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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Authors
Journal
Journal of Visualized Experiments
1940-087X
Publisher
MyJoVE Corporation
Publication Date
Issue
76
Identifiers
DOI: 10.3791/50131
Source
Legacy
Keywords
  • Neuroscience
Disciplines
  • Computer Science

Abstract

When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.

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