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Short‐time windows of correlation between large‐scale functional brain networks predict vigilance intraindividually and interindividually

机译:大型功能性大脑网络之间的短期相关窗口可分别和分别预测警惕

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摘要

A better understanding of how behavioral performance emerges from interacting brain systems may come from analysis of functional networks using functional magnetic resonance imaging. Recent studies comparing such networks with human behavior have begun to identify these relationships, but few have used a time scale small enough to relate their findings to variation within a single individual's behavior. In the present experiment we examined the relationship between a psychomotor vigilance task and the interacting default mode and task positive networks. Two time‐localized comparative metrics were calculated: difference between the two networks' signals at various time points around each instance of the stimulus (peristimulus times) and correlation within a 12.3‐s window centered at each peristimulus time. Correlation between networks was also calculated within entire resting‐state functional imaging runs from the same individuals. These metrics were compared with response speed on both an intraindividual and an interindividual basis. In most cases, a greater difference or more anticorrelation between networks was significantly related to faster performance. While interindividual analysis showed this result generally, using intraindividual analysis it was isolated to peristimulus times 4 to 8 s before the detected target. Within that peristimulus time span, the effect was stronger for individuals who tended to have faster response times. These results suggest that the relationship between functional networks and behavior can be better understood by using shorter time windows and also by considering both intraindividual and interindividual variability. . © 2012 Wiley Periodicals, Inc.
机译:通过使用功能磁共振成像对功能网络进行分析,可以更好地理解交互大脑系统如何表现出行为表现。最近将此类网络与人类行为进行比较的研究已开始确定这些关系,但是很少有人使用足够小的时间尺度将其发现与单个人的行为变化相关联。在本实验中,我们研究了心理运动警惕任务与交互默认模式和任务阳性网络之间的关系。计算了两个时间局部的比较度量:两个网络信号在每个刺激实例周围的不同时间点(蠕动时间)之间的差异,以及在每个刺激周围时间为中心的12.3秒窗口内的相关性。在同一个人的整个静止状态功能成像过程中,还计算了网络之间的相关性。在个体和个体之间将这些指标与响应速度进行了比较。在大多数情况下,网络之间的更大差异或更多反相关与更快的性能显着相关。尽管个体间分析通常显示出该结果,但使用个体内分析将其隔离到被检测目标之前4到8 s的周围刺激时间。在那个刺激时间范围内,对于倾向于具有更快响应时间的个体,效果更强。这些结果表明,通过使用较短的时间窗口以及同时考虑个体内部和个体之间的可变性,可以更好地理解功能网络与行为之间的关系。 。 ©2012 Wiley Periodicals,Inc.

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