CAREER: Unifying Neuroscience and Biomechanics Paradigms for Modeling Brain and Muscle Responses to Mechanical Impacts

职业:统一神经科学和生物力学范式,模拟大脑和肌肉对机械冲击的反应

基本信息

  • 批准号:
    2239110
  • 负责人:
  • 金额:
    $ 58.55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2028-08-31
  • 项目状态:
    未结题

项目摘要

Traumatic brain injury (TBI) remains a growing public health concern, with an annual prevalence of about 1.7 million cases and a yearly cost of about $40.6 billion in the United States alone. Despite an extensive body of work on TBI in biomechanics and neuroscience domains, there is still much progress to be made to advance the knowledge of TBI mechanics and associated motor impairments. In particular, fundamental knowledge of how and to what extent mechanical force impacts brain neuronal activity and, in turn, how and to what extent brain impairment affects neck muscle responses remains unknown. Therefore, this Faculty Early Career Development (CAREER) project seeks to develop a breakthrough computational framework that can mimic realistic brain-muscle activation dynamics and support discovering fundamental knowledge about TBI mechanics and associated interventions. This research requires methods and knowledge from various disciplines, including neuroscience, biomechanics, human factors, and control engineering, thus impacting the convergence of engineering and medicine. The project’s synergistic education and outreach activities outline a plan to strengthen the interdisciplinary field of neuro-biomechanics in bioengineering, industrial engineering, mechanical engineering, and chemical engineering through course development, involvement of graduate and undergraduate students in the research activities, and K-12 outreach activities. In addition, the outreach through webinars and video blogging will enhance scientific literacy levels about TBI among broad audiences, including first responders and TBI patients.The investigator’s long-term goal is to discover the fundamental relationship between brain multiphysics and neuromuscular dynamics in order to develop engineering technologies (i.e., helmet technologies, neuroprosthetics, etc.) and therapeutic interventions (e.g., TBI-focused rehabilitation, surgical treatments, etc.) to reduce TBI in sports, workplaces, and daily activities. In pursuit of this vision, this project will provide a Brain-Muscle-Interaction framework, called BMI-frame, a closed-loop framework composed of multiscale brain neuronal models, head-neck finite-element (FE) structures, proportional-integral-derivative (PID) algorithms, and neural network (NN) agents. This objective will be accomplished through three specific tasks: 1) investigate the effects of mechanical impacts on brain neuronal signals, 2) identify NN agents to predict brain and muscle PID gain parameters, and 3) characterize brain and muscle responses to mechanical impacts. Task 1 focuses on developing and validating brain electromechanical models to understand brain neuronal response to various (sub) traumatic impacts. Task 2 will explore novel NN algorithms in order to accurately tune brain signals and individual neck muscle activations with a minimal number of iterations and loop delays. Task 3 focuses on validating the BMI-frame platform by exploring the dynamics of brain-muscle interactions in response to various (sub) traumatic mechanical impacts and TBI conditions. The research is a breakthrough innovation as it transforms brain-muscle interaction dynamics into a mathematically-grounded engineering framework, with the purpose of creating unprecedented scientific knowledge about how (sub) traumatic mechanical impacts cause electromechanical disruptions of brain neuronal dynamics and, in turn, how brain neuronal disruptions affect neck muscle responses.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
创伤性脑损伤(TBI)仍然是一个日益严重的公共卫生问题,仅在美国每年就有约170万例患者,每年的成本约为406亿美元。尽管在生物力学和神经科学领域对颅脑损伤进行了大量的研究,但在提高对颅脑损伤力学和相关运动损伤的认识方面仍有很大的进展。特别是,机械力如何和在多大程度上影响脑神经元活动,以及大脑损伤如何和在多大程度上影响颈部肌肉反应的基础知识仍然未知。因此,该学院早期职业发展(CALEAR)项目寻求开发一个突破性的计算框架,该框架可以模拟现实的脑-肌肉激活动力学,并支持发现有关脑外伤机制和相关干预的基本知识。这项研究需要不同学科的方法和知识,包括神经科学、生物力学、人类因素和控制工程,从而影响工程学和医学的融合。该项目的协同教育和外展活动概述了一项计划,通过课程开发、研究生和本科生参与研究活动以及K-12外展活动,加强生物工程、工业工程、机械工程和化学工程中神经生物力学的跨学科领域。此外,通过网络研讨会和视频博客的推广将提高广大受众对脑外伤的科学素养水平,包括急救员和脑外伤患者。研究人员的长期目标是发现脑多物理和神经肌肉动力学之间的基本关系,以便开发工程技术(即头盔技术、神经假体等)。和治疗干预措施(例如,以脑外伤为重点的康复、外科治疗等)减少运动、工作场所和日常活动中的脑损伤。为了实现这一愿景,该项目将提供一个大脑-肌肉-交互框架,称为BMI-Frame,一个由多尺度脑神经元模型、头颈部有限元(FE)结构、比例-积分-导数(PID)算法和神经网络(NN)代理组成的闭环框架。这一目标将通过三个具体任务来实现:1)调查机械冲击对大脑神经元信号的影响,2)识别神经网络代理以预测大脑和肌肉的PID增益参数,以及3)表征大脑和肌肉对机械冲击的反应。任务1的重点是开发和验证大脑机电模型,以了解大脑神经元对各种(亚)创伤冲击的反应。任务2将探索新的神经网络算法,以便以最小的迭代次数和循环延迟精确调整大脑信号和个别颈部肌肉的激活。任务3的重点是通过探索脑-肌肉相互作用的动力学来验证BMI-Frame平台,以响应各种(亚)创伤性机械冲击和脑外伤条件。这项研究是一项突破性的创新,它将大脑-肌肉相互作用的动力学转变为一个基于数学的工程框架,目的是创造关于(亚)创伤性机械冲击如何导致脑神经元动力学的机电干扰,以及脑神经元破坏如何影响颈部肌肉反应的前所未有的科学知识。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

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 }}

Suman Chowdhury其他文献

Solar Power Potentiality Analysis in Some Regions of Bangladesh in the Case of Solar Irradiance
  • DOI:
    10.12691/joe-2-2-5
  • 发表时间:
    2014-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Suman Chowdhury
  • 通讯作者:
    Suman Chowdhury
Challenges in the management of localized intracranial ependymoma in children: Experience from a referral oncology center in Eastern India
儿童局部颅内室管膜瘤治疗的挑战:印度东部转诊肿瘤中心的经验
  • DOI:
    10.1080/08880018.2018.1564806
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    1.7
  • 作者:
    Anirban Das;Suman Chowdhury;R. Achari;L. Zameer;S. Sen;Reghu K. Sukumaran;A. Bhattacharyya
  • 通讯作者:
    A. Bhattacharyya
Bioactive Phytocompounds: Anti-amyloidogenic Effects Against Hen Egg-White Lysozyme Aggregation
生物活性植物化合物:对鸡蛋清溶菌酶聚集的抗淀粉样蛋白生成作用
  • DOI:
    10.1007/s10930-020-09946-5
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Suman Chowdhury;Suresh Kumar
  • 通讯作者:
    Suresh Kumar
Power Performance Evaluation of a PV Module Using MPPT with Fuzzy Logic Control
使用带有模糊逻辑控制的 MPPT 评估光伏模块的功率性能
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Suman Chowdhury;Dilip Kumar Das;Md Sharafat Hossain
  • 通讯作者:
    Md Sharafat Hossain
Plasmonic polyhedral silver nanocrystal decorated 2D-MoSsub2/sub as efficient SERS substrate for analyte detection
等离子体多面体银纳米晶修饰的二维二硫化钼作为用于分析物检测的高效表面增强拉曼散射基底
  • DOI:
    10.1016/j.molstruc.2025.142705
  • 发表时间:
    2025-10-15
  • 期刊:
  • 影响因子:
    4.700
  • 作者:
    Ummiya Qamar;Nikhil Kumar;Suman Chowdhury;Santanu Das
  • 通讯作者:
    Santanu Das

Suman Chowdhury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 }}

相似海外基金

UNIfying Grid-FOllowing And Grid-foRMing Control In Inverter-based Resources (UNIFORM)
统一基于逆变器的资源中的网格跟随和网格形成控制(UNIFORM)
  • 批准号:
    EP/Y001575/1
  • 财政年份:
    2024
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Research Grant
Unifying Object Detection and Image Captioning using Vision-Language Knowledge Base for Open-World Comprehension
使用视觉语言知识库统一对象检测和图像描述以实现开放世界理解
  • 批准号:
    24K20830
  • 财政年份:
    2024
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
CAREER: Dual Reinforcement Learning: A Unifying Framework with Guarantees
职业:双重强化学习:有保证的统一框架
  • 批准号:
    2340651
  • 财政年份:
    2024
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Continuing Grant
A unifying model for ion exchange membranes – towards a low carbon future
离子交换膜的统一模型 — 迈向低碳未来
  • 批准号:
    DP240101405
  • 财政年份:
    2024
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Discovery Projects
CAREER: Unifying Scientific Knowledge with Machine Learning for Forward, Inverse, and Hybrid Modeling of Scientific Systems
职业:将科学知识与机器学习相结合,对科学系统进行正向、逆向和混合建模
  • 批准号:
    2239328
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Continuing Grant
Unifying Pre-training and Multilingual Semantic Representation Learning for Low-resource Neural Machine Translation
统一预训练和多语言语义表示学习以实现低资源神经机器翻译
  • 批准号:
    22KJ1843
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
Unifying discrete and continuous methods in quantum information theory
统一量子信息论中的离散和连续方法
  • 批准号:
    FT230100571
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    ARC Future Fellowships
"Circular Transparency Platform", unifying the apparel value chain: From Thread to Second Life+. Enabling stakeholders from manufacturing and retail, to engage consumers with visual, incentivised Environmental, Social and Circular product experiences
“循环透明平台”,统一服装价值链:从Thread到Second Life。
  • 批准号:
    10059608
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Collaborative R&D
Unifying models of information processing across machine learning, artificial intelligence and neuroscience
统一机器学习、人工智能和神经科学的信息处理模型
  • 批准号:
    EP/X011151/1
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Fellowship
Unifying Probabilistic Computation for PDEs and Linear Systems
统一偏微分方程和线性系统的概率计算
  • 批准号:
    EP/Y001028/1
  • 财政年份:
    2023
  • 资助金额:
    $ 58.55万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了