ITR/Comp Bio: The Computer Science of Biologically Embedded Systems

ITR/Comp Bio：生物嵌入式系统的计算机科学

• 批准号: 0113679
• 负责人: Michael Black
• 金额: $ 44.7万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0113679&HistoricalAwards=false
• 关键词: ITR; Comp; Bio; Computer; Science

EIA- 0113679 Black, MichaelBrown University ITR/SY: The Computer Science of Biologically-Embedded SystemsBiologically-embedded systems that directly couple artificial computational devices with neural systems are emerging as a new area of information technology research. The physical structure and adaptability of the human brain make these biologically-embedded systems quite different from computational systems typically studied in Computer Science.Fundamentally, biologically-embedded systems must make inferences about the behavior of a biological system based on measurements of neural activity that are indirect, ambiguous, and uncertain. Moreover these systems must adapt to short- and long-term changes in neural activity of the brain. These problems are addressed by a multi-disciplinary team in the context of developing a robot arm that is controlled by simultaneous recordings from neurons in the motor cortex of awake behaving monkeys. The goal is to probabilistically model the behavior of these neurons as a function of arm motion and then reconstruct continuous arm trajectories based on the neural activity. To do so, the project will exploit mathematical and computational techniques from computer vision, image processing, and machine learning.This work will enhance scientific knowledge about how to design and build new types of hybrid human/computer systems, will explore new devices to assist the severely disabled, will address the information technology questions raised by these biologically-embedded systems, and will contribute to the understanding of neural coding.

EIA- 0113679 Black，Michael Brown University ITR/SY：生物嵌入式系统的计算机科学直接将人工计算设备与神经系统耦合的生物嵌入式系统正在成为信息技术研究的一个新领域。 人类大脑的物理结构和适应性使得这些生物嵌入式系统与计算机科学中典型研究的计算系统非常不同。从根本上说，生物嵌入式系统必须基于间接的、模糊的和不确定的神经活动测量来推断生物系统的行为。 此外，这些系统必须适应大脑神经活动的短期和长期变化。 这些问题是由一个多学科的团队在开发一个机器人手臂的背景下解决的，该机器人手臂由清醒行为猴子运动皮层神经元的同步记录控制。 我们的目标是概率建模这些神经元的行为作为手臂运动的函数，然后根据神经活动重建连续的手臂轨迹。 为此，该项目将利用计算机视觉，图像处理和机器学习的数学和计算技术。这项工作将提高有关如何设计和构建新型混合人/计算机系统的科学知识，将探索帮助严重残疾人的新设备，将解决这些生物嵌入式系统提出的信息技术问题，并将有助于理解神经编码。