ArticleNeuron2019
Detection of Multiway Gamma Coordination Reveals How Frequency Mixing Shapes Neural Dynamics.
Article in Neuron, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- A proposal for realizing cognitive functions using traveling waves, phase-locked and synchronized patterns, holography, neural mixing, and single sideband communications.Frontiers in computational neuroscience · 2026Article
- Time-domain brain: temporal mechanisms for brain functions using time-delay nets, holographic processes, radio communications, and emergent oscillatory sequences.Frontiers in computational neuroscience · 2025Article
- Kernel-based joint independence tests for multivariate stationary and non-stationary time series.Royal Society open science · 2023Article
- Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement.Frontiers in neuroscience · 2022Article
- Golden rhythms as a theoretical framework for cross-frequency organization.Neurons, behavior, data analysis, and theory · 2022Article
- Contribution of animal models toward understanding resting state functional connectivity.NeuroImage · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
A principle of communication technology, frequency mixing, describes how novel oscillations are generated when rhythmic inputs converge on a nonlinearly activating target. As expected given that neurons are nonlinear integrators, it was demonstrated that neuronal networks exhibit mixing in response to imposed oscillations of known frequencies. However, determining when mixing occurs in spontaneous conditions, where weaker or more variable rhythms prevail, has remained impractical. Here, we show that, by exploiting the predicted phase (rather than frequency) relationships between oscillations, the contributions of mixing can be readily identified, even in small samples of noisy data. Assessment of extracellular data using this approach revealed that frequency mixing is widely expressed in a state- and region-dependent manner and that oscillations emerging from mixing entrain unit activity. Frequency mixing is thus intrinsic to the structure of neural activity and contributes importantly to neural dynamics.
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Registered trials
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.