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基于虚拟现实的被动感觉P300网络的神经元相关性

Neuronal correlates of a virtual-reality-based passive sensory P300 network.

作者信息

Chen Chun-Chuan, Syue Kai-Syun, Li Kai-Chiun, Yeh Shih-Ching

机构信息

Graduate Institute of Biomedical Engineering, National Central University, Jhongli city, Taoyuan County, Taiwan.

Department of Computer Science and Information Engineering, National Central University, Jhongli city, Taoyuan County, Taiwan.

出版信息

PLoS One. 2014 Nov 17;9(11):e112228. doi: 10.1371/journal.pone.0112228. eCollection 2014.

Abstract

P300, a positive event-related potential (ERP) evoked at around 300 ms after stimulus, can be elicited using an active or passive oddball paradigm. Active P300 requires a person's intentional response, whereas passive P300 does not require an intentional response. Passive P300 has been used in incommunicative patients for consciousness detection and brain computer interface. Active and passive P300 differ in amplitude, but not in latency or scalp distribution. However, no study has addressed the mechanism underlying the production of passive P300. In particular, it remains unclear whether the passive P300 shares an identical active P300 generating network architecture when no response is required. This study aims to explore the hierarchical network of passive sensory P300 production using dynamic causal modelling (DCM) for ERP and a novel virtual reality (VR)-based passive oddball paradigm. Moreover, we investigated the causal relationship of this passive P300 network and the changes in connection strength to address the possible functional roles. A classical ERP analysis was performed to verify that the proposed VR-based game can reliably elicit passive P300. The DCM results suggested that the passive and active P300 share the same parietal-frontal neural network for attentional control and, underlying the passive network, the feed-forward modulation is stronger than the feed-back one. The functional role of this forward modulation may indicate the delivery of sensory information, automatic detection of differences, and stimulus-driven attentional processes involved in performing this passive task. To our best knowledge, this is the first study to address the passive P300 network. The results of this study may provide a reference for future clinical studies on addressing the network alternations under pathological states of incommunicative patients. However, caution is required when comparing patients' analytic results with this study. For example, the task presented here is not applicable to incommunicative patients.

摘要

P300是一种在刺激后约300毫秒诱发的正性事件相关电位(ERP),可通过主动或被动的oddball范式引出。主动P300需要个体做出有意反应,而被动P300则不需要有意反应。被动P300已被用于无交流能力患者的意识检测和脑机接口。主动和被动P300在波幅上存在差异,但在潜伏期或头皮分布上无差异。然而,尚无研究探讨被动P300产生的潜在机制。特别是,当不需要反应时,被动P300是否与主动P300共享相同的产生网络架构仍不清楚。本研究旨在使用ERP的动态因果模型(DCM)和基于虚拟现实(VR)的新型被动oddball范式,探索被动感觉P300产生的层次网络。此外,我们研究了该被动P300网络的因果关系以及连接强度的变化,以探讨其可能的功能作用。进行了经典的ERP分析,以验证所提出的基于VR的游戏能否可靠地引出被动P300。DCM结果表明,被动和主动P300共享相同的用于注意力控制的顶叶-额叶神经网络,并且在被动网络中,前馈调制强于反馈调制。这种前向调制的功能作用可能表明感觉信息的传递、差异的自动检测以及执行该被动任务时涉及的刺激驱动的注意力过程。据我们所知,这是第一项研究被动P300网络的研究。本研究结果可能为未来关于无交流能力患者病理状态下网络改变的临床研究提供参考。然而,将患者的分析结果与本研究进行比较时需要谨慎。例如,这里呈现的任务不适用于无交流能力患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9c8/4234463/774f7a6c85b5/pone.0112228.g001.jpg

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