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通过血氧水平依赖变压器在N-回溯工作记忆任务中评估认知功能和脑活动模式

Evaluating Cognitive Function and Brain Activity Patterns via Blood Oxygen Level-Dependent Transformer in N-Back Working Memory Tasks.

作者信息

Zhang Zhenming, Chen Yaojing, Men Aidong, Jiang Zhuqing

机构信息

School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.

出版信息

Brain Sci. 2025 Mar 5;15(3):277. doi: 10.3390/brainsci15030277.

Abstract

(1) Background: Working memory, which involves temporary storage, information processing, and regulating attention resources, is a fundamental cognitive process and constitutes a significant component of neuroscience research. This study aimed to evaluate brain activation patterns by analyzing functional magnetic resonance imaging (fMRI) time-series data collected during a designed N-back working memory task with varying cognitive demands. (2) Methods: We utilized a novel transformer model, blood oxygen level-dependent transformer (BolT), to extract the activation level features of brain regions in the cognitive process, thereby obtaining the influence weights of regions of interest (ROIs) on the corresponding tasks. (3) Results: Compared with previous studies, our work reached similar conclusions in major brain region performance and provides a more precise analysis for identifying brain activation patterns. For each type of working memory task, we selected the top 5 percent of the most influential ROIs and conducted a comprehensive analysis and discussion. Additionally, we explored the effect of prior knowledge conditions on the performance of different tasks in the same period and the same tasks at different times. (4) Conclusions: The comparison results reflect the brain's adaptive strategies and dependencies in coping with different levels of cognitive demands and the stability optimization of the brain's cognitive processing. This study introduces innovative methodologies for understanding brain function and cognitive processes, highlighting the potential of transformer in cognitive neuroscience. Its findings offer new insights into brain activity patterns associated with working memory, contributing to the broader landscape of neuroscience research.

摘要

(1) 背景:工作记忆涉及临时存储、信息处理和注意力资源调节,是一种基本的认知过程,也是神经科学研究的重要组成部分。本研究旨在通过分析在具有不同认知需求的设计好的n-back工作记忆任务中收集的功能磁共振成像(fMRI)时间序列数据,来评估大脑激活模式。(2) 方法:我们利用一种新型的变压器模型,即血氧水平依赖变压器(BolT),来提取认知过程中脑区的激活水平特征,从而获得感兴趣区域(ROI)对相应任务的影响权重。(3) 结果:与以往研究相比,我们的工作在主要脑区表现上得出了相似的结论,并为识别大脑激活模式提供了更精确的分析。对于每种类型的工作记忆任务,我们选择了最具影响力的ROI中排名前5%的区域进行全面分析和讨论。此外,我们还探讨了先验知识条件对同一时期不同任务以及不同时间相同任务表现的影响。(4) 结论:比较结果反映了大脑在应对不同水平认知需求时的适应性策略和依赖性,以及大脑认知处理的稳定性优化。本研究引入了理解脑功能和认知过程的创新方法,突出了变压器模型在认知神经科学中的潜力。其研究结果为与工作记忆相关的大脑活动模式提供了新的见解,为神经科学研究的更广阔领域做出了贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11940435/acd872f296c7/brainsci-15-00277-g001.jpg

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