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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

基本信息

批准号：
8289561
负责人：
LYNNE Marie REDER
金额：
$ 24.44万
依托单位：
CARNEGIE-MELLON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
1998
资助国家：
美国
起止时间：
1998-07-01 至 2014-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8289561
关键词：
Methods cognitive neuroscience

项目摘要

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）：CMU有一个悠久的传统，即努力建立完整的认知模型，用一套小的共同理论假设来解释广泛的现象。我们的培训项目是唯一专注于训练认知建模技能的项目。认知神经科学研究的计算和行为结合方法（T32）的具体目标是为博士后和博士生提供形式化他们关于正常和异常认知行为和大脑功能背后机制的理论的能力。我们将为学员提供机会进行最先进的行为研究、神经成像研究，并建立计算模型来预测和解释认知任务的行为和神经科学数据。培训教师利用的方法包括功能磁共振成像、ERP、心理药理学干预、眼动追踪以及反应时间和其他行为研究，这些方法与计算模型相结合，进一步加深了我们对认知的理解。这些方法中的许多都是组合使用的。此外，学员将有机会轮转到一位医学科学家的实验室，该科学家进行认知神经科学研究，涉及几种不同类型的精神障碍：自闭症、躁郁症、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在特殊人群中测试正常行为理论，并为学员提供有关认知和情绪障碍本质的有用信息。这个提议的目标主要是训练下一代的认知和认知脑功能的计算建模者；然而，作为认知神经科学的一个限制性案例，在无序认知的正式模型上的合作工作有望为两个企业带来协同效应，并推动两个学科的理论工作向前发展。这项提议令人兴奋的一面是，它不仅将训练年轻的研究人员欣赏临床认知问题，并使他们接触到转化研究，而且它承诺促进协同合作，这有可能为患者的正常功能或治疗提供新的见解。我们要求两年的支持，每年任命2名博士生和2名博士后。