ArticleJournal of mathematical biology2019
How well do reduced models capture the dynamics in models of interacting neurons?
Article in Journal of mathematical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Efficient models of cortical activity via local dynamic equilibria and coarse-grained interactions.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex.PLoS computational biology · 2021Article
- Model Reduction Captures Stochastic Gamma Oscillations on Low-Dimensional Manifolds.Frontiers in computational neuroscience · 2021Article
- Stochastic neural field model: multiple firing events and correlations.Journal of mathematical biology · 2019Article
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Authors and funding
3 authors.
Funding
Abstract
This paper introduces a class of stochastic models of interacting neurons with emergent dynamics similar to those seen in local cortical populations. Rigorous results on existence and uniqueness of nonequilibrium steady states are proved. These network models are then compared to very simple reduced models driven by the same mean excitatory and inhibitory currents. Discrepancies in firing rates between network and reduced models are investigated and explained by correlations in spiking, or partial synchronization, working in concert with "nonlinearities" in the time evolution of membrane potentials. The use of simple random walks and their first passage times to simulate fluctuations in neuronal membrane potentials and interspike times is also considered.
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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.