Understanding Selective Recruitment in Neuronal Networks via Systems Theory
通过系统理论理解神经网络中的选择性招募
基本信息
- 批准号:1826065
- 负责人:
- 金额:$ 37.33万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-10-01 至 2022-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project will study the dynamics of systems characterized by a particular interconnection structure, inspired by properties of nerve cells. Nerve cell models typically implement some type of activation function, which determines how the nerve cell responds to input stimuli from other nerve cells. The activation function studied in this project passes an input signal without changes, if the input to the structure is positive. However, if the input to the activation function is negative, then the output is zero. This activation function gives rise to a model of nerve cell dynamics that is capable of accurately representing some behaviors of real neurons. There are powerful mathematical results available for these models. In contrast, nerve cell models with activation functions based on exponentials can be difficult to analyze. This project will create new mathematical tools to study how different subnetworks interact, either to suppress unwanted activity or to synchronize and reinforce their responses. These subnetworks can be built up hierarchically into progressively more complex structures. The project will relate these networks to both normal and abnormal neuronal circuits. The results will be of interest for the insight they provide into the architecture of the human brain, but also for constructing explainable engineered networks that can learn and adapt. This project will advance the national health and welfare by increasing understanding of biological neuronal systems, and by enabling the creation of robotic systems with enhanced resilience and adaptabilty. The project will also impact the training of a new generation of undergraduate and graduate students through undergraduate student involvement in research, graduate supervision and curriculum development, outreach targeted at middle, high school, incoming freshman and transfer students, involvement and retention of minority students, and broad dissemination activities.This project addresses the existing gap between the experimental evidence on selective recruitment in the brain and the theoretical understanding of the mechanisms that explain it. Taking a systems and controls perspective, the research effort aims to develop a mathematical framework to analyze how neuronal networks optimize their computational capabilities and unravel the role that network structure plays in shaping the dynamical behavior of the brain. This research seeks to advance the current knowledge on how the brain selects the relevant subnetworks during each time interval and suppresses the activity of others, and how it efficiently recruits those selected subnetworks and coordinates information transfer to and from them. The research plan is structured along the following interconnected research thrusts: (i) network stability and emergence of oscillations. The project seeks an in-depth characterization of the conditions on network structure that determine its dynamical properties, in particular, existence, uniqueness, and asymptotic stability of equilibrium points and limit cycles; (ii) inhibitory control and dynamic dimensionality. The project aims to characterize the mechanisms by which long-range connections between two networks can be used by one to dynamically inhibit different subset of nodes in the other. An aspect of particular importance is the consideration of physiologically-relevant scenarios involving feedforward and feedback inhibition, and their relation to network size, structure, and robustness; (iii) inter-regional connectivity and information transfer. Building on the lessons learned in the previous two thrusts, the project sets out to characterize the mechanisms of information transfer through coherent oscillations. This involves the study of ways in which neuronal networks can encode and decode information as oscillations and the role that the hierarchical structure and inter-regional connectivity of the brain has on them.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.
该项目将研究以特定互连结构为特征的系统的动力学,灵感来自神经细胞的特性。神经细胞模型通常实现某种类型的激活函数,其确定神经细胞如何响应来自其他神经细胞的输入刺激。本项目中研究的激活函数在结构的输入为正的情况下传递输入信号而不改变。然而,如果激活函数的输入为负,则输出为零。该激活函数产生了能够准确地表示真实的神经元的某些行为的神经细胞动力学模型。有强大的数学结果可用于这些模型。相比之下,具有基于指数的激活函数的神经细胞模型可能很难分析。该项目将创建新的数学工具来研究不同的子网络如何相互作用,以抑制不必要的活动或同步和加强它们的反应。这些子网络可以按层次逐步构建成更复杂的结构。该项目将把这些网络与正常和异常的神经元回路联系起来。这些结果将有助于我们深入了解人类大脑的结构,也有助于构建可解释的工程网络,使其能够学习和适应。该项目将通过增加对生物神经系统的了解,并通过创建具有增强弹性和适应性的机器人系统来促进国民健康和福利。该项目还将通过本科生参与研究、研究生监督和课程制定、针对初中、高中、新生和转学生的外联活动、少数民族学生的参与和保留,该项目旨在解决大脑中选择性招募的实验证据与理论证据之间存在的差距。从系统和控制的角度来看,研究工作旨在开发一个数学框架来分析神经网络如何优化其计算能力,并揭示网络结构在塑造大脑动力学行为中的作用。这项研究旨在推进目前的知识,即大脑如何在每个时间间隔内选择相关的子网络并抑制其他子网络的活动,以及它如何有效地招募这些选定的子网络并协调与它们之间的信息传输。 研究计划是结构沿着以下相互关联的研究重点:(一)网络的稳定性和振荡的出现。该项目旨在深入表征网络结构的条件,确定其动态特性,特别是平衡点和极限环的存在性,唯一性和渐近稳定性;(ii)抑制控制和动态维数。该项目旨在描述两个网络之间的远程连接可以被一个网络用来动态地抑制另一个网络中的不同节点子集的机制。特别重要的一个方面是考虑生理相关的情况下,涉及前馈和反馈抑制,以及它们与网络的大小,结构和鲁棒性;(iii)区域间的连接和信息传输。在前两个重点所吸取的经验教训的基础上,该项目着手确定通过相干振荡进行信息传递的机制的特征。这涉及到神经元网络如何将信息编码和解码为振荡的研究,以及大脑的层次结构和区域间连接对它们的作用。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估而被认为值得支持。
项目成果
期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Heterogeneity of central nodes explains the benefits of time-varying control scheduling in complex dynamical networks
- DOI:10.1093/comnet/cnz001
- 发表时间:2019-02
- 期刊:
- 影响因子:0
- 作者:Erfan Nozari;F. Pasqualetti;J. Cortés
- 通讯作者:Erfan Nozari;F. Pasqualetti;J. Cortés
Hierarchical Selective Recruitment in Linear-Threshold Brain Networks Part II: Multilayer Dynamics and Top-Down Recruitment
- DOI:10.1109/tac.2020.2997854
- 发表时间:2021-03-01
- 期刊:
- 影响因子:6.8
- 作者:Nozari,Erfan;Cortes,Jorge
- 通讯作者:Cortes,Jorge
Selective Recruitment in Hierarchical Complex Dynamical Networks with Linear-Threshold Rate Dynamics
- DOI:10.1109/cdc.2018.8618734
- 发表时间:2018-12
- 期刊:
- 影响因子:0
- 作者:Erfan Nozari;J. Cortés
- 通讯作者:Erfan Nozari;J. Cortés
Oscillations and coupling in interconnections of two-dimensional brain networks
二维大脑网络互连中的振荡和耦合
- DOI:
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:E. Nozari, J. Cortés
- 通讯作者:E. Nozari, J. Cortés
Structural characterization of oscillations in brain networks with rate dynamics
具有速率动力学的脑网络振荡的结构表征
- DOI:10.1016/j.automatica.2022.110653
- 发表时间:2022
- 期刊:
- 影响因子:6.4
- 作者:Nozari, Erfan;Planas, Robert;Cortés, Jorge
- 通讯作者:Cortés, Jorge
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Jorge Cortes其他文献
Optimal initial therapy for patients with newly diagnosed chronic myeloid leukemia in chronic phase
新诊断慢性粒细胞白血病慢性期患者的最佳初始治疗
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:3.2
- 作者:
E. Atallah;Jorge Cortes - 通讯作者:
Jorge Cortes
Update of Olverembatinib (HQP1351) Overcoming Ponatinib and/or Asciminib Resistance in Patients (Pts) with Heavily Pretreated/Refractory Chronic Myeloid Leukemia (CML) and Philadelphia Chromosome-Positive Acute Lymphoblastic Leukemia (Ph <sup>+</sup> ALL)
- DOI:
10.1182/blood-2023-187744 - 发表时间:
2023-11-02 - 期刊:
- 影响因子:
- 作者:
Elias Jabbour;Hagop M. Kantarjian;Paul B. Koller;Omer Jamy;Vivian G. Oehler;Elza Lomaia;Anthony M. Hunter;Olga Uspenskaya;Svetlana Samarina;Sudipto Mukherjee;Maria R. Baer;Vera Zherebtsova;Vasily Shuvaev;Anna Turkina;Igor Davydkin;Jorge Cortes;Huanshan Guo;Zi Chen;Lei Fu;Hengbang Wang - 通讯作者:
Hengbang Wang
Association and Significance of Allostatic Load with Outcomes of Patients with Chronic Myeloid Leukemia (CML)
- DOI:
10.1182/blood-2023-186127 - 发表时间:
2023-11-02 - 期刊:
- 影响因子:
- 作者:
Muhannad Sharara;Marisol Miranda-Galvis;Brenda Santellano;Jorge Cortes - 通讯作者:
Jorge Cortes
A Highly Successful Model to Decrease Racial Disparities and Increase Access to Autologous Transplants Among African Americans with Multiple Myeloma - Outreach and Satellite Transplant Clinics
- DOI:
10.1182/blood-2023-191069 - 发表时间:
2023-11-02 - 期刊:
- 影响因子:
- 作者:
Anand Jillella;Danielle Bradshaw;Mohammad Mian;Jorge Cortes;Amany R. Keruakous;Ayushi Chauhan;Locke Johnson Bryan;Molly Denlinger;Vamsi K. Kota - 通讯作者:
Vamsi K. Kota
Outcomes of Regimented Weight Monitoring on Morbidity and Mortality during AML Induction
- DOI:
10.1182/blood-2023-190979 - 发表时间:
2023-11-02 - 期刊:
- 影响因子:
- 作者:
Anvay Shah;Nabil Ghani;Danielle Bradshaw;Anand Jillella;Vamsi K. Kota;Jorge Cortes;Mark Dalgetty;Zachery Branham;Sandeep Yerraguntla;Locke Johnson Bryan;Amany R. Keruakous;Ayushi Chauhan - 通讯作者:
Ayushi Chauhan
Jorge Cortes的其他文献
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{{ truncateString('Jorge Cortes', 18)}}的其他基金
Collaborative Research: Analysis and Control of Nonlinear Oscillatory Networks for the Design of Novel Cortical Stimulation Strategies
合作研究:用于设计新型皮质刺激策略的非线性振荡网络的分析和控制
- 批准号:
2308640 - 财政年份:2023
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
Collaborative Research: Closed-loop Optimization and Control of Physical Networks Subject to Dynamic Costs, Constraints, and Disturbances
协作研究:受动态成本、约束和干扰影响的物理网络的闭环优化和控制
- 批准号:
2044900 - 财政年份:2021
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
CPS: Breakthrough: Robust Team-Triggered Coordination for Real-Time Control of Networked Cyber-Physical Systems
CPS:突破:强大的团队触发协调,用于网络信息物理系统的实时控制
- 批准号:
1329619 - 财政年份:2013
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
Self-triggered coordination of robotic networks
机器人网络的自触发协调
- 批准号:
1307176 - 财政年份:2013
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
Robust Distributed Online Convex Optimization
鲁棒分布式在线凸优化
- 批准号:
1300272 - 财政年份:2013
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
CDI Type-II: Distributed Ocean Monitoring via Integrated Data Analysis of Coordinated Buoyancy Drogues
CDI Type-II:通过协调浮力锥套的综合数据分析进行分布式海洋监测
- 批准号:
0941692 - 财政年份:2010
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
NetSE: Small: Collaborative Research: A Geometric Computational Approach to Efficiently Deploy and Manage Self-Organizing Wireless Communication Networks
NetSE:小型:协作研究:有效部署和管理自组织无线通信网络的几何计算方法
- 批准号:
0917166 - 财政年份:2009
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
DynSyst_Special_Topics: Couplings, Network Dynamics, and Stability of Multi-Agent Systems
DynSyst_Special_Topics:耦合、网络动力学和多智能体系统的稳定性
- 批准号:
0908508 - 财政年份:2009
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
CAREER: Information-driven distributed coordination of mobile sensor networks in dynamic scenarios
职业:动态场景下信息驱动的移动传感器网络分布式协调
- 批准号:
0830601 - 财政年份:2008
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
CAREER: Information-driven distributed coordination of mobile sensor networks in dynamic scenarios
职业:动态场景下信息驱动的移动传感器网络分布式协调
- 批准号:
0546871 - 财政年份:2006
- 资助金额:
$ 37.33万 - 项目类别:
Standard Grant
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How does the cerebellum contribute to neocortical processing across functional domains? Using selective recruitment to test the role of the cerebellum in the coordination of mental processes.
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