DYNAMIC PATTERNS IN COMPLEX BIOLOGICAL SYSTEMS/COMPETING

复杂生物系统/竞争中的动态模式

• 批准号: 2651547
• 负责人: J A SCOTT KELSO
• 金额: $ 41.14万
• 依托单位: FLORIDA ATLANTIC UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-08-01 至 2001-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2651547
• 关键词: auditory stimulus; behavioral /social science research tag; biological models; biomagnetism measurement; biomechanics; brain electrical activity; computational neuroscience; electrodes; electroencephalography; electromyography; electrophysiology; form /pattern perception; human subject; learning; limb movement; mathematical model; model design /development; neural information processing; neuropsychology; neuroregulation; perception; psychoacoustics; psychophysics; sensorimotor system; stimulus /response; visual stimulus

This proposal seeks continuation of a multi-disciplinary research effort at F.A..U.~s Center for Complex Systems between neuroscience, psychology and physics that seeks to uncover the basic organizational principles and mechanisms underlying higher brain function. In particular, questions asked are how human beings coordinate their actions with environment, how they perceive and categorize the world around them, and how they learn new skills. The principal hypothesis guiding the research, which embraces theory, computation and experiment, is that brain and behavior are self-organized, governed by coupled dynamical rules on several scales of observation. Such dynamics determine the collective activity of the nervous system, generating the time course of coordination states on a given level of description. Three major experimental sections are proposed to test predicted features of specific dynamical models in the context of the theory of self- organization. In each case, detailed hypotheses are made regarding the neural structures involved and their selective, task-specific engagement over time (to be obtained through a synergism of high density electrode, SquID arrays and fMRI). This information in turn will be used for two purposes: first, to meet the much needed demand for image analysis, compression and visualization that preserves the real-time dynamics of the brain; and, second, to develop theoretical models of global brain function that are based on realistic neuroanatomical and neurophysiological considerations. In addition, a number of new paradigms are proposed aimed at exposing novel dynamical processes that will promote further theoretical developments. Identifying key quantities for collective activity at both brain and behavioral levels and the dynamical rules by which self-organization occurs, should put us in a much better position to understand functional brain disorders. Since the relevant information will be known at the macroscopic level, this knowledge will place constraints on which microscopic processes and variables are relevant and which are not.

该提案寻求继续进行多学科研究 佛罗里达大学复杂系统中心的努力 神经科学、心理学和物理学试图揭示 上级组织的基本原则和机制 大脑功能。 特别是，提出的问题是人类如何 生物体将他们的行为与环境以及他们的感知方式相协调 并对他们周围的世界以及他们如何学习新事物进行分类 技能。 指导研究的主要假设， 涵盖理论、计算和实验，是大脑和 行为是自组织的，受耦合动态规则控制 在几个观察尺度上。这种动态决定了 神经系统的集体活动，产生时间进程 给定描述级别上的协调状态。 三大 提出实验部分来测试预测的特征 自我理论背景下的具体动力学模型 组织。 在每种情况下，都做出了详细的假设 所涉及的神经结构及其选择性、特定任务 随着时间的推移，参与度（通过高 密度电极、SquID 阵列和功能磁共振成像）。 该信息在 转会用于两个目的：第一，满足急需 对图像分析、压缩和可视化的需求 保留大脑的实时动态；其次， 开发基于全球大脑功能的理论模型 基于现实的神经解剖学和神经生理学考虑。 此外，还提出了一些新的范式，旨在 揭示新的动态过程，将进一步促进 理论发展。 确定集体的关键数量 大脑和行为层面的活动以及动力学规则 自组织的发生应该让我们处于一个更好的境地 了解功能性大脑疾病的立场。 由于相关 信息将在宏观层面上被了解，这些知识 将限制哪些微观过程和变量 哪些是相关的，哪些是不相关的。