ArticleJournal of computational neuroscience2018
A mathematical model of recurrent spreading depolarizations.
Article in Journal of computational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- An astro-neural-field model with application to cortical spreading depolarization.Journal of computational neuroscience · 2026Article
- Glial Versus Neuronal NaGlia · 2025Article
- GABAergic neurons can facilitate the propagation of cortical spreading depolarization: experiments in mouse neocortical slices and a novel neural field computational model.PLoS computational biology · 2025Article
- An electrodiffusive network model with multicompartmental neurons and synaptic connections.PLoS computational biology · 2024Article
- Analysis of Network Models with Neuron-Astrocyte Interactions.Neuroinformatics · 2023Article
- A computational study on the role of glutamate and NMDA receptors on cortical spreading depression using a multidomain electrodiffusion model.PLoS computational biology · 2019Article
- Mitochondrial dysfunction and role in spreading depolarization and seizure.Journal of computational neuroscience · 2019Article
- Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics.Frontiers in neuroinformatics · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A detailed biophysical model for a neuron/astrocyte network is developed in order to explore mechanisms responsible for the initiation and propagation of recurrent cortical spreading depolarizations. The model incorporates biophysical processes not considered in the earlier models. This includes a model for the Na
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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.