Computational and Neural Mechanisms of Cognitive Control

认知控制的计算和神经机制

• 批准号: 7220729
• 负责人: JEREMY R REYNOLDS
• 金额: $ 4.86万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-29 至 2009-09-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7220729
• 关键词: behavioral /social science research tag; bioimaging /biomedical imaging; brain imaging /visualization /scanning; brain mapping; brain metabolism; clinical research; cognition; computational neuroscience; computer simulation; functional magnetic resonance imaging; human subject; neural information processing; neuropsychology; postdoctoral investigator; psychomotor function; short term memory; stimulus /response; university student

DESCRIPTION (provided by applicant): The purpose of the proposed research is to understand how biologically plausible mechanisms lead to controlled behavior. It is commonly acknowledged that there are typically many different ways to perform cognitive tasks, and further, that individual differences in personal strategies are a potential problem for experimental cognitive neuroscientists. However, there is very little theoretical development of why particular strategies are selected, or even how to address this issue. The proposed research uses computational simulations to investigate the trade-offs between different implemented strategies in the performance of a complex sequential working memory task. Further, predictions from such simulations are tested in subsequent empirical work. The trade-offs are investigated in the context of how quickly the different strategies learn to perform the task, the internal representations that they use to perform the task, and asymptotic performance. These studies will provide a formal basis for understanding how task demands influence the selection of different strategies, and they will provide experimental cognitive neuroscientists with additional insights into how to develop new paradigms that constrain the strategies that participants use. In addition to developing scientific tools, such an understanding will facilitate the development of behavioral therapies for patients with deficits in control, such as older adults and patients with schizophrenia. This project serves public health by developing a more comprehensive understanding of how humans perform difficult tasks that require control. By understanding why participants select the strategies they use to perform such tasks, researchers can develop new therapies that encourage the most efficient alternate strategies when the optimal ones are incapacitated through trauma, aging, or pathology.

描述（由申请人提供）：拟议研究的目的是了解生物学上合理的机制如何导致受控行为。人们普遍认为，执行认知任务的方法通常有许多不同的方法，此外，个人策略中的个体差异是实验性认知神经科学家的潜在问题。但是，为什么选择特定策略，甚至如何解决此问题的理论发展很少。拟议的研究使用计算模拟来研究复杂的顺序工作记忆任务执行不同实施策略之间的权衡。此外，在随后的经验工作中测试了此类模拟的预测。在不同的策略学习执行任务的速度，他们用来执行任务的内部表示以及渐近绩效的背景下，对权衡进行了研究。这些研究将为理解任务要求如何影响不同策略的选择提供正式的基础，它们将为实验认知神经科学家提供有关如何开发新范式来限制参与者使用的策略的其他见解。除了开发科学工具外，这种理解还将促进对控制缺陷的患者（例如老年人和精神分裂症患者）的行为疗法的发展。该项目通过对人类如何执行需要控制的艰巨任务有更全面的了解来为公共卫生提供服务。通过了解为什么参与者选择他们使用这些任务的策略，研究人员可以开发新的疗法，这些疗法在通过创伤，衰老或病理学使最佳策略无能为力时，鼓励最有效的替代策略。