What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?
What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?
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DOI：
10.3390/e22111262
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发表时间：
2020-11-06
期刊：
影响因子：
--
通讯作者：
Makeig S
中科院分区：
文献类型：
--
作者：
Martínez-Cancino R;Delorme A;Wagner J;Kreutz-Delgado K;Sotero RC;Makeig S
将高频皮层场活动的振幅调制锁定到较慢脑节律的相位变化，称为相位振幅耦合（PAC）。对这种现象的研究在神经科学中获得了越来越多的关注，因为有几份关于它在人类正常和病理性大脑过程中以及不同哺乳动物物种中出现的报告。这导致的建议，PAC可能是一个内在的大脑过程，促进大脑跨不同时空尺度的区域间通信。已经提出了几种方法来测量PAC过程，但这些方法很少能够详细研究其时间过程。似乎没有研究报告的PAC动态的细节，包括其可能的方向延迟特性。在这里，我们研究和表征使用一种新的信息理论的措施，可以解决这个限制：本地转移熵。我们使用模拟和实际颅内脑电图数据。在这两种情况下，我们观察到的初始迹象表明，本地传输熵可以用来检测的发病和偏移的调制过程中透露的互信息估计相位振幅耦合（MIPAC）。我们审查我们的研究结果的背景下，目前的理论PAC在脑电活动，并讨论了技术问题，必须解决本地传输熵更广泛地应用于PAC分析。目前的工作为进一步使用局部传递熵估计PAC过程动态奠定了基础，并扩展和补充了我们以前的工作，使用局部互信息计算PAC（MIPAC）。
Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristic. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data. In both cases, we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information estimated phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis. The current work sets the foundations for further use of local transfer entropy for estimating PAC process dynamics, and extends and complements our previous work on using local mutual information to compute PAC (MIPAC).
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影响因子：
3
作者：
Dvorak, Dino;Fenton, Andre A.
通讯作者：
Fenton, Andre A.
影响因子：
5.7
作者：
Florin, Esther;Gross, Joachim;Timmermann, Lars
通讯作者：
Timmermann, Lars
影响因子：
1
作者：
Antos, A;Kontoyiannis, I
通讯作者：
Kontoyiannis, I
影响因子：
4.3
作者：
Dimitriadis SI;Laskaris NA;Bitzidou MP;Tarnanas I;Tsolaki MN
通讯作者：
Tsolaki MN
DOI：
10.1073/pnas.1214546110
发表时间：
2013-03-19
影响因子：
11.1
作者：
de Hemptinne, Coralie;Ryapolova-Webb, Elena S.;Starr, Philip A.
通讯作者：
Starr, Philip A.