Firing rate distributions in a feedforward network of neural oscillators with intrinsic and network heterogeneity

DOI10.3934/MBE.2019099zbMath1503.92013OpenAlexW2921462066WikidataQ92346769 ScholiaQ92346769MaRDI QIDQ2091893

Kyle Wendling, Cheng Ly

Publication date: 2 November 2022

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2019099

zbMATH Keywords

heterogeneityphase reductionphase oscillatorsPRCpopulation firing rate

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Fokker-Planck equations (35Q84)

Related Items (2)

Optimal Phase-Selective Entrainment of Heterogeneous Oscillator Ensembles ⋮ Statistical Analysis of Decoding Performances of Diverse Populations of Neurons

Cites Work

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• Mathematical frameworks for oscillatory network dynamics in neuroscience
• Chemical oscillations, waves, and turbulence
• Mathematical foundations of neuroscience
• The Fokker-Planck equation. Methods of solution and applications.
• Variable synaptic strengths controls the firing rate distribution in feedforward neural networks
• Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity
• Analysis of Recurrent Networks of Pulse-Coupled Noisy Neural Oscillators
• Implications of Neuronal Diversity on Population Coding
• The geometry of biological time.
• Synchrony, stability, and firing patterns in pulse-coupled oscillators

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