Combining Computational and Empirical Methods in Cognitive Neuroscience

认知神经科学中计算方法和经验方法的结合

• 批准号: 7434101
• 负责人: LYNNE Marie REDER
• 金额: $ 18.78万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7434101
• 关键词: Methods; cognitive neuroscience

DESCRIPTION (provided by applicant): There is a long tradition at CMU of striving for complete cognitive models to account for a wide range of phenomena using a small common set of theoretical assumptions. Our training program is the only one focused on training cognitive modeling skills. The Combined Computational and Behavioral Approaches to the Study of Cognitive Neuroscience (T32) has the specific aim of providing pre and postdoctoral trainees with the ability to formalize their theories about the mechanisms underlying normal and abnormal cognitive behavior and brain functioning. We will provide trainees with opportunities to conduct state of the art behavioral studies, neuro-imaging studies and build computational models that predict as well as account for behavioral and neuroscience data of cognitive tasks. The methodologies that the training faculty exploit to further our understanding of cognition include fMRI, ERP, psychopharmacological interventions and eye- tracking as well as reaction time and other behavioral studies in combination with computational modeling. Many of these methodologies are used in combination. In addition, the trainees will have the opportunity to rotate into the lab of a medical scientist who conducts cognitive neuroscience research concerned with one of several different types of mental disorders: autism, bi-polar, depression, or schizophrenia. The collaboration among trainee, mentor and clinical researcher will result in the opportunity to test theories of normal behavior with special populations as well as providing useful exposure for the trainees concerning the nature of cognitive and mood disorders. The goal of this proposal is primarily to train the next generation of computational modelers of cognition and cognitive brain function; however, the collaborative work on formal models of disordered cognition as a limiting case in cognitive neuroscience has the promise to bring synergy to both enterprises and move the theoretical work forward in both disciplines. The exciting aspect of this proposal is that it will not only train young researchers to appreciate clinical-cognitive issues and expose them to translational research but it promises to foster synergistic collaborations that have the potential to provide new insights into both normal functioning or treatments for patients who are suffering. We request two years of support for 2 predoctoral and 2 postdoctoral fellows appointed each year.

描述（由申请人提供）：卡耐基梅隆大学有着悠久的传统，致力于使用一组共同的理论假设来解释各种现象的完整认知模型。我们的培训计划是唯一专注于培训认知建模技能的培训计划。认知神经科学研究的计算和​​行为相结合的方法（T32）的具体目标是为博士前和博士后学员提供将其关于正常和异常认知行为和大脑功能背后机制的理论形式化的能力。我们将为学员提供进行最先进的行为研究、神经成像研究和构建计算模型的机会，以预测和解释认知任务的行为和神经科学数据。培训教师用来加深我们对认知的理解的方法包括功能磁共振成像、ERP、心理药理学干预和眼动追踪以及反应时间和其他与计算模型相结合的行为研究。许多这些方法可以组合使用。此外，学员将有机会轮流进入医学科学家的实验室，该实验室进行与几种不同类型的精神障碍之一有关的认知神经科学研究：自闭症、双相情感障碍、抑郁症或精神分裂症。学员、导师和临床研究人员之间的合作将有机会测试特殊人群的正常行为理论，并为学员提供有关认知和情绪障碍本质的有用知识。该提案的目标主要是训练下一代认知和认知大脑功能的计算建模者；然而，作为认知神经科学的一个极限案例，关于无序认知的正式模型的合作工作有望为两家企业带来协同效应，并推动这两个学科的理论工作向前发展。该提案令人兴奋的方面在于，它不仅将培训年轻研究人员认识临床认知问题并使他们接触转化研究，而且有望促进协同合作，有可能为遭受痛苦的患者的正常功能或治疗提供新的见解。我们请求为每年任命的 2 名博士前研究员和 2 名博士后研究员提供两年的支持。