@misc {43097,
	title = {Hjerneprat med Marte Julie S{\ae}tra og Gaute Einevoll - Del 2},
	year = {2023},
	month = {01/2023},
	publisher = {Simula},
	type = {Videocast},
	address = {YouTube},
	url = {https://youtu.be/BP9tY6AUMQU},
	author = {Marte J. {S{\ae}tra}}
}
@misc {43098,
	title = {Hjerneprat med Marte Julie S{\ae}tra og Gaute Einevoll - Del 3},
	year = {2023},
	month = {01/2023},
	publisher = {Simula},
	type = {Videocast},
	address = {YouTube},
	url = {https://youtu.be/pTq-GZVZjh0},
	author = {Marte J. {S{\ae}tra}}
}
@article {43168,
	title = {Neural activity induces strongly coupled electro-chemo-mechanical interactions and fluid flow in astrocyte networks and extracellular space {\textendash} a computational study},
	journal = {PLoS Computational Biology},
	volume = {19},
	year = {2023},
	month = {07/2023},
	pages = {e1010996},
	publisher = {Public Library of Science},
	doi = {https://doi.org/10.1371/journal.pcbi.1010996},
	url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010996},
	author = {Marte J. {S{\ae}tra} and Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@misc {43323,
	title = {Neural activity induces strongly coupled electro-chemo-mechanical interactions and fluid flow in astrocyte networks and extracellular space},
	howpublished = {32nd Annual Computational Neuroscience Meeting},
	year = {2023},
	publisher = {Organization for Computational Neuroscience},
	author = {Marte J. {S{\ae}tra}}
}
@misc {43260,
	title = {Paneldeltager i Abels t{\r a}rn},
	howpublished = {Vil vi kunne gj{\o}re opptak av v{\r a}re dr{\o}mmer i fremtiden?},
	year = {2023},
	month = {05/2023},
	publisher = {NRK P2},
	type = {Radio / Podcast},
	url = {https://radio.nrk.no/podkast/abels_taarn/sesong/202305/l_e3cb7694-7667-41b0-8b76-94766731b072},
	author = {Marte J. {S{\ae}tra}}
}
@article {28146,
	title = {Baseline oxygen consumption decreases with cortical depth},
	journal = {PLoS Biology},
	volume = {20},
	year = {2022},
	month = {10/2022},
	pages = {e3001440},
	publisher = {PLOS},
	doi = {https://doi.org/10.1101/2021.10.13.464176},
	url = {https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001440},
	author = {M{\"a}chler, Philipp and Fomin-Thunemann, Natalie and Thunemann, Martin and Marte J. {S{\ae}tra} and Desjardins, Mich{\`e}le and K{\i}l{\i}{\c c}, K{\i}v{\i}lc{\i}m and Layth N {Amra} and Emily A {Martin} and Ichun Anderson {Chen} and {\c S}encan-E{\u g}ilmez, Ikbal and Li, Baoqiang and Saisan, Payam and John X. {Jiang} and Cheng, Qun and Kimberly L {Weldy} and David A {Boas} and Richard B {Buxton} and Gaute T {Einevoll} and Anders M {Dale} and Sakad{\v z}i{\'c}, Sava and Devor, Anna}
}
@misc {42663,
	title = {Computational modeling of ion concentration dynamics in brain tissue},
	howpublished = {Mathbio seminar, University of Pennsylvania, PA, USA},
	year = {2022},
	publisher = {Mathbio seminar},
	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].\&nbsp;[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.},
	url = {https://www.math.upenn.edu/events/computational-modeling-ion-concentration-dynamics-brain-tissue},
	author = {Marte J. {S{\ae}tra}}
}
@misc {42668,
	title = {Computational modeling of ion concentration dynamics in brain tissue},
	howpublished = {Math graduate seminar, University of Pennsylvania, PA, USA},
	year = {2022},
	publisher = {Math graduate seminar},
	author = {Marte J. {S{\ae}tra}}
}
@misc {42477,
	title = {Gjest i podkasten J{\o}ss!?, Episode 67},
	howpublished = {Kniv av b{\ae}sj, kabel i Atlanteren og poljakt i Sibir},
	year = {2022},
	month = {05/2022},
	publisher = {plingplong},
	url = {https://open.spotify.com/episode/3OtRF1ON7xoETE6MGO9Sra?si=d2de081f39bf47bb},
	author = {Marte J. {S{\ae}tra}}
}
@misc {42512,
	title = {Gjest i podkasten J{\o}ss!?, Episode 70},
	howpublished = {Heise baller opp i flaggstang, fjerne minner fra hjernen og en by av bare Disney-slott},
	year = {2022},
	month = {06/2022},
	publisher = {plingplong},
	author = {Marte J. {S{\ae}tra}}
}
@misc {42856,
	title = {High oxygen metabolism in layer I revealed with two-photon phosphorescence lifetime microscopy in awake mice under rest and stimulation},
	year = {2022},
	month = {11/2022},
	publisher = {Society for Neuroscience},
	address = {Neuroscience 2022},
	author = {Fomin-Thunemann, Natalie and M{\"a}chler, Philipp and Thunemann, Martin and Marte J. {S{\ae}tra} and Desjardins, Mich{\`e}le and K{\i}l{\i}{\c c}, K{\i}v{\i}lc{\i}m and Vayisoglu, Tugberk and Doran, Patrick and Jiang, John and Martin, Emily and {\c S}encan, Ikbal and Li, Baoqiang and Saisan, Payam and Cheng, Qun and Weldy, Kimberly and Boas, David and Buxton, Richard and Einevoll, Gaute and Dale, Anders and Sakad{\v z}i{\'c}, Sava and Devor, Anna}
}
@misc {42560,
	title = {Hjerneprat med Marte Julie S{\ae}tra og Gaute Einevoll},
	year = {2022},
	month = {06/2022},
	publisher = {YouTube, Simula},
	type = {Videocast},
	url = {https://youtu.be/GwnHNGnpLUA},
	author = {Marte J. {S{\ae}tra}}
}
@misc {28481,
	title = {Min virtuelle verden},
	year = {2022},
	month = {03/2022},
	publisher = {Realfagsdagene, NTNU},
	type = {Presentasjon og stand},
	author = {Marte J. {S{\ae}tra}}
}
@misc {42855,
	title = {Modeling electrodiffusive, osmotic, and hydrostatic interplay in astrocyte networks},
	year = {2022},
	month = {11/2022},
	publisher = {Society for Neuroscience},
	address = {Neuroscience 2022},
	abstract = {During high neuronal activity, the intra- and extracellular ion concentrations change. These changes affect the osmotic pressure gradients across the membranes of both neurons and astrocytes, leading to water movement and cellular swelling. We asked: Can swelling generate a hydrostatic pressure gradient of sufficient magnitude to drive non-negligible fluid flow within astrocytes or the extracellular space [1]? As it is currently infeasible to measure such intracellular pressure gradients in vivo, computational modeling emerges as a viable alternative to study the interplay between osmotic and hydrostatic forces at the microscale.\&nbsp;\&nbsp;In this study, we present a computational model of ionic electrodiffusion, hydrostatic pressures, and transmembrane- and intracompartmental fluid flow in a homogenized astrocytic syncytium surrounded by extracellular space. The model builds on previous models of ionic electrodiffusion [2,3],\&nbsp;and potassium buffering [4]. Our findings show that increases in extracellular potassium concentrations in response to neuronal activity induce swelling and hydrostatic pressure gradients within the intra- and extracellular spaces. The fluid flow induced by these hydrostatic pressure gradients alone did not have a significant effect on the transport of potassium within any of the compartments. However, when also accounting for fluid flow induced by osmotic gradients within the astrocytic syncytium, convection played a considerable role in potassium clearance. These findings point at a mechanistic understanding of how astrocytic permeability may impact fluid flow in the brain.[1] Halnes, G., Pettersen, K. H., {\O}yehaug, L., Rognes, M. E. \&amp; Einevoll, G. T. Astrocytic ion dynamics: Implications for potassium buffering and liquid flow. In Computational Glioscience, 363{\textendash}391 (Springer, 2019).[2] Mori, Y. A multidomain model for ionic electrodiffusion and osmosis with an application to cortical spreading depression. Phys. D: Nonlinear Phenom. 308, 94{\textendash}108 (2015).[3]\&nbsp; Zhu, Y., Xu, S., Eisenberg, R. S. \&amp; Huang, H. Optic nerve microcirculation: Fluid flow and electrodiffusion. Phys. Fluids 33, 041906 (2021).[4] Halnes, G., {\O}stby, I., Pettersen, K. H., Omholt, S. W. \&amp; Einevoll, G. T. Electrodiffusive model for astrocytic and neuronal ion concentration dynamics. PLoS computational biology 9, e1003386 (2013).},
	author = {Marte J. {S{\ae}tra} and Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@misc {42769,
	title = {Spatially resolved estimation of CMRO2},
	howpublished = {Neurovsascular Imaging Laboratory, Boston University, MA, USA},
	year = {2022},
	publisher = {Neurovsascular Imaging Laboratory},
	author = {Marte J. {S{\ae}tra}}
}
@article {10.1371/journal.pcbi.1008143,
	title = {An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain},
	journal = {PLOS Computational Biology},
	volume = {17},
	number = {7},
	year = {2021},
	month = {07/2021},
	pages = {1-45},
	publisher = {Public Library of Science},
	abstract = {Within the computational neuroscience community, there has been a focus on simulating the electrical activity of neurons, while other components of brain tissue, such as glia cells and the extracellular space, are often neglected. Standard models of extracellular potentials are based on a combination of multicompartmental models describing neural electrodynamics and volume conductor theory. Such models cannot be used to simulate the slow components of extracellular potentials, which depend on ion concentration dynamics, and the effect that this has on extracellular diffusion potentials and glial buffering currents. We here present the electrodiffusive neuron-extracellular-glia (edNEG) model, which we believe is the first model to combine compartmental neuron modeling with an electrodiffusive framework for intra- and extracellular ion concentration dynamics in a local piece of neuro-glial brain tissue. The edNEG model (i) keeps track of all intraneuronal, intraglial, and extracellular ion concentrations and electrical potentials, (ii) accounts for action potentials and dendritic calcium spikes in neurons, (iii) contains a neuronal and glial homeostatic machinery that gives physiologically realistic ion concentration dynamics, (iv) accounts for electrodiffusive transmembrane, intracellular, and extracellular ionic movements, and (v) accounts for glial and neuronal swelling caused by osmotic transmembrane pressure gradients. The edNEG model accounts for the concentration-dependent effects on ECS potentials that the standard models neglect. Using the edNEG model, we analyze these effects by splitting the extracellular potential into three components: one due to neural sink/source configurations, one due to glial sink/source configurations, and one due to extracellular diffusive currents. Through a series of simulations, we analyze the roles played by the various components and how they interact in generating the total slow potential. We conclude that the three components are of comparable magnitude and that the stimulus conditions determine which of the components that dominate.},
	doi = {10.1371/journal.pcbi.1008143},
	url = {https://doi.org/10.1371/journal.pcbi.1008143},
	author = {Marte J. {S{\ae}tra} and Gaute T. {Einevoll} and Halnes, Geir}
}
@misc {27935,
	title = {Hvor mye veier jorda?},
	year = {2021},
	month = {03/2021},
	publisher = {Titan.uio.no},
	url = {https://titan.uio.no/fysikk/2021/hvor-mye-veier-jorda},
	author = {Marte J. {S{\ae}tra}}
}
@misc {28149,
	title = {Hvordan utforske hjernen med fysikk og datasimuleringer?},
	howpublished = {Dataanalyser som redder verden {\textendash} science not fiction},
	year = {2021},
	month = {11/21},
	publisher = {Centre for Digial Life Norway},
	type = {Presentasjon og sofasamtale},
	address = {Kulturhuset og online},
	author = {Marte J. {S{\ae}tra}}
}
@misc {27933,
	title = {Marte Julie (28) fors{\o}ker {\r a} l{\o}se et av verdens st{\o}rste mysterier},
	year = {2021},
	month = {02/2021},
	publisher = {NRK P3},
	url = {https://p3.no/loser-hjernens-mysterier/},
	author = {Marte J. {S{\ae}tra}}
}
@misc {28064,
	title = {Marte Julie S{\ae}tra er forsker i hjernefysikk},
	howpublished = {Min hjernehelse},
	volume = {1},
	year = {2021},
	month = {10/2021},
	pages = {26-27},
	publisher = {Hjerner{\r a}det},
	type = {Interview},
	author = {Marte J. {S{\ae}tra}}
}
@misc {27932,
	title = {Paneldeltager i Abels t{\r a}rn},
	year = {2021},
	month = {02/2021},
	publisher = {NRK P2},
	url = {https://radio.nrk.no/podkast/abels_taarn/sesong/202102/l_d258f492-831a-418e-98f4-92831af18e39},
	author = {Marte J. {S{\ae}tra}}
}
