A multi-modal wireless oscillator array for high-resolution mapping of neurovascular coupling

用于神经血管耦合高分辨率映射的多模态无线振荡器阵列

基本信息

  • 批准号:
    10516470
  • 负责人:
  • 金额:
    $ 210.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-08-18 至 2025-07-31
  • 项目状态:
    未结题

项目摘要

Abstract An outstanding challenge of brain research is to link the cross-scale functional perspectives from the cellular and molecular level to the circuit and systems level. To address this unmet need, simultaneous fMRI with electroencephalogram (EEG) recording presents a unique scheme for functional dynamic mapping that would link neuronal activity with vascular hemodynamics. But mismatching of spatial localization between EEG and MRI, and their crosstalk due to electromagnetic interference have complicated post-processing procedures and interpretation of functional dynamics. Moreover, the confounding effect of astrocytic modulation can make fMRI signals have large variability, sometimes even opposite coupling features to neuronal activity. Therefore, there is strong motivation to surpass conventional paradigms of concurrent fMRI, EEG, and fiber photometry, to boost their performance via complementary strengths. Toward this goal, we will fabricate a wirelessly powered detector that can encode both neuronal and MRI signals into the same wireless carrier wave (Aim 1). We will validate the oscillator’s uncompromised detection performance against conventional wired detectors. We will also validate neuronal activation detected by wireless electrode against neuronal Ca2+ flux detected by fiber photometry. In Aim 2, we will develop a multi-electrode wireless oscillator to record neuronal signals from multiple brain layers and correlate them with layer-resolved line-scanning fMRI acquired in real-time. Meanwhile, we will use astrocytic Ca2+ as an indicator for spontaneous versus evoked neuronal activity. In Aim 3, we will develop a multi-element oscillator array to map neuro-glial-vascular (NGV) interaction across the entire brain, providing unique insights into synchronized neuronal activity when epileptic-like events are induced by optogenetic stimulation in the hippocampus. Successful completion of this project will enable us to better understand the NGV modulation of functional MRI, paving the way to bridge neuronal activity and behavior in normal and pathological brains.
摘要 脑研究的一个突出挑战是将跨尺度的功能观点从细胞和分子水平连接到电路和系统水平。为了解决这一未满足的需求,同步功能磁共振成像与脑电图(EEG)记录提出了一个独特的方案,功能动态映射,将神经元活动与血管血流动力学。但EEG和MRI之间的空间定位不匹配,以及由于电磁干扰引起的串扰,使得后处理过程和功能动力学解释变得复杂。此外,星形胶质细胞调制的混杂效应可以使fMRI信号具有较大的变异性,有时甚至与神经元活动相反的耦合特征。因此,有强烈的动机,超越传统的范式并发功能磁共振成像,脑电图,和纤维光度,以提高他们的性能,通过互补的优势。为了实现这一目标,我们将制造一个无线供电的探测器,它可以将神经元和MRI信号编码到同一个无线载波中(Aim 1)。我们将验证振荡器的不妥协的检测性能对传统的有线探测器。我们还将验证无线电极检测到的神经元激活与纤维光度法检测到的神经元Ca2+通量。在目标2中,我们将开发一种多电极无线振荡器,以记录来自多个大脑层的神经元信号,并将其与实时采集的层分辨线扫描fMRI相关联。同时,我们将使用星形胶质细胞Ca 2+作为自发性与诱发性神经元活动的指标。在目标3中,我们将开发一种多元件振荡器阵列,以映射整个大脑中的神经胶质血管(NGV)相互作用,当海马中的光遗传学刺激诱导癫痫样事件时,为同步神经元活动提供独特的见解。该项目的成功完成将使我们能够更好地了解功能性MRI的NGV调制,为桥接正常和病理大脑中的神经元活动和行为铺平道路。

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 }}

Chunqi Qian其他文献

Chunqi Qian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('Chunqi Qian', 18)}}的其他基金

Sensitivity enhancement of MRI with a Wireless Amplified NMR Detector
使用无线放大 NMR 探测器增强 MRI 的灵敏度
  • 批准号:
    8990836
  • 财政年份:
    2015
  • 资助金额:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 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:
    $ 210.25万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了