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eNeuro. 2019 Aug 1;6(4). pii: ENEURO.0142-19.2019. doi: 10.1523/ENEURO.0142-19.2019. Print 2019 Jul/Aug.

Methodological Considerations on the Use of Different Spectral Decomposition Algorithms to Study Hippocampal Rhythms.

Author information

1
Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611.
2
McKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL 32610.
3
Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611 drewmaurer@ufl.edu.
4
Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611.

Abstract

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25- to 50-Hz range ("slow γ") are proposed to support memory retrieval independent of other frequencies. However, θ harmonics extend up to 48 Hz, necessitating a study to determine whether these oscillations are fundamentally the same. We compared the spectral analysis methods of wavelet, ensemble empirical-mode decomposition (EEMD), and Fourier transform. EEMD, as previously applied, failed to account for the θ harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order θ harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25- to 50-Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted slow γ in a synthetic dataset that only contained θ and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120- to 250-Hz events. When Fourier is applied to high power, 25- to 50-Hz events, only θ harmonics are resolved. This analysis challenges the identification of the slow γ rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow γ is present in the rat hippocampus, the analysis presented here shows that unless care is exerted in the application of EEMD and wavelet techniques, the results may be misleading, in this case misrepresenting θ harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent γ bands.

KEYWORDS:

EEMD; low γ; nonlinearity; velocity

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