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作为认知计算的瞬态振荡:分析、建模与功能。

Transient oscillations as computations for cognition: Analysis, modeling and function.

机构信息

Institute for Neural Computation, Faculty of Computer Science, Ruhr-University Bochum, Germany.

Neural Basis of Learning, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Germany.

出版信息

Curr Opin Neurobiol. 2023 Dec;83:102796. doi: 10.1016/j.conb.2023.102796. Epub 2023 Oct 6.

Abstract

Our view of neural oscillations is currently changing. The dominant picture of sustained oscillations is now often replaced by transient oscillations occurring in bursts. This phenomenon seems to be quite comprehensive, as it has been reported for different oscillation frequencies, including the theta, beta, and gamma bands, as well as cortical and subcortical regions in a variety of cognitive tasks and species. Here we review recent developments in their analysis, computational modeling, and functional roles. For the analysis of transient oscillations methods using lagged coherence and Hidden Markov Models have been developed and applied in recent studies to ascertain their transient nature and study their contribution to cognitive functions. Furthermore, computational models have been developed that account for their stochastic nature, which poses interesting functional constraints. Finally, as transient oscillations have been observed across many species, they are likely of functional significance and we consider challenges in characterizing their function.

摘要

我们对神经振荡的看法正在发生变化。持续振荡的主导形象现在经常被突发的瞬态振荡所取代。这种现象似乎非常普遍,因为它已经在不同的振荡频率下得到了报道,包括θ、β和γ波段,以及各种认知任务和物种中的皮质和皮质下区域。在这里,我们回顾了它们的分析、计算模型和功能作用的最新进展。对于瞬态振荡的分析,使用滞后相干性和隐马尔可夫模型的方法已经在最近的研究中得到了发展和应用,以确定它们的瞬态性质,并研究它们对认知功能的贡献。此外,还开发了计算模型来解释它们的随机性质,这对功能提出了有趣的限制。最后,由于瞬态振荡已经在许多物种中被观察到,它们可能具有功能意义,我们考虑在描述它们的功能方面所面临的挑战。

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