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基于脑电图的n-back任务期间ACT-R模块之间的皮质水平连通性。

Cortex level connectivity between ACT-R modules during EEG-based n-back task.

作者信息

Das Chakladar Debashis

机构信息

Machine Learning Group, Luleå University of Technology, Luleå, Sweden.

出版信息

Cogn Neurodyn. 2024 Dec;18(6):4033-4045. doi: 10.1007/s11571-024-10177-y. Epub 2024 Oct 21.

Abstract

Finding the synchronization between Electroencephalography (EEG) and human cognition is an essential aspect of cognitive neuroscience. Adaptive Control of Thought-Rational (ACT-R) is a widely used cognitive architecture that defines the cognitive and perceptual operations of the human mind. This study combines the ACT-R and EEG-based cortex-level connectivity to highlight the relationship between ACT-R modules during the EEG-based -back task (for validating working memory performance). Initially, the source localization method is performed on the EEG signal, and the mapping between ACT-R modules and corresponding brain scouts (on the cortex surface) is performed. Once the brain scouts are identified for ACT-R modules, then those scouts are called ACT-R scouts. The linear (Granger Causality: GC) and non-linear effective connectivity (Multivariate Transfer Entropy: MTE) methods are applied over the scouts' time series data. From the GC and MTE analysis, for all -back tasks, information flow is observed from the visual-to-imaginal ACT-R scout for storing the visual stimuli (i.e., input letter) in short-term memory. For 2 and 3-back tasks, causal flow exists from imaginal to retrieval ACT-R scout and vice-versa. Causal flow from procedural to the imaginal ACT-R scout is also observed for all workload levels to execute the set of productions. Identifying the relationship among ACT-R modules through scout-level connectivity in the cortical surface facilitates the effects of human cognition in terms of brain dynamics.

摘要

找到脑电图(EEG)与人类认知之间的同步性是认知神经科学的一个重要方面。思维自适应控制-理性(ACT-R)是一种广泛使用的认知架构,它定义了人类思维的认知和感知操作。本研究将ACT-R与基于EEG的皮层水平连通性相结合,以突出基于EEG的回退任务(用于验证工作记忆表现)期间ACT-R模块之间的关系。首先,对EEG信号执行源定位方法,并执行ACT-R模块与相应脑区(在皮层表面)之间的映射。一旦为ACT-R模块确定了脑区,那么这些脑区就被称为ACT-R脑区。将线性(格兰杰因果关系:GC)和非线性有效连通性(多变量转移熵:MTE)方法应用于脑区的时间序列数据。从GC和MTE分析来看,对于所有回退任务,观察到信息流从视觉ACT-R脑区流向想象ACT-R脑区,以便将视觉刺激(即输入字母)存储在短期记忆中。对于2-back和3-back任务,则存在从想象ACT-R脑区到检索ACT-R脑区的因果流,反之亦然。在所有工作负载水平下,也观察到从程序ACT-R脑区到想象ACT-R脑区的因果流,以执行一组生产活动。通过皮层表面脑区水平的连通性来识别ACT-R模块之间的关系,有助于从脑动力学角度理解人类认知的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a23/11655808/6402a94f175c/11571_2024_10177_Fig1_HTML.jpg

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