Classifying fMRI-derived resting-state connectivity patterns according to their daily rhythmicity
Classifying fMRI-derived resting-state connectivity patterns according to their daily rhythmicity
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DOI：
10.1016/j.neuroimage.2012.08.010
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发表时间：
2013-05-01
期刊：
影响因子：
5.7
通讯作者：
Meindl, Thomas
中科院分区：
文献类型：
--
作者：
Blautzik, Janusch;Vetter, Celine;Meindl, Thomas
绝大多数的生物功能表现为一天24小时的节律波动。我们通过评估8小时(4次)内20种连接模式的时间进程，研究了15名受试者通过功能磁共振成像(FMRI)获得的静息状态数据的每日调制程度。对于每个受试者，我们确定了描述个体昼夜节律与当地时间之间关系的时型。因此，我们可以分析控制内部时间的连接模式的每日时间进程。此外，由于参与者的扫描时间是错开的，这是他们的时型函数，我们防止了睡眠不足，并保持了受试者的清醒时间恒定。在每个会话中，每个连接模式中的单个功能连接性被定义为通过平均z值测量的连接强度，以及由激活的体素数量表示的空间范围。高节奏的连接模式包括默认模式网络(DMN)的两个子系统和延伸到感觉运动区的网络。我们得出结论，日常调制的程度在不同fMRI产生的静息状态连接模式中有很大的不同，从高节奏到稳定不等。在解释功能磁共振研究的结果时，这一发现应该得到考虑。(C)2013 Elsevier Inc.保留所有权利。
The vast majority of biological functions express rhythmic fluctuations across the 24-hour day. We investigated the degree of daily modulation across fMRI (functional Magnetic Resonance Imaging) derived resting-state data in 15 subjects by evaluating the time courses of 20 connectivity patterns over 8 h (4 sessions).For each subject, we determined the chronotype, which describes the relationship between the individual circadian rhythm and the local time. We could therefore analyze the daily time course of the connectivity patterns controlling for internal time. Furthermore, as the participants' scan times were staggered as a function of their chronotype, we prevented sleep deprivation and kept time awake constant across subjects. Individual functional connectivity within each connectivity pattern was defined at each session as connectivity strength measured by a mean z-value and, in addition, as the spatial extent expressed by the number of activated voxels.Highly rhythmic connectivity patterns included two sub-systems of the Default-Mode Network (DMN) and a network extending over sensori-motor regions. The network characterized as the most stable across the day is mainly associated with processing of executive control.We conclude that the degree of daily modulation largely varies across fMRI derived resting-state connectivity patterns, ranging from highly rhythmic to stable. This finding should be considered when interpreting results from fMRI studies. (C) 2013 Elsevier Inc. All rights reserved.