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

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25-50 Hz range ('slow gamma') are proposed to support memory retrieval independent of other frequencies. However, theta harmonics extend up to 48 Hz, necessitating a study to determine if 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 theta harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order theta harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25-50 Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted 'slow gamma' in a synthetic dataset that only contained theta and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120-250 Hz events. When Fourier is applied to high power, 25-50 Hz events, only theta harmonics are resolved. This analysis challenges the identification of the slow gamma rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow gamma 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 theta harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent gamma bands.