Interval Timing and Motor Programming by Cortico-Striatal Ensembles

皮质纹状体整体的间隔计时和运动编程

基本信息

  • 批准号:
    8298994
  • 负责人:
  • 金额:
    $ 50.94万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-08-01 至 2016-07-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Proper timing of movements is crucial for many behaviors of living organisms. Disorders of temporal processing have been linked to neurological diseases, such as aphasia, dyslexia and Parkinson's disease. Neurophysiological studies revealed the involvement of many brain areas in temporal processing, but the neural mechanism of behavioral timing remains poorly understood. This is in part because previous studies examined brain regions in isolation, whereas temporal processing may be fundamentally distributed. To address this problem, we propose a study in which we will apply the methods of multielectrode recordings and neural interfaces to elucidate the mechanisms of motor timing and their plasticity in corticostriatal ensembles. We hypothesize that corticostriatal ensembles simultaneously encode temporal and spatial parameters of motor activities and facilitate learning of new temporal contingencies. This hypothesis will be tested through three specific aims: 1. Identify neural modulations in corticostriatal ensembles underlying temporal programming of movements and their plasticity during learning. Rhesus macaques will be implanted with multielectrode arrays in multiple cortical areas and the striatum. Monkey arm-reaching motor tasks will require both interval timing and directional programming. Novel instructions will be used to introduce learning paradigms. We expect to find that spatial and temporal components of motor tasks are processed and modified conjointly by the corticostriatal system. 2. Develop neural decoders that extract spatial and temporal information from corticostriatal ensembles. We will use neural decoding algorithms (Wiener filter, Kalman filter, discriminant analysis and Markov chains) to extract both temporal and spatial characteristics of motor patterns from large populations of cortical and striatal neurons. We expect to find that overlapping populations of neurons contribute to the extraction of both temporal and spatial characteristics. 3. Develop a real-time paradigm in which temporal and spatial motor behaviors are learned and controlled through a neural interface. Rhesus macaques will perform the same tasks as in Aim 1, but through a neural interface which will use decoding algorithms developed in Aim 2. We expect that corticostriatal ensembles will plastically adapt to this direct brain control. As the outcome of the proposed study we expect to have uncovered essential features of corticostriatal control of temporal sequencing of movements and neural plasticity involved. Moreover, we expect to have created an interface that extracts temporal and spatial parameters of movements in real time. These findings will contribute to therapies of neurological disorders of temporal processing and to neural prosthetics that reproduce decoded motor patterns in assistive devices.
描述(由申请人提供):适当的运动时机对生物的许多行为是至关重要的。时间加工障碍与神经疾病有关,如失语症、阅读障碍和帕金森氏症。神经生理学研究表明,许多脑区参与了时间加工,但行为计时的神经机制仍然知之甚少。这在一定程度上是因为之前的研究孤立地检查了大脑区域,而时间处理可能基本上是分布式的。为了解决这个问题,我们提出了一项研究,在这项研究中,我们将应用多电极记录和神经接口的方法来阐明运动计时的机制及其在皮质纹状体系统中的可塑性。我们假设皮质纹状体集合同时编码运动活动的时间和空间参数,并促进对新的时间偶发事件的学习。这一假说将通过三个具体的目标来检验:1.确定皮层纹状体集合中的神经调制,以支持运动的时间编程及其在学习过程中的可塑性。猕猴将在多个皮质区域和纹状体植入多个电极阵列。猴子伸展手臂的运动任务将需要间隔计时和方向编程。将使用新颖的指导来介绍学习范例。我们期望发现运动任务的空间和时间部分由皮质纹状体系统共同处理和修改。2.开发神经解码器,从皮质纹状体集合中提取空间和时间信息。我们将使用神经解码算法(维纳滤波、卡尔曼滤波、判别分析和马尔可夫链)从大量皮质和纹状体神经元中提取运动模式的时间和空间特征。我们希望发现重叠的神经元群体对时间和空间特征的提取都有贡献。3.开发一种实时范式,在该范式中,通过神经接口学习和控制时间和空间运动行为。猕猴将执行与目标1相同的任务,但通过一个神经接口,将使用目标2中开发的解码算法。我们预计皮质纹状体系统将在可塑性上适应这种直接的大脑控制。作为拟议研究的结果,我们期望揭示皮质纹状体对运动的时间顺序的控制和所涉及的神经可塑性的基本特征。此外,我们预计已经创建了一个界面,可以实时提取运动的时间和空间参数。这些发现将有助于治疗神经系统的暂时性加工障碍,以及在辅助设备中复制解码运动模式的神经假体。

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 }}

Miguel A. L. Nicolelis其他文献

The brain decade in debate: VI. Sensory and motor maps: dynamics and plasticity.
大脑十年争论:VI。

Miguel A. L. Nicolelis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('Miguel A. L. Nicolelis', 18)}}的其他基金

Interval Timing and Motor Programming by Cortico-Striatal Ensembles
皮质-纹状体整体的间隔计时和运动编程
  • 批准号:
    8707567
  • 财政年份:
    2011
  • 资助金额:
    $ 50.94万
  • 项目类别:
Interval Timing and Motor Programming by Cortico-Striatal Ensembles
皮质纹状体整体的间隔计时和运动编程
  • 批准号:
    8084921
  • 财政年份:
    2011
  • 资助金额:
    $ 50.94万
  • 项目类别:
Interval Timing and Motor Programming by Cortico-Striatal Ensembles
皮质-纹状体整体的间隔计时和运动编程
  • 批准号:
    8896075
  • 财政年份:
    2011
  • 资助金额:
    $ 50.94万
  • 项目类别:
Interval Timing and Motor Programming by Cortico-Striatal Ensembles
皮质纹状体整体的间隔计时和运动编程
  • 批准号:
    8510738
  • 财政年份:
    2011
  • 资助金额:
    $ 50.94万
  • 项目类别:
A Virtual Reality Simulator to Study VLSBA and Test Brain-Actuating Technologies
用于研究 VLSBA 和测试大脑驱动技术的虚拟现实模拟器
  • 批准号:
    8153106
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:
A Virtual Reality Simulator to Study VLSBA and Test Brain-Actuating Technologies
用于研究 VLSBA 和测试大脑驱动技术的虚拟现实模拟器
  • 批准号:
    8708975
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:
Dorsal Column Stimulation as a New Therapy for Motor Disorders
背柱刺激作为运动障碍的新疗法
  • 批准号:
    8477324
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:
Dorsal Column Stimulation as a New Therapy for Motor Disorders
背柱刺激作为运动障碍的新疗法
  • 批准号:
    8150902
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:
Dorsal Column Stimulation as a New Therapy for Motor Disorders
背柱刺激作为运动障碍的新疗法
  • 批准号:
    8284352
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:
Dorsal Column Stimulation as a New Therapy for Motor Disorders
背柱刺激作为运动障碍的新疗法
  • 批准号:
    8016999
  • 财政年份:
    2010
  • 资助金额:
    $ 50.94万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 50.94万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了