Motor cortical signaling of impedance during manipulation

操纵过程中运动皮层阻抗信号

基本信息

项目摘要

Project Summary A large body of research has led to statistical models showing how movement velocity is encoded in the motor cortex. However, forces also need to be controlled in harmony with motion when interacting with objects and research has rarely focused on how the motor system coordinates both together. The simultaneous variation of force and motion is incorporated in the definition of impedance. Our current neural models do not describe impedance encoding, which limits our understanding of object interaction, an important aspect of human behavior. The proposed research will develop new models of motor cortical impedance encoding during object interaction. Using these new models to decode ongoing impedance signaling, we will substantiate an advanced theory of impedance control used by the motor system to produce accurate object displacement in response to the forces applied by the hand. This research bridges the expertise of Dr. Schwartz in neurophysiology and of Dr. Hogan in robot control. Monkey subjects will perform tasks with real and virtual tools that naturally encourage the use of impedance control. We will record the activity of motor cortical neurons during these tasks and develop new mathematical models to describe the relation between neural activity and force, motion and impedance. Results from electromyography recordings, joint angle measurements and torque calculations, together with the neural models, will be used to better understand how impedance is regulated at the level of muscles and joints. Contributions of stretch reflexes to impedance will be studied and compared to the predictive impedance signaling decoded from motor cortex. This work promises to extend our understanding of the neural control principles governing the way we use our arms and hands to interact with our surroundings. These principles can be used to build new theories of the cognitive processes used to predict and effect changes in the world around us. At the same time, elucidation of the neural and mechanical details of forceful interaction will lead to new rehabilitative and neural prosthetic approaches to paralysis.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

ANDREW B. SCHWARTZ其他文献

ANDREW B. SCHWARTZ的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('ANDREW B. SCHWARTZ', 18)}}的其他基金

Motor cortical signaling of impedance during manipulation
操纵过程中运动皮层阻抗信号
  • 批准号:
    10362744
  • 财政年份:
    2020
  • 资助金额:
    $ 54.34万
  • 项目类别:
Motor cortical signaling of impedance during manipulation
操纵过程中运动皮层阻抗信号
  • 批准号:
    9885601
  • 财政年份:
    2020
  • 资助金额:
    $ 54.34万
  • 项目类别:
Building Better Brains: Neural Prosthetics and Beyond
构建更好的大脑:神经修复术及其他
  • 批准号:
    8007319
  • 财政年份:
    2010
  • 资助金额:
    $ 54.34万
  • 项目类别:
Model-based training for BCI rehabilitation
基于模型的 BCI 康复训练
  • 批准号:
    7937831
  • 财政年份:
    2009
  • 资助金额:
    $ 54.34万
  • 项目类别:
Model-based training for BCI rehabilitation
基于模型的 BCI 康复训练
  • 批准号:
    7817973
  • 财政年份:
    2009
  • 资助金额:
    $ 54.34万
  • 项目类别:
Cortical Control of a Dextrous Prosthetic Hand
灵巧假手的皮质控制
  • 批准号:
    7491025
  • 财政年份:
    2006
  • 资助金额:
    $ 54.34万
  • 项目类别:
Cortical Control of a Dextrous Prosthetic Hand
灵巧假手的皮质控制
  • 批准号:
    8516286
  • 财政年份:
    2006
  • 资助金额:
    $ 54.34万
  • 项目类别:
Cortical Control of a Dextrous Prosthetic Hand
灵巧假手的皮质控制
  • 批准号:
    7287764
  • 财政年份:
    2006
  • 资助金额:
    $ 54.34万
  • 项目类别:
Cortical Control of a Dextrous Prosthetic Hand
灵巧假手的皮质控制
  • 批准号:
    7125655
  • 财政年份:
    2006
  • 资助金额:
    $ 54.34万
  • 项目类别:
Cortical Control of a Dextrous Prosthetic Hand
灵巧假手的皮质控制
  • 批准号:
    7675933
  • 财政年份:
    2006
  • 资助金额:
    $ 54.34万
  • 项目类别:

相似海外基金

Shared and Distributed Memory Parallel Pre-Conditioning and Acceleration Algorithms for "Spline- Enhanced" Spatial Discretisations
用于“样条增强”空间离散化的共享和分布式内存并行预处理和加速算法
  • 批准号:
    2907459
  • 财政年份:
    2023
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Studentship
Efficient algorithms and succinct data structures for acceleration of telescoping and related problems
用于加速伸缩及相关问题的高效算法和简洁数据结构
  • 批准号:
    RGPIN-2021-03147
  • 财政年份:
    2022
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Discovery Grants Program - Individual
Acceleration framework for training deep learning by cooperative with algorithms and computer architectures
通过与算法和计算机架构合作训练深度学习的加速框架
  • 批准号:
    21K17768
  • 财政年份:
    2021
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Efficient algorithms and succinct data structures for acceleration of telescoping and related problems
用于加速伸缩及相关问题的高效算法和简洁数据结构
  • 批准号:
    RGPIN-2021-03147
  • 财政年份:
    2021
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Discovery Grants Program - Individual
Material and Device Building Blocks for Hardware Acceleration of Machine Learning and Artificial Intelligence Algorithms
用于机器学习和人工智能算法硬件加速的材料和设备构建模块
  • 批准号:
    2004791
  • 财政年份:
    2020
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Continuing Grant
CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
CIF:小型:协作研究:大规模非凸优化的加速算法
  • 批准号:
    1909291
  • 财政年份:
    2019
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Standard Grant
Acceleration of trigger algorithms with FPGAs at the LHC implemented using higher-level programming languages
使用高级编程语言在 LHC 上使用 FPGA 加速触发算法
  • 批准号:
    ST/S005560/1
  • 财政年份:
    2019
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Training Grant
CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
CIF:小型:协作研究:大规模非凸优化的加速算法
  • 批准号:
    1909298
  • 财政年份:
    2019
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Standard Grant
Acceleration of trigger algorithms with FPGAs at the LHC implemented using higher-level programming languages
使用高级编程语言在 LHC 上使用 FPGA 加速触发算法
  • 批准号:
    2348748
  • 财政年份:
    2019
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Studentship
OAC Core: Small: Enabling High-fidelity Turbulent Reacting-Flow Simulations through Advanced Algorithms, Code Acceleration, and High-order Methods for Extreme-scale Computing
OAC 核心:小型:通过高级算法、代码加速和超大规模计算的高阶方法实现高保真湍流反应流模拟
  • 批准号:
    1909379
  • 财政年份:
    2019
  • 资助金额:
    $ 54.34万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了