@misc{16674,
  author = {Marte S{\ae}tra},
  title = {Computational modeling of ion concentration dynamics in brain tissue},
  abstract = {Over the past decades, computational neuroscientists have developed ever more sophisticated and morphologically complex neuron models. Most of these models assume that the intra- and extracellular ion concentrations remain constant over the simulated period and thus do not account for concentration-dependent effects on neuronal firing properties. Of the models that do incorporate ion concentration dynamics, few account for the electrodiffusive nature of intra- and extracellular ion transport. In this talk, I will present the first multicompartmental neuron model that accounts for ion concentration dynamics in a biophysically consistent manner [1]. I will also show how electrodiffusive modeling of neurons and glial cells can be used to explore the genesis of slow potentials in the brain [2]. [1] S{\ae}tra, M.J., Einevoll, G.T. and Halnes, G., 2020. An electrodiffusive, ion conserving Pinsky-Rinzel model with homeostatic mechanisms. PLoS Computational Biology, 16(4), p.e1007661.[2] S{\ae}tra, M.J., Einevoll, G.T. and Halnes, G., 2021. An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain. PLoS Computational Biology, 17(7), p.e1008143.},
  year = {2022},
  journal = {Mathbio seminar, University of Pennsylvania, PA, USA},
  publisher = {Mathbio seminar},
  url = {https://www.math.upenn.edu/events/computational-modeling-ion-concentration-dynamics-brain-tissue},
}