Computational Models in Electroencephalography.
Computational Models in Electroencephalography.
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DOI：
10.1007/s10548-021-00828-2
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发表时间：
2022-01
期刊：
影响因子：
2.7
通讯作者：
Franceschiello B
中科院分区：
文献类型：
--
作者：
Glomb K;Cabral J;Cattani A;Mazzoni A;Raj A;Franceschiello B
计算模型位于基础神经科学和医疗保健应用的交叉点，因为它们允许研究人员在计算机中测试假设并预测在现实中很难测试的实验和交互的结果。然而，神经科学和心理学不同领域的研究人员对“计算模型”的含义有多种不同的理解，阻碍了沟通和协作。在这篇综述中，我们指出了脑电图 (EEG) 计算建模的最新技术，并概述了如何使用这些模型来整合电生理学、网络级模型和行为的发现。一方面，计算模型用于研究产生大脑活动的机制，例如用脑电图测量，例如在不同频带和/或不同空间拓扑下短暂出现的振荡。另一方面，计算模型用于在计算机中设计实验和测试假设。脑电图计算模型的最终目的是全面了解脑电图信号背后的机制。这对于准确解释脑电图测量至关重要，最终可能有助于开发新颖的临床应用。
Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by “computational model” is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.
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影响因子：
5.7
作者：
Abdelnour F;Dayan M;Devinsky O;Thesen T;Raj A
通讯作者：
Raj A
DOI：
10.1098/rstb.2000.0769
发表时间：
2001-03-29
影响因子：
6.3
作者：
Bressloff, PC;Cowan, JD;Wiener, MC
通讯作者：
Wiener, MC
影响因子：
3.7
作者：
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影响因子：
2.4
作者：
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Liley, DTJ
影响因子：
5.7
作者：
Abbas, Kausar;Amico, Enrico;Goni, Joaquin
通讯作者：
Goni, Joaquin