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- W4307831175 abstract "<p>Modulation can be identified in a signal from correlations of power across frequencies. Resolving power over time and frequency using standard techniques of bandpass filtering and squaring creates bias: filtering presupposes a timescale and bandwidth for modulation, while squaring complicates separation from noise. Higher-order spectra (HOS) can be used to estimate power correlations without bias. HOS are not widely familiar because their meaning is thought to be obscure. A natural interpretation of the fourth-order spectrum (trispectrum) as a measure of linear relationships between power across frequencies is explained. This interpretation motivates a new tool, the modulogram, for identifying various types of modulation. The modulogram can be further decomposed into a low-dimensional feature space describing characteristic patterns of modulation. These developments are demonstrated with the blind identification of beta burst in rodent local field potential (LFP) recordings.</p>" @default.
- W4307831175 created "2022-11-06" @default.
- W4307831175 creator A5028976280 @default.
- W4307831175 date "2022-11-02" @default.
- W4307831175 modified "2023-10-17" @default.
- W4307831175 title "A Slice of Trispectrum for Patterns of Modulation" @default.
- W4307831175 doi "https://doi.org/10.36227/techrxiv.21401703.v1" @default.
- W4307831175 hasPublicationYear "2022" @default.
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