Huang Ruey-Song, Wang Mengxiao, Leong Teng Ieng, Lei Ut Meng, Sereno Martin I, Li Defeng, Lei Victoria Lai Cheng
Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China.
Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.
bioRxiv. 2025 Aug 1:2025.07.29.667380. doi: 10.1101/2025.07.29.667380.
This study investigates the intricate interplay between the task-positive network and the default mode network (DMN) during transitions between overt language tasks and brief resting periods. While previous research suggests that these networks are not invariably anticorrelated, the precise timing of transitions has remained elusive. We employed rapid phase-encoded fMRI to decode brain dynamics with ultimate precision, capturing these transitions in real time. By utilizing phasor diagrams to represent the oscillatory activities, we examined the amplitudes and phases of hemodynamic fluctuations within the language network and DMN. Our findings align with existing empirical and theoretical perspectives on DMN functions and cognitive task performance, affirming the validity of our approach. We identified heterogeneous micro resting states interwoven with periods of overt speech production. Notably, various core regions of the DMN exhibited task-dependent amplitude and phase modulations, with activation strength and delay rising in line with increasing task complexity, ranging from comprehension to immediate and delayed speech production. This study sheds light on the dynamic engagement of the DMN during overt speech production, providing precise timing data of transitions between the DMN and language network. It demonstrates that rapid phase-encoded fMRI and phasor diagrams are powerful tools for measuring the switching between active tasks and micro resting states with subsecond accuracy, while also elucidating task load-dependent changes in the DMN. By accurately measuring the timing of these transitions, we gain insights into cognitive flexibility, attention, and the efficiency of information processing.
本研究调查了在明显的语言任务和短暂休息期之间转换时,任务积极网络与默认模式网络(DMN)之间复杂的相互作用。虽然先前的研究表明这些网络并非总是反相关,但转换的精确时间仍不清楚。我们采用快速相位编码功能磁共振成像(fMRI)以极高的精度解码脑动力学,实时捕捉这些转换。通过利用相量图来表示振荡活动,我们检查了语言网络和DMN内血液动力学波动的幅度和相位。我们的研究结果与关于DMN功能和认知任务表现的现有实证和理论观点一致,证实了我们方法的有效性。我们识别出与明显言语产生期交织在一起的异质性微休息状态。值得注意的是,DMN的各个核心区域表现出与任务相关的幅度和相位调制,激活强度和延迟随着任务复杂性的增加而上升,范围从理解到即时和延迟言语产生。本研究揭示了DMN在明显言语产生过程中的动态参与,提供了DMN与语言网络之间转换的精确时间数据。它表明快速相位编码fMRI和相量图是用于以亚秒级精度测量活跃任务与微休息状态之间切换的强大工具,同时还阐明了DMN中与任务负荷相关的变化。通过准确测量这些转换的时间,我们深入了解了认知灵活性、注意力和信息处理效率。