Cognitive and Neural Correlates of Mathematics Problem Solving Using Diagnostic Modeling and Dynamic Real-Time fMRI
使用诊断模型和动态实时功能磁共振成像解决数学问题的认知和神经关联
基本信息
- 批准号:1561716
- 负责人:
- 金额:$ 149.96万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-08-01 至 2021-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The broad objective of this study, led by a team of researchers at Case Western Reserve University, is to further understanding of the neural and cognitive basis for mathematics learning. The focus will be on mathematics problem-solving strategies used by adolescents, and how these strategies are adopted and changed as problems become systematically more difficult. The project will examine the association of these strategies with mathematics-related cognitive skills, scores on tests of mathematics achievement, and patterns of brain activations displayed by adolescents while engaged in these strategies. Problem-solving strategies are of interest because of their relation to higher-level mathematic achievement and the insights they can offer into the basis of individual differences in mathematics learning. The longer-term objective of the project is to discover new ways to tailor mathematical learning strategies to individual cognitive and neural capacities. The project will also undertake innovative methods of collecting information about neural functioning during math tasks with the potential to influence future studies of the brain systems involved in learning and behavior. The project is funded by the EHR (Education and Human Resources directorate) Core Research program, which supports fundamental research that advances the literature on STEM (Science, Technology, Engineering and Mathematics) learning. Participants will be adolescents, 14-16 years of age, who were previously enrolled in a longitudinal study of the consequences of preterm versus term birth on academic progress across the first 3 years in school. Measures will include tests of spatial skills, attention, executive functions such as working memory, number sense, and mathematics achievement; sets of mental arithmetic and fractions problems of varying difficulty designed to reveal individual differences in problem-solving strategies; and functional magnetic resonance imaging (fMRI) procedures to examine the neural correlates of these strategies. Following piloting with a separate sample of young adults, cognitive and achievement tests and assessments of problem-solving strategies will be administered to 100 adolescents, 50 of whom will be selected on the basis of their problem-solving strategies to complete in-magnet problem-solving tasks. Adolescents with more advanced problem-solving strategies (characterized by reliance on retrieval of solutions) are hypothesized to display more intact cognitive profiles and higher levels of mathematics achievement than those using less advanced approaches (characterized by more effortful multi-step procedures). Adolescents using more advanced strategies are also hypothesized to show patterns of brain activation in regions specialized for efficient mathematics processing, such as the hippocampus and posterior parietal region, as compared to regions that are less specialized such as the prefrontal area. These participants are also expected to display less pronounced changes in activation patterns with increased problem difficulty, suggestive of greater neural efficiency in mathematics problem-solving and less reliance on compensatory systems. The project will include novel statistical methods for cognitive modeling and an exciting new approach to assess brain functioning during math problem solving. This research will provide insight into the cognitive skills and neural processes associated with successful strategy adoption for problem solving, with an emphasis on neural capacity, efficiency, and compensation.
由凯斯西储大学的一组研究人员领导的这项研究的主要目标是进一步了解数学学习的神经和认知基础。重点将是青少年使用的数学解决问题的策略,以及这些策略是如何被采用和改变的问题变得更加系统的困难。该项目将研究这些策略与数学相关的认知技能,数学成绩测试分数以及青少年在参与这些策略时所显示的大脑激活模式之间的关联。解决问题的策略是感兴趣的,因为它们关系到更高层次的数学成绩和见解,他们可以提供到数学学习中的个体差异的基础。该项目的长期目标是发现新的方法来调整数学学习策略,以适应个人的认知和神经能力。该项目还将采取创新方法,收集有关数学任务期间神经功能的信息,有可能影响未来对参与学习和行为的大脑系统的研究。该项目由EHR(教育和人力资源董事会)核心研究计划资助,该计划支持推进STEM(科学,技术,工程和数学)学习文献的基础研究。参与者将是14-16岁的青少年,他们之前参加了一项纵向研究,研究早产与足月分娩对学校前3年学业进步的影响。措施将包括空间技能,注意力,执行功能,如工作记忆,数感和数学成绩的测试;不同难度的心算和分数问题,旨在揭示个体差异的解决问题的策略;和功能性磁共振成像(fMRI)程序,以检查这些策略的神经相关性。在对年轻成年人进行单独抽样试点后,将对100名青少年进行认知和成绩测试以及解决问题策略评估,根据他们的解决问题策略选择其中50人完成磁铁内解决问题任务。假设具有更先进的解决问题的策略(其特征在于依赖于检索的解决方案)的青少年显示更完整的认知配置文件和更高水平的数学成绩比那些使用较不先进的方法(其特征在于更努力的多步骤程序)。使用更高级策略的青少年也被假设为在专门用于有效数学处理的区域(如海马体和后顶叶区域)中显示大脑激活模式,而不是像前额区那样专门化程度较低的区域。这些参与者也预计显示不太明显的变化,在激活模式增加的问题难度,暗示更大的神经效率在数学问题解决和补偿系统的依赖较少。该项目将包括用于认知建模的新颖统计方法和一种令人兴奋的新方法,以评估数学问题解决过程中的大脑功能。这项研究将深入了解与成功采用解决问题的策略相关的认知技能和神经过程,重点是神经能力,效率和补偿。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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Curtis Tatsuoka其他文献
eP366: A comprehensive study of E200K genetic Creutzfeldt Jakob disease cases; effects of codon 129 polymorphism
- DOI:
10.1016/j.gim.2022.01.401 - 发表时间:
2022-03-01 - 期刊:
- 影响因子:
- 作者:
Melissa Keinath;Ignazio Cali;Megan Piazza;Mark Cohen;Curtis Tatsuoka;Thomas Prior;Brian Appleby;Shashirekha Shetty - 通讯作者:
Shashirekha Shetty
ASO Visual Abstract: Normal CEA Levels After Neoadjuvant Chemotherapy and Cytoreduction with Hyperthermic Intraperitoneal Chemoperfusion Predict Improved Survival from Colorectal Peritoneal Metastases
- DOI:
10.1245/s10434-024-15065-7 - 发表时间:
2024-02-14 - 期刊:
- 影响因子:3.500
- 作者:
Michael M. Wach;Geoffrey Nunns;Ahmed Hamed;Joshua Derby;Mark Jelinek;Curtis Tatsuoka;Matthew P. Holtzman;Amer H. Zureikat;David L. Bartlett;Steven A. Ahrendt;James F. Pingpank;M. Haroon A. Choudry;Melanie Ongchin - 通讯作者:
Melanie Ongchin
Toward AI-Assisted Clinical Assessment for Patients with Multiple Myeloma: Feature Selection for Large Language Models
- DOI:
10.1182/blood-2023-172710 - 发表时间:
2023-11-02 - 期刊:
- 影响因子:
- 作者:
Ehsan Malek;Gi-Ming Wang;Anant Madabhushi;Jennifer Cullen;Curtis Tatsuoka;James J. Driscoll - 通讯作者:
James J. Driscoll
PLATELET AND MONOCYTE ACTIVATION AFTER TRANSCATHETER AORTIC VALVE REPLACEMENT (POTENT-TAVR): A RANDOMIZED CONTROLLED TRIAL OF TICAGRELOR VERSUS CLOPIDOGREL BEFORE TAVR
- DOI:
10.1016/s0735-1097(20)32097-0 - 发表时间:
2020-03-24 - 期刊:
- 影响因子:
- 作者:
David Alexander Zidar;Sadeer Al-Kindi;Anthony Main;Michael Osnard;Nour Tashtish;Sahil Parikh;Nicholas Funderburg;Steven Juchnowski;Christopher Longenecker;Trevor Jenkins;Christopher Nmai;Curtis Tatsuoka;Marco Costa;Eugene Blackstone;Michael Lederman;Guilherme Attizzani;Daniel I. Simon - 通讯作者:
Daniel I. Simon
P-137 Optimizing Feature Selection for Large Language Models in AI-Assisted Clinical Assessment of Multiple Myeloma
- DOI:
10.1016/s2152-2650(24)02040-8 - 发表时间:
2024-09-01 - 期刊:
- 影响因子:
- 作者:
Ehsan Malek;Gi-Ming Wang;Anant Madabhushi;Jennifer Cullen;Curtis Tatsuoka;James J. James J. Driscoll - 通讯作者:
James J. James J. Driscoll
Curtis Tatsuoka的其他文献
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{{ truncateString('Curtis Tatsuoka', 18)}}的其他基金
Collaborative Research: EAGER: Automating CI Configuration Troubleshooting with Bayesian Group Testing
协作研究:EAGER:使用贝叶斯组测试自动化 CI 配置故障排除
- 批准号:
2333326 - 财政年份:2023
- 资助金额:
$ 149.96万 - 项目类别:
Standard Grant
Cognitive Diagnosis with Multinomial Response Distributions
多项响应分布的认知诊断
- 批准号:
9810202 - 财政年份:1998
- 资助金额:
$ 149.96万 - 项目类别:
Standard Grant
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Neural Process模型的多样化高保真技术研究
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- 资助金额:30 万元
- 项目类别:青年科学基金项目
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