Action Potentials vs. Field Potentials as Inputs to a Brain-Machine Interface

动作电位与场电位作为脑机接口的输入

• 批准号: 7876844
• 负责人: Marc W. Slutzky
• 金额: $ 16.78万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7876844
• 关键词: Action Potentials; Address; Algorithms; American; Amyotrophic Lateral Sclerosis; Arts; Benchmarking; Biological Neural Networks; Brain; Cerebral Palsy; Cervical spinal cord injury; Clinical Research; Complex; Computer Simulation; Craniotomy; Data; Development Plans; Discriminant Analysis; Disease; Dura Mater; Electrodes; Electroencephalography; Environment; Evaluation; Figs - dietary; Fostering; Frequencies; Genetic Programming; Goals; Hand; Implant; Implanted Electrodes; Knowledge; Learning; Macaca; Macaca mulatta; Machine Learning; Measures; Mentors; Methods; Modeling; Monkeys; Motor; Motor Cortex; Movement; Muscle; Neurons; Operative Surgical Procedures; Output; Patients; Performance; Physicians; Pontine structure; Principal Investigator; Procedures; Process; Quadriplegia; Rattus; Relative (related person); Research; Research Personnel; Resolution; Scalp structure; Scientist; Signal Transduction; Source; Spinal cord injury; Statistical Methods; Stroke; Sum; Supervision; System; Techniques; Time; Tissues; Training; Visual; arm; brain machine interface; career development; computerized data processing; cranium; design; disability; feeding; flexibility; improved; in vivo; independent component analysis; motor control; novel; programs; prototype; relating to nervous system; research study; surgical technique development

DESCRIPTION (provided by applicant): Over 600,000 Americans have severely impaired motor function from disorders including spinal cord injury, amyotrophic lateral sclerosis, pontine stroke, and cerebral palsy. A brain-machine interface (BMI) could enable locked-in or tetraplegic patients to communicate and interact with their environment. Two crucial decisions in designing a BMI are (1) what type of brain signals to use as inputs to a controller and (2) what methods to use to decode those signals. Most BMIs have used either noninvasive scalp EEG recordings or invasive intracortical recordings of single- or multi-neuron spikes as control inputs. A few have used subdural or intracortical local field potentials (LFPs). However, no group has yet systematically compared these signals in motor cortex for use in BMI applications. This proposal's first goal is to assess the relative performance of spikes and field potentials (both intracortical and epidural) as control inputs for a variety of movement-related outputs. Epidural field potentials (EFPs) are intermediate in invasiveness, signal quality, stability and spatial resolution compared with existing scalp, subdural, and intracortical recordings, and thus represent an unexplored middle ground. This proposal's second goal is to evaluate linear and nonlinear techniques-including several novel to BMI applications-for both decoding data and reducing the inherently large dimensionality of data from multiple neural signals. The primary hypotheses of the proposed project are (1) that spikes will perform better in decoding more complex movement-related outputs, but that field potentials may perform similarly on decoding simpler outputs, and (2) that nonlinear decoders and dimensionality-reduction techniques may provide improved accuracy over linear methods. The specific aims to address these hypotheses are 1) to evaluate single neuron spikes as inputs to decoders of movement- related outputs, 2) to develop a novel epidural multi-electrode recording technique in the macaque monkey, and 3) to evaluate field potential signals as inputs to decoders of movement-related outputs. Aims 1 and 3 will involve application of dimensionality-reduction algorithms (e.g., independent components analysis, Isomap) and decoding algorithms (system identification, neural networks, support vector machines) to both spikes and field potentials. Aim 2 will entail using a computer model and spatial spectral analysis to optimize the epidural electrode array design. This project will provide the first comparison of spikes, LFPs and EFPs as inputs for identical BMI output applications. The supervision of Drs. Lee Miller and W. Zev Rymer, with additional guidance from Drs. Simon Levine, Jonathan Wolpaw and Nicholas Hatsopoulos, will provide the principal investigator with expertise in recording and processing both spikes and field potentials for BMI applications using a variety of state-of-the- art techniques. A comprehensive career development plan including clinical and research mentoring, seminars, and courses, will foster the candidate's transition into an independent physician-scientist.

描述（由申请人提供）： 超过60万的美国人因脊髓损伤、肌萎缩性侧索硬化、脑桥中风和脑瘫等疾病而严重损害运动功能。脑机接口（BMI）可以使闭锁或四肢瘫痪患者与他们的环境进行交流和互动。设计BMI的两个关键决定是（1）使用哪种类型的大脑信号作为控制器的输入，以及（2）使用什么方法来解码这些信号。大多数BMI使用非侵入性头皮EEG记录或侵入性皮质内记录单个或多个神经元尖峰作为控制输入。少数使用硬膜下或皮质内局部场电位（LFP）。然而，还没有一个研究小组系统地比较这些信号在运动皮层中的BMI应用。该建议的第一个目标是评估尖峰和场电位（皮质内和硬膜外）作为各种运动相关输出的控制输入的相对性能。与现有的头皮、硬膜下和皮质内记录相比，硬膜外场电位（EFP）在侵入性、信号质量、稳定性和空间分辨率方面处于中间水平，因此代表了一种未探索的中间地带。该提案的第二个目标是评估线性和非线性技术-包括BMI应用中的几种新技术-用于解码数据和减少来自多个神经信号的数据的固有大维度。拟议项目的主要假设是：（1）尖峰在解码更复杂的运动相关输出时表现更好，但场电位在解码更简单的输出时可能表现类似，以及（2）非线性解码器和降维技术可以提供比线性方法更高的准确性。解决这些假设的具体目的是：1）评估作为运动相关输出解码器输入的单个神经元尖峰，2）在猕猴中开发新型硬膜外多电极记录技术，以及3）评估作为运动相关输出解码器输入的场电位信号。目标1和3将涉及降维算法的应用（例如，独立分量分析，Isomap）和解码算法（系统识别，神经网络，支持向量机）的尖峰和场电位。目标2将需要使用计算机模型和空间频谱分析来优化硬膜外电极阵列设计。该项目将首次比较尖峰、LFP和EFP作为相同BMI输出应用的输入。Lee米勒和W. Zev Rymer在Simon Levine、Jonathan Wolpaw和Nicholas Hatsopoulos博士的额外指导下，将为主要研究者提供使用各种最先进技术记录和处理BMI应用的尖峰和场电位的专业知识。一个全面的职业发展计划，包括临床和研究指导，研讨会和课程，将促进候选人的过渡到一个独立的医生，科学家。