OF HOUSTON
• 依托单位国家: 美国
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-01 至 1997-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3475970
• 关键词: computational neuroscience; computer simulation; model design /development; psychological models; psychophysics; single cell analysis

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.

本研究旨在建立前注意视觉运动的神经模型 perception. 更深入地了解设计原则， 生物视觉与知觉神经描述的统一 现象转化为共同的理论语言与少量的动态 法律和组织原则是预期的长期成果， 研究项目。 由于各种因素，例如 眼睛和外部物体的运动，整合时间， 聚散度、调节和非均匀采样， 非常短暂、模糊和扭曲。 然而，这个问题得到了非常 很少有人注意，因为文献中提出的大多数模型 建立在静态（或稳态）分析的基础上， 聚焦图像。 因此，视觉中的一个基本问题包括： 分析图像瞬变，以实现动态而清晰的感知， 这些模糊的效果。 在本提案中，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。 创新实施 利用非线性分析技术和计算机进行理论研究 模拟测试和扩展的预测专门的神经 网络架构，我们提出了解释广泛的数据， 无脊椎动物和脊椎动物的运动和形状感知。 的 工作将考虑一方面运动知觉没有复杂的形式， 无脊椎动物的知觉，另一方面， 脊椎动物的复杂形状感知。 对前遗嘱的研究 包括通过分析最近的数据来改进我们早期的工作， 特别是关于通过运动提示进行的对象跟踪的数据。 的研究 后者将由运动通道和表单通道组成。 用于运动 通道，我们将扩展，适当的修改，我们的无脊椎动物模型 到脊椎动物 我们模型的基本性质，即非线性 预处理，瞬时行为和习惯敏感化将是 通过考虑探测这些性质的实验范例来研究， 即傅立叶运动和非傅立叶运动、视运动和偏析 运动对比度。 对于表单通道，我们将测试 通过研究相关实验数据对模型进行预测：掩蔽 数据，以测试动态形式的瞬时持续相互作用的作用 感知和去模糊数据，以测试所提出的时间相位， 它们的神经相关物。 我们还将进行分叉分析， 建立更普遍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学的广泛数据 对各种物种进行实验。