Multi-scale brain network mechanisms of working memory and short-term memory

工作记忆和短期记忆的多尺度脑网络机制

• 批准号: MR/V013769/1
• 负责人: Satu Palva
• 金额: $ 84.7万
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV013769%2F1
• 关键词: Multi; scale; brain; network; mechanisms

Short-term memory (STM) and working memory (WM) are core cognitive processes with a limited capacity varying across individuals and from trial-to-trial. STM refers to online retention of sensory information and working memory (WM) to the manipulation of that information. STM and WM are comprised of multiple components e.g. sustained maintenance of sensory information, and its attentional and executive control. Neuronal processing underlying these functions is parallel and distributed across brain anatomy into functionally modular cortical networks, where neuronal activity is characterized by neuronal oscillations concurrently in many frequencies. The key challenge is to resolve what mechanisms integrates this both anatomically and temporally distributed processing into subjectively coherent STM and WM, differentiate these two memory functions and limit their capacity. Despite the obvious relevance, the systems-level neuronal substrates coordinating and integrating this distributed processing and setting the capacity limits of STM and WM are poorly understood. In this project, we will use state-of-the art multimodal neuroimaging with combined magneto/ electroencephalography (M/EEG) and combined transcranial magnetic stimulation (TMS)-EEG and exploit cutting-edge analyses of complex brain networks to establish the systems-level neuronal mechanisms underlying the maintenance of information in STM and WM in healthy human subjects. Our overarching goal is to reveal the multi-scale brain oscillatory network mechanisms of STM and WM. Neuronal phase synchronization (PS) within frequency bands has been proposed to coordinate anatomically distributed processing. We will use combined M/EEG with advanced source-connectivity analyses and network theory pioneered by us to identify cortex-wide PS networks and their role in STM and WM. Our first goal is to use cutting-edge source connectivity analysis to establish that multi-scale large-scale network synchronization could be an integrative systems-level mechanism for coordinating processing across anatomically distributed neuronal circuits in STM and WM and resolve whether complexity of these oscillatory network interactions differentiate STM and WM. Within-frequency PS cannot coordinate neuronal processing that is also distributed across multiple oscillatory networks at distinct frequencies. We have proposed and provided initial evidence for that synchronization across oscillatory frequencies, a.k.a. cross-frequency synchronization (CFS), serves integration across oscillations and across cortical hierarchies. Our second goal is to establish that neuronal processing distributed across frequencies during STM and WM are integrated via CFS. We propose that by connecting PS networks across oscillatory frequencies, CFS could underlie the integration of distinct cognitive processes. As M/EEG yield only correlative evidence for the functional significance of synchronization coordinating behavioral performance, we will obtain causal evidence with combined TMS-EEG, the usage of which our team has pioneered. Employing unique M/EEG network analyses guided rhythmic TMS (rhTMS) to stimulate network hubs and to entrain synchronization, we aim to modulate memory performance. This will thus enable resolving the mechanistic role of multi-scale network synchronization in coordinating STM and WM performance. This project will discover how distributed neuronal processing is integrated into subjectively coherent STM and WM. This will further yield first-time causal evidence for significance of network synchronization in human memory performance. This project has a groundbreaking potential to bridge the gap between neurophysiology and psychology. As STM and WM deficits characterize many brain diseases, this work will give novel insights into the disease mechanisms and pave the way for novel treatments for memory disorders.

短时记忆（STM）和工作记忆（WM）是核心的认知过程，其能力有限，个体和试验之间存在差异。短时记忆指的是感觉信息的在线保持，工作记忆指的是对这些信息的操纵。短时记忆和工作记忆是由多个部分组成的，如感觉信息的持续保持、注意和执行控制。这些功能背后的神经元处理是平行的，并分布在大脑解剖结构中的功能模块化皮层网络中，其中神经元活动的特征在于同时在许多频率下的神经元振荡。关键的挑战是要解决什么机制整合这两个解剖和时间分布的加工到主观连贯的短时记忆和工作记忆，区分这两个记忆功能，并限制其容量。尽管有明显的相关性，系统水平的神经基板协调和整合这种分布式处理和设置的STM和WM的容量限制知之甚少。在这个项目中，我们将使用最先进的多模态神经成像与组合磁/脑电图（M/EEG）和组合经颅磁刺激（TMS）-EEG，并利用复杂的大脑网络的尖端分析，以建立系统水平的神经元机制，在健康的人类受试者中维持STM和WM中的信息。我们的首要目标是揭示短时记忆和工作记忆的多尺度脑振荡网络机制。频带内的神经元相位同步（PS）已被提出来协调解剖分布的处理。我们将结合M/EEG与先进的源连接分析和网络理论，我们开创了识别皮层范围的PS网络和他们的作用，在STM和WM。我们的第一个目标是使用尖端的源连接分析，以建立多尺度的大规模网络同步可能是一个综合的系统级机制，协调处理跨解剖分布的神经元回路在STM和WM，并解决这些振荡网络相互作用的复杂性是否区分STM和WM。频率内PS不能协调也分布在不同频率的多个振荡网络中的神经元处理。我们已经提出并提供了初步的证据，同步振荡频率，又名。交叉频率同步（CFS），服务于跨振荡和跨皮层层次的整合。我们的第二个目标是建立跨频率分布的神经元加工过程中STM和WM通过CFS集成。我们认为，通过连接PS网络的振荡频率，CFS可以根据不同的认知过程的整合。由于M/EEG只产生同步协调行为表现的功能意义的相关证据，我们将获得与TMS-EEG相结合的因果关系证据，我们的团队率先使用了这种方法。采用独特的M/EEG网络分析引导的节奏TMS（rhTMS）刺激网络枢纽和夹带同步，我们的目标是调节记忆性能。因此，这将能够解决多尺度网络同步在协调STM和WM性能中的机械作用。这个项目将发现分布式神经元处理如何整合到主观连贯的STM和WM中。这将进一步为网络同步在人类记忆表现中的重要性提供首次因果证据。这个项目具有突破性的潜力，可以弥合神经生理学和心理学之间的差距。由于STM和WM缺陷是许多脑疾病的特征，这项工作将为疾病机制提供新的见解，并为记忆障碍的新治疗方法铺平道路。

项目成果

Synchronization networks reflect the contents of visual working memory

同步网络反映视觉工作记忆的内容

• DOI: 10.21203/rs.3.rs-3853906/v1
• 发表时间: 2024
• 作者: Haque H