Mappings between a macroscopic neural mass model and a reduced conductance-based model
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Publication:2376467
DOI10.1007/S00422-010-0372-ZzbMath1266.92041OpenAlexW2094230117WikidataQ39889942 ScholiaQ39889942MaRDI QIDQ2376467
John R. Terry, Serafim Rodrigues, Frank Marten, Anton V. Chizhov
Publication date: 21 June 2013
Published in: Biological Cybernetics (Search for Journal in Brave)
Full work available at URL: https://research-information.bristol.ac.uk/en/publications/mappings-between-a-macroscopic-neural-mass-model-and-a-reduced-conductancebased-model(8db436e0-ae9e-4148-8a19-9380f22b67e9).html
Related Items (3)
Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural net\-works ⋮ Macroscopic neural mass model constructed from a current-based network model of spiking neurons ⋮ On the Electrodynamics of Neural Networks
Cites Work
- Lectures in supercomputational neuroscience. Dynamics in complex brain networks. Papers based on the presentations at the 5th Helmholtz summer school on supercomputational physics ``Complex networks in brain dynamics, September 2005, Potsdam, Germany.
- Dynamics of pattern formation in lateral-inhibition type neural fields
- On the simulation of large populations of neurons.
- Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns
- Onset of polyspike complexes in a mean-field model of human electroencephalography and its application to absence epilepsy
- Almost Sure Stable Oscillations in a Large System of Randomly Coupled Equations
- Spiking Neuron Models
- Rate Models for Conductance-Based Cortical Neuronal Networks
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