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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Localizing Spectral Interactions in the Resting State Network Using the Hilbert-Huang Transform.

Ai-Ling Hsu1,2, Chia-Wei Li3, Pengmin Qin4,5,6

  • 1Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan 33305, Taiwan.

Brain Sciences
|February 25, 2022
PubMed
Summary

Researchers explored brain functional connectivity using the Hilbert-Huang transform (HHT) to analyze resting-state fMRI (rs-fMRI) data. This novel ensemble spectral interaction (ESI) method revealed differences in visual network frequency couplings between eye-closed and eye-open states.

Keywords:
Hilbert–Huang transformamplitude-to-amplitude couplingensemble spectral interactionresting-state fMRItime-frequency mapwavelet analysis

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Area of Science:

  • Neuroscience
  • Brain Imaging
  • Signal Processing

Background:

  • Brain synchronizations rely on neuronal oscillations and frequency interactions.
  • Understanding how intrinsic interactions create functional integrity across brain regions is challenging.
  • Previous studies focused on localizing frequency interactions in resting-state fMRI (rs-fMRI).

Purpose of the Study:

  • To investigate fMRI-based spectral interactions using time-frequency (TF) analysis.
  • To overcome limitations of Fourier-based TF analyses in rs-fMRI due to limited time points.
  • To introduce and validate the Hilbert-Huang transform (HHT) for analyzing ensemble spectral interactions (ESI) in rs-fMRI.

Main Methods:

  • Employed the Hilbert-Huang transform (HHT) for time-frequency analysis of rs-fMRI signals.
  • Simulated data with time-variant frequency changes to assess HHT performance.
  • Detected amplitude-to-amplitude frequency couplings (AAC) across brain regions to compare eye-closed (EC) and eye-open (EO) conditions.

Main Results:

  • Hilbert TF maps demonstrated superior spectro-temporal resolution compared to wavelet maps.
  • ESI analysis revealed amplified spectral interaction strength (0.03-0.04 Hz) in the visual network during EC compared to EO.
  • Canonical connectivity analysis failed to detect these condition-specific differences.

Conclusions:

  • The study introduces ensemble spectral interaction (ESI) using HHT for mapping fMRI-based functional connectivity via AAC.
  • ESI provides a novel perspective on functional connectivity at specific frequency bins.
  • ESI holds potential for enhanced diagnostic capabilities in clinical neuroscience.