Methodological considerations for studying neural oscillations.
Methodological considerations for studying neural oscillations.
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研究神经振荡的方法学考虑因素。
DOI：
10.1111/ejn.15361
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发表时间：
2022-06
期刊：
影响因子：
--
通讯作者：
Voytek B
中科院分区：
文献类型：
--
作者：
Donoghue T;Schaworonkow N;Voytek B
神经振荡在记录方法和物种中普遍存在，与认知任务广泛相关，并且适用于研究神经回路产生机制和神经种群动态的计算建模。正因为如此，神经振荡为联系理论、生理学和认知机制提供了一个令人兴奋的潜在机会。然而，尽管它们很普遍，但仍然存在许多新的和旧的问题，即我们的分析假设如何与已知的场势数据属性相违背。为了正确解释神经振荡的研究，并最终发展成机械理论，有必要仔细考虑我们采用的方法的潜在假设。在这里，我们讨论分析神经振荡的七个方法学考虑。考虑的是1)验证振荡的存在，因为它们可能不存在；2)验证振荡频带定义，以解决可变峰值频率；3)考虑到并发的非振荡非周期活动，否则可能会混淆测量；测量和解释4)时间变化和5)神经振荡的波形形状，这些振荡通常是突发的和/或非正弦的，可能导致虚假的结果；6)分离空间重叠的节奏，可能相互干扰；7)考虑获得可靠估计所需的信噪比。对于每个主题，我们都提供了相关的例子，展示了解释的潜在错误，并提供了解决这些问题的建议。我们主要关注单变量测量，如功率和相位估计，尽管我们讨论了这些问题如何传播到多变量测量。这些考虑和建议为测量和解释神经振荡提供了有益的指导。神经振荡是神经场数据的普遍特征，具有很大的潜力，可以帮助我们理解神经功能及其与认知的关系。然而，在调查它们的方法和报告的发现方面存在很大程度的差异。在这篇文章中，我们探讨了分析神经振荡的方法学考虑，这可能是一些潜在误解的基础，并提出了解决这些问题的最佳实践指南。
Neural oscillations are ubiquitous across recording methodologies and species, broadly associated with cognitive tasks, and amenable to computational modeling that investigates neural circuit generating mechanisms and neural population dynamics. Because of this, neural oscillations offer an exciting potential opportunity for linking theory, physiology, and mechanisms of cognition. However, despite their prevalence, there are many concerns—new and old—about how our analysis assumptions are violated by known properties of field potential data. For investigations of neural oscillations to be properly interpreted, and ultimately developed into mechanistic theories, it is necessary to carefully consider the underlying assumptions of the methods we employ. Here, we discuss seven methodological considerations for analyzing neural oscillations. The considerations are to 1) verify the presence of oscillations, as they may be absent; 2) validate oscillation band definitions, to address variable peak frequencies; 3) account for concurrent non-oscillatory aperiodic activity, which might otherwise confound measures; measure and account for 4) temporal variability and 5) waveform shape of neural oscillations, which are often bursty and/or nonsinusoidal, potentially leading to spurious results; 6) separate spatially overlapping rhythms, which may interfere with each other; and 7) consider the required signal-to-noise ratio for obtaining reliable estimates. For each topic, we provide relevant examples, demonstrate potential errors of interpretation, and offer suggestions to address these issues. We primarily focus on univariate measures, such as power and phase estimates, though we discuss how these issues can propagate to multivariate measures. These considerations and recommendations offer a helpful guide for measuring and interpreting neural oscillations. Neural oscillations are ubiquitous features of neural field data, with great potential for informing our understanding of neural function and how it relates to cognition. However, there is a great degree of variability in methods for investigating them, and findings that are reported. In this piece, we explore methodological considerations for analyzing neural oscillations, that may underlie some potential misinterpretations, and propose best practice guidelines for addressing them.
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DOI：
10.1038/nrn3241
发表时间：
2012-05-18
期刊：
Nature reviews. Neuroscience
影响因子：
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作者：
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