0


基于生态系统的神经科学和神经工程

ECoG-Based Neuroscience and Neuroengineering
课程网址: http://videolectures.net/bbci2012_schalk_neuroscience/  
主讲教师: Gerwin Schalk
开课单位: 纽约州卫生署
开课时间: 2012-12-03
课程语种: 英语
中文简介:
信号处理/机器学习、计算机科学、材料工程和神经科学的交叉开始为系统和认知神经科学以及转化神经工程的重要进展带来令人兴奋的机遇。我们过去15年的工作重点是利用这些机会。我们的神经科学研究通过将计算技术应用于人类大脑表面的记录(皮质电图(ECoG))来研究运动、语言和认知功能的神经基础。例如,我们研究不同皮质区域的局部场电位如何准备和执行手或手指的运动。我们的神经工程研究利用由此产生的神经科学的理解,旨在解决特定的临床问题。该工作包括统计信号处理、机器学习和实时系统设计与实现。例如,我们一直在为侵入性脑外科开发一种新的实时成像技术。在这个演讲中,我将描述在ECoG中可以检测到的信号类型,以及对它们的生理起源的新认识。然后,我将演示ECoG编码功能的详细方面,如实际或想象的语音。最后,我将展示基于ecogs的通信和控制的演示,以及我们的实时无源功能映射技术。总的来说,这次演讲的目的是交流神经科学和神经工程整合所带来的大量研究和新兴的商业机会,并希望激励神经技术社区参与其中。
课程简介: The intersection of signal processing/machine learning, computer science, material engineering and neuroscience is beginning to open up exciting opportunities for important advances in systems and cognitive neuroscience and in translational neuroengineering. Our work over the past 15 years has focused on taking advantages of these opportunities. Our neuroscience research investigates the neural basis of motor, language, and cognitive function by applying computational techniques to recordings from the surface of the brain (electrocorticography (ECoG)) in humans. For example, we study how local field potentials in different cortical areas prepare for and execute hand or finger movements. Our neuroengineering research is taking advantage of the resulting neuroscientific understanding and aims to address particular clinical problems. This work includes statistical signal processing, machine learning, and real-time system design and implementation. For example, we have been developing a new real-time imaging technique for invasive brain surgery. In this talk, I will describe the types of signals that can be detected in ECoG and the emerging understanding of their physiological origin. I will then demonstrate that ECoG encodes detailed aspects of function, such as actual or imagined speech. Finally, I will show demonstrations of ECoG-based communication and control, and of our real-time passive functional mapping technique. Overall, this talk aims to communicate the substantial research and emerging commercial opportunities that arise from integration of neuroscience and neuroengineering, and hopes to inspire the neurotechnology community to participate in them.
关 键 词: 信号处理; 机器学习; 计算机科学; 材料工程和神经科学的交叉; 认知神经科学; 转化神经工程
课程来源: 视频讲座网
最后编审: 2019-10-22:cwx
阅读次数: 83