Electrophysiological and Computational studies on action monitoring
动作监测的电生理学和计算研究
基本信息
- 批准号:1125788
- 负责人:
- 金额:$ 64.37万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-09-01 至 2015-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
How humans regulate their behaviors is a fundamental question. With funding from the National Science Foundation, Dr. Michael Frank of Brown University is investigating interactions between different brain regions involved in how people monitor, learn, and control their actions. This research project focuses on how humans accomplish restrained control over behavior when confronted with difficult decisions. Theoretical models and empirical results suggest that the prefrontal cortex and the basal ganglia interact during these motivated behaviors, and that the neurochemical dopamine plays a central role in both the prefrontal cortex and basal ganglia brain regions. Using electroencephalography (EEG), the investigators are measuring participants' brain waves associated with prefrontal cortex activity, while they perform computerized cognitive tasks that assess learning and decision making in difficult circumstances. The brain wave activity is expected to predict participants' cognitive performance on these tasks. Critically, this brain-behavior relationship is predicted to differ as a function of genetic variants in dopamine function in both the prefrontal cortex and basal ganglia. In another experiment, researchers are directly manipulating dopamine pharmacologically in order to determine how these brain and behavior relationships are causally altered by dopamine levels. In all of their studies, the investigators use detailed mathematical models guided by contemporary theory to isolate specific brain-behavior relationships. It is theorized that both genetic variants and pharmacological manipulations affect the way that the brain monitors, learns, and controls actions. The brain wave measures are allowing the research team to define how neurochemicals modulate the processes of large neural systems.This research has the goal to substantially advance our understanding of how humans are able to regulate their behaviors as a function of motivation and cognitive control. Scientists widely appreciate that there are large individual differences in these types of motivated behaviors, but only recently have they begun to understand some of the factors governing these differences. By combining multiple research approaches, this project is posed to reveal the ways in which genetic and neurochemical factors alter activity in brain areas that are critically involved in such behaviors. The project also has the potential to identify mechanisms that disrupt brain circuitry and lead to disorders in motivated behavior and cognitive control, including addiction and obsessive compulsive disorder among others.
人类如何调节自己的行为是一个基本问题。在美国国家科学基金会的资助下,布朗大学的迈克尔·弗兰克博士正在研究不同大脑区域之间的相互作用,这些区域涉及人们如何监测、学习和控制他们的行为。这个研究项目的重点是人类如何在面对困难的决定时实现对行为的克制控制。理论模型和实验结果表明,前额叶皮层和基底神经节在这些动机行为的相互作用,神经化学物质多巴胺在前额叶皮层和基底神经节脑区发挥着核心作用。使用脑电图(EEG),研究人员正在测量参与者与前额叶皮层活动相关的脑电波,同时他们执行计算机化的认知任务,评估在困难情况下的学习和决策。 脑波活动预计将预测参与者在这些任务上的认知表现。至关重要的是,这种大脑行为关系被预测为不同的功能,在前额叶皮层和基底神经节的多巴胺功能的遗传变异。在另一项实验中,研究人员直接操纵多巴胺水平,以确定这些大脑和行为关系是如何被多巴胺水平改变的。在他们所有的研究中,研究人员使用当代理论指导下的详细数学模型来分离特定的大脑-行为关系。理论上,遗传变异和药理学操作都会影响大脑监测、学习和控制行为的方式。 脑电波测量使研究小组能够确定神经化学物质如何调节大型神经系统的过程。这项研究的目标是大大推进我们对人类如何能够调节其行为作为动机和认知控制功能的理解。科学家们普遍认为,这些类型的动机行为存在很大的个体差异,但直到最近,他们才开始了解这些差异的一些因素。通过结合多种研究方法,该项目旨在揭示遗传和神经化学因素改变与此类行为密切相关的大脑区域活动的方式。该项目还有可能确定破坏大脑回路并导致动机行为和认知控制障碍的机制,包括成瘾和强迫症等。
项目成果
期刊论文数量(0)
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会议论文数量(0)
专利数量(0)
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Michael Frank其他文献
Logic Programming with Max-Clique and its Application to Graph Coloring (Tool Description)
Max-Clique逻辑编程及其在图形着色中的应用(工具说明)
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
M. Codish;Michael Frank;Amit Metodi;Morad Muslimany - 通讯作者:
Morad Muslimany
Pathological laughter
- DOI:
10.1016/s0196-0644(05)82056-6 - 发表时间:
1990-03-01 - 期刊:
- 影响因子:
- 作者:
Gordon L Zellers;Michael Frank;James Dougherty - 通讯作者:
James Dougherty
Transfer of Persistence to the Acquisition of a New Behaviour
将持久性转变为新行为的习得
- DOI:
- 发表时间:
1979 - 期刊:
- 影响因子:0
- 作者:
R. Eisenberger;J. Carlson;Michael Frank - 通讯作者:
Michael Frank
Twenty-Five Comparators Is Optimal When Sorting Nine Inputs (and Twenty-Nine for Ten)
对 9 个输入进行排序时,25 个比较器是最佳选择(对于 10 个输入,则需要 29 个比较器)
- DOI:
10.1109/ictai.2014.36 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
M. Codish;L. Cruz;Michael Frank;Peter Schneider - 通讯作者:
Peter Schneider
MANUAL THERAPY AS AN ALTERNATIVE TREATMENT FOR PANIC ATTACKS
手动疗法作为惊恐发作的替代治疗方法
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Sergii Frank;Michael Frank;George Frank - 通讯作者:
George Frank
Michael Frank的其他文献
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{{ truncateString('Michael Frank', 18)}}的其他基金
REU Site: Language, Cognition and Computation
REU 网站:语言、认知和计算
- 批准号:
1950223 - 财政年份:2020
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
REU Site: Language, Cognition and Computation
REU 网站:语言、认知和计算
- 批准号:
1659585 - 财政年份:2017
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
Collaborative Research: CompCog: Broad-coverage probabilistic models of communication in context
协作研究:CompCog:上下文中通信的广泛覆盖概率模型
- 批准号:
1456077 - 财政年份:2015
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
Wordbank: An Open Repository for Developmental Vocabulary Data
Wordbank:发展词汇数据的开放存储库
- 批准号:
1528526 - 财政年份:2015
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
How prefrontal cortex augments reinforcement learning
前额皮质如何增强强化学习
- 批准号:
1460604 - 财政年份:2015
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
Collaborative Research: RAPID: Evaluating the Cognitive and Educational Benefits of Mental Abacus Training
合作研究:RAPID:评估心算训练的认知和教育效益
- 批准号:
1550667 - 财政年份:2015
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
Travel Support For Junior Researchers Attending The Workshop On Frontiers Of Extreme Computing; October 23-27, 2005; Santa Cruz, CA
为参加极限计算前沿研讨会的初级研究人员提供差旅支持;
- 批准号:
0553518 - 财政年份:2005
- 资助金额:
$ 64.37万 - 项目类别:
Standard Grant
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