CAREER: System Theoretic Methods for Understanding the Dynamics of Cognition
CAREER: System Theoretic Methods for Understanding the Dynamics of Cognition
批准号:
1653589
负责人:
ShiNung Ching
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2023-07-31
中文摘要
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英文摘要
This Faculty Early Career Award (CAREER) project is aimed at understanding cognitive functions in the human brain by investigating neural mechanisms of cognition using tools from systems and control theory. The research will develop mathematical models that will help understand internal brain dynamics. The study will focus on establishing connections between properties of neural circuits and their information processing functionality. The research will use brain activity data from human subjects to validate the newly developed mathematical models to establish connections between brain dynamics and cognitive functions. The outcomes of this project can provide insights into developing treatments for neurological conditions associated with altered cognitive functions such as loss of cognitive ability due to severe brain injuries. The project will also help to educate scientists working in the cross-cutting discipline of systems theory and neuroscience and will improve interpretability and accessibility of neurological diagnostics. The PI has well integrated educational outreach program for students from a St. Louis magnet school that includes use of neurotechnology kits for exploring and visualizing brain dynamics. This research will foster sustained excitement for scientific inquiry in mathematics and brain science. This CAREER project will develop tools and techniques to understand certain cognitive states using methods of dynamics and control theory to analyze the dynamic behavior of neurons and the networks they form. The research will shed light on the role of dynamics and control within micro-scale neuronal networks as they relate to information processing. It will help understand how the dynamics of brain networks enable cognitively salient operations such as multi-modal integration and information retention. Along with these control-theoretic developments, this work will explore new methods for model- and data-driven characterization of neuronal dynamics at multiple spatial scales. The three specific objectives of this work are: (i) analyzing the relationship between macro-scale brain dynamics and cognitive function through new developments in dynamics and control; (ii) studying how neural dynamics may emerge in ways that support information processing; (iii) ensuring the long-term success of the program through numerous pedagogical and curricular endeavors.
期刊论文(25)
专著(0)
科研奖励(0)
会议论文
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DOI:
10.1016/j.neucom.2020.03.008
发表时间:
2020-08-04
期刊:
NEUROCOMPUTING
影响因子:
6
作者:
[Ghazizadeh,Elham, Ching,ShiNung]
通讯作者:
Ching,ShiNung
Resolving and characterizing the incidence of millihertz EEG modulation in critically ill children
解析和表征危重儿童毫赫兹脑电图调制的发生率
DOI:
10.1016/j.clinph.2022.02.010
发表时间:
2022
期刊:
Clinical Neurophysiology
影响因子:
4.7
作者:
[Loe, Maren E., Khanmohammadi, Sina, Morrissey, Michael J., Landre, Rebekah, Tomko, Stuart R., Guerriero, Réjean M., Ching, ShiNung]
通讯作者:
Ching, ShiNung
Geometric classification of brain network dynamics via conic derivative discriminants.
通过圆锥导数判别式对大脑网络动力学进行几何分类。
DOI:
10.1016/j.jneumeth.2018.06.019
发表时间:
2018
期刊:
Journal of neuroscience methods
影响因子:
3
作者:
[Singh,MatthewF, Braver,ToddS, Ching,ShiNung]
通讯作者:
Ching,ShiNung
DOI:
10.1162/neco_a_01182
发表时间:
2019-05-01
期刊:
NEURAL COMPUTATION
影响因子:
2.9
作者:
[Yi,Peng, Ching,ShiNung]
通讯作者:
Ching,ShiNung
Spiking networks as efficient distributed controllers
尖峰网络作为高效的分布式控制器
DOI:
10.1007/s00422-018-0769-7
发表时间:
2019
期刊:
Biological Cybernetics
影响因子:
1.9
作者:
[Huang, Fuqiang, Ching, ShiNung]
通讯作者:
Ching, ShiNung
共 17 条
NCS-FO: Modeling Individual Differences in Cognitive Control as Variation in Neural Activation Trajectories
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批准号:1835209
-
项目类别:Standard Grant
-
资助金额:$61.06万
-
财政年份:2018
-
负责人:ShiNung Ching
-
依托单位:
CRCNS Research Proposal: Collaborative Research: Studying Competitive Neural Network Dynamics Elicited By Attractive and Aversive Stimuli and their Mixtures
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批准号:1724218
-
项目类别:Continuing Grant
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资助金额:$46.95万
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财政年份:2017
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负责人:ShiNung Ching
-
依托单位:
Towards Analysis and Control of Dynamic Brain States
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批准号:1537015
-
项目类别:Standard Grant
-
资助金额:$37.46万
-
财政年份:2015
-
负责人:ShiNung Ching
-
依托单位:
国内基金
海外基金
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