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Related Concept Videos

¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

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The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
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Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
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Frequency Response of a Circuit01:20

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Inductive circuits present intriguing challenges in electrical engineering, particularly during the transition from the time domain to the frequency domain. This transformation involves converting inductors into impedances and utilizing phasor representation.
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NMR Spectroscopy: Spin–Spin Coupling01:08

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The spin state of an NMR-active nucleus can have a slight effect on its immediate electronic environment. This effect propagates through the intervening bonds and affects the electronic environments of NMR-active nuclei up to three bonds away; occasionally, even farther. This phenomenon is called spin–spin coupling or J-coupling. Coupling interactions are mutual and result in small changes in the absorption frequencies of both nuclei involved. While nuclei of the same element are involved...
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Oscillations In An LC Circuit01:30

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An idealized LC circuit of zero resistance can oscillate without any source of emf by shifting the energy stored in the circuit between the electric and magnetic fields. In such an LC circuit, if the capacitor contains a charge q before the switch is closed, then all the energy of the circuit is initially stored in the electric field of the capacitor. This energy is given by
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¹H NMR Signal Multiplicity: Splitting Patterns01:13

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When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
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Related Experiment Video

Updated: Jan 15, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
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Functional Connectivity Is Dominated by Aperiodic, Rather Than Oscillatory, Coupling.

N Monchy1, J Duprez1, J-F Houvenaghel1,2

  • 1Univ Rennes, LTSI - U1099, Rennes F-35000, France.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|October 8, 2025
PubMed
Summary

Most functional connectivity (FC) studies may be analyzing aperiodic brain activity, not true neural oscillations. This research highlights that aperiodic signals dominate delta, theta, gamma, and beta networks, impacting interpretations of brain function.

Keywords:
aperiodic activityfunctional connectivityoscillations

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Brain Imaging

Background:

  • Functional connectivity (FC) analysis is crucial for understanding brain circuits in health and disease.
  • Traditional FC methods assume signals reflect neural oscillations, but may conflate them with non-oscillatory aperiodic activity.

Purpose of the Study:

  • To quantify the contribution of aperiodic neural activity to reconstructed oscillatory functional networks in human electroencephalography (EEG) data.
  • To investigate whether resting-state and task-based FC predominantly reflects oscillatory or aperiodic processes.

Main Methods:

  • Analysis of two human EEG databases (resting-state and cognitive task recordings).
  • Quantification of aperiodic activity's contribution to functional networks across different frequency bands (delta, theta, alpha, beta, gamma).

Main Results:

  • Aperiodic activity drives approximately 99% of delta, theta, and gamma networks, and over 90% of beta networks.
  • Between 23% and 61% of alpha functional networks are also driven by aperiodic activity.
  • Oscillatory functional networks are likely much sparser than commonly assumed.

Conclusions:

  • Most current FC studies using resting-state data may be reflecting aperiodic networks rather than oscillatory ones.
  • Researchers should verify the presence of aperiodicity-unbiased neural oscillations before estimating statistical coupling to improve FC study robustness and interpretability.