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功能磁共振成像数据的定向传递函数分析以研究网络动力学。

Directed transfer function analysis of fMRI data to investigate network dynamics.

作者信息

Deshpande Gopikrishna, LaConte Stephen, Peltier Scott, Hu Xiaoping

机构信息

Dept. of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:671-4. doi: 10.1109/IEMBS.2006.259969.

Abstract

In this work, we have adapted the directed transfer function (DTF) to fMRI for the analysis of cortical network dynamics. While modern fMRI sequences are capable of sampling at second or sub-second rates, the underlying hemodynamic response limits the true temporal resolution to the order of 6-12 seconds. Therefore, DTF analysis of fMRI is appropriate for characterizing dynamics in brain response which evolves more slowly than the fMRI response, such as those during learning, fatigue and habituation. In such cases, the response to repeated trials will change with time and a summary measure from each trial can be used as input to the DTF analysis because these summary measures are of appropriate sampling rates and are not affected by the sluggishness of the hemodynamic response. As an example, we investigated the dynamic effects of muscle fatigue on the motor network. Specifically, DTF was used as a multivariate measure of the strength and direction of information flow between the various nodes of the network. We found that the primary motor area had a causal influence on the supplementary motor area, pre-motor area and cerebellum, and this influence initially increased with time and diminished towards the end of the experiment, probably as a result of fatigue.

摘要

在这项工作中,我们将定向传递函数(DTF)应用于功能磁共振成像(fMRI),以分析皮质网络动力学。虽然现代fMRI序列能够以秒或亚秒级速率进行采样,但潜在的血液动力学响应将真正的时间分辨率限制在6至12秒的量级。因此,fMRI的DTF分析适用于表征大脑响应中的动力学,这种动力学的演变比fMRI响应更慢,例如学习、疲劳和习惯化过程中的动力学。在这种情况下,对重复试验的响应会随时间变化,并且每次试验的汇总测量值可作为DTF分析的输入,因为这些汇总测量值具有合适的采样速率,且不受血液动力学响应迟缓的影响。例如,我们研究了肌肉疲劳对运动网络的动态影响。具体而言,DTF被用作网络各个节点之间信息流强度和方向的多变量测量指标。我们发现,初级运动区对辅助运动区、运动前区和小脑有因果影响,并且这种影响最初随时间增加,在实验接近尾声时减弱,这可能是疲劳的结果。

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