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Europe PubMed Central
Article . 2008
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Testing for nested oscillation

Authors: Penny, W.D.; Duzel, E.; Miller, K.J.; Ojemann, J.G.;

Testing for nested oscillation

Abstract

AbstractNested oscillation occurs when the amplitude of a faster rhythm is coupled to the phase of a slower rhythm. It has been proposed to underlie the discrete nature of perception and the capacity of working memory and is a phenomenon observable in human brain imaging data. This paper compares three published methods for detecting nested oscillation and a fourth method proposed in this paper. These are: (i) the modulation index, (ii) the phase-locking value (PLV), (iii) the envelope-to-signal correlation (ESC) and (iv) a general linear model (GLM) measure derived from ESC. We applied the methods to electrocorticographic (ECoG) data recorded during a working-memory task and to data from a simulated hippocampal interneuron network. Further simulations were then made to address the dependence of each measure on signal to noise level, coupling phase, epoch length, sample rate, signal nonstationarity, and multi-phasic coupling. Our overall conclusion is that the GLM measure is the best all-round approach for detecting nested oscillation.

Subjects by Vocabulary

Microsoft Academic Graph classification: Modulation index Phase (waves) Signal Measure (mathematics) General linear model business.industry Oscillation Linear model Amplitude Artificial intelligence business Psychology Algorithm

Keywords

Male, Oscillations, Neuroscience(all), Hippocampus, Article, Biological Clocks, Interneurons, Humans, Computer Simulation, Cross-frequency coupling, Evoked Potentials, Cerebral Cortex, Neurons, Brain Mapping, Intracranial EEG, General Neuroscience, Electroencephalography, Signal Processing, Computer-Assisted, Phase coupling, Memory, Short-Term, Linear Models, Nerve Net, Artifacts, Algorithms

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    205
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
205
Top 1%
Top 10%
Top 10%
Green
hybrid
Funded by
NSF| Exploring the Neural Dynamics of Cognition through Human Electrocorticography
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0642848
  • Funding stream: Directorate for Social, Behavioral & Economic Sciences | Division of Behavioral and Cognitive Sciences
,
WT
Project
  • Funder: Wellcome Trust (WT)
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Neuroinformatics
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