Evidence map›Paper›PMID 31324673›Full record

ArticleeNeuro

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

Y Zhou, A Sheremet, Y Qin, J P Kennedy, N M DiCola, S N Burke, A P Maurer

Abstract read
In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Spectral dependence as a framework for neural coordination.Current research in neurobiology · 2026
    Article
  3. Novelty, Ecological Relevance, and Sexual Receptivity Modulate Neuronal Interactions between the Amygdala and Hippocampus.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Golden rhythms as a theoretical framework for cross-frequency organization.Neurons, behavior, data analysis, and theory · 2022
    Article
  15. Article
  16. Article
  17. Spectrum Degradation of Hippocampal LFP During Euthanasia.Frontiers in systems neuroscience · 2021
    Article
  18. Article
  19. Floating ideas on theta waves.Behavioral neuroscience · 2020
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Y ZhouEngineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611.
A SheremetEngineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611.ORCID 0000-0002-8895-4700
Y QinEngineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611.
J P KennedyMcKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL 32610.
N M DiColaMcKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL 32610.
S N BurkeMcKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL 32610.ORCID 0000-0002-1773-1294
A P MaurerEngineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611 drewmaurer@ufl.edu.ORCID 0000-0002-5470-237X

Funding

Testing and forecasting hippocampal theta wave propagation in learning and memoryR01MH109548 · NIMH · UNIVERSITY OF FLORIDA · PI MAURER, ANDREW PORTER · 2016 to 2020
$2.1M
Age-associated changes in hippocampal circuits and cognitive functionR01AG055544 · NIA · UNIVERSITY OF FLORIDA · PI MAURER, ANDREW PORTER · 2017 to 2021
$1.9M
NIA NIH HHS R01 AG055544NIMH NIH HHS R01 MH109548
6 · The paper itself

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.

Indexed as

Brain WavesSignal Processing, Computer-AssistedAlgorithmsAnimalsFemaleHippocampusMaleRatsEEMDlow γnonlinearityvelocity

Identifiers

PMID31324673
PMCPMC6709234

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.