Geir Halnes

• Hanssen, Kine Ødegård; Grødem, Sverre; Fyhn, Marianne; Hafting, Torkel; Einevoll, Gaute & Ness, Torbjørn V [Show all 7 contributors for this article] (2023). Responses in fast-spiking interneuron firing rates to parameter variations associated with degradation of perineuronal nets. Journal of Computational Neuroscience. ISSN 0929-5313. 51, p. 283–298. doi: 10.1007/s10827-023-00849-9. Full text in Research Archive
• Hanssen, Kine Ødegård; Grødem, Sverre; Fyhn, Marianne; Hafting, Torkel; Einevoll, Gaute & Ness, Torbjørn Vefferstad [Show all 7 contributors for this article] (2022). Effects of perineuronal nets on neural ring properties. Research Square. ISSN 2693-5015. doi: 10.21203/rs.3.rs-2198467/v1.
• Ellingsrud, Ada Johanne; Dukefoss, Didrik Bakke; Enger, Rune; Halnes, Geir; Pettersen, Klas Henning & Rognes, Marie Elisabeth (2022). Validating a Computational Framework for Ionic Electrodiffusion with Cortical Spreading Depression as a Case Study. eNeuro. ISSN 2373-2822. 9(2). doi: 10.1523/ENEURO.0408-21.2022. Full text in Research Archive Show summary

  Cortical spreading depression (CSD) is a wave of pronounced depolarization of brain tissue accompanied by substantial shifts in ionic concentrations and cellular swelling. Here, we validate a computational framework for modeling electrical potentials, ionic movement, and cellular swelling in brain tissue during CSD. We consider different model variations representing wild-type (WT) or knock-out/knock-down mice and systematically compare the numerical results with reports from a selection of experimental studies. We find that the data for several CSD hallmarks obtained computationally, including wave propagation speed, direct current shift duration, peak in extracellular K+ concentration as well as a pronounced shrinkage of extracellular space (ECS) are well in line with what has previously been observed experimentally. Further, we assess how key model parameters including cellular diffusivity, structural ratios, membrane water and/or K+ permeabilities affect the set of CSD characteristics.

• Hagen, Espen; Magnusson, Steinn; Ness, Torbjørn Vefferstad; Halnes, Geir; Babu, Pooja N. & Linssen, Charl [Show all 8 contributors for this article] (2022). Brain signal predictions from multi-scale networks using a linearized framework. PLoS Computational Biology. ISSN 1553-734X. 18(8). doi: 10.1371/journal.pcbi.1010353. Full text in Research Archive
• Ellingsrud, Ada Johanne; Enger, Rune; Dukefoss, Didrik Bakke; Halnes, Geir; Pettersen, Klas Henning & Rognes, Marie Elisabeth (2021). Validating a computational framework for ionic electrodiffusion with cortical spreading depression as a case study. bioRxiv. ISSN 2692-8205. doi: 10.1101/2021.11.29.470301.
• Sætra, Marte Julie; Einevoll, Gaute & Halnes, Geir (2021). An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain. PLoS Computational Biology. ISSN 1553-734X. 17(7). doi: 10.1371/journal.pcbi.1008143. Full text in Research Archive Show summary

  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.

• Næss, Solveig; Halnes, Geir; Hagen, Espen; Hagler, Donald J.; Dale, Anders M. & Einevoll, Gaute [Show all 7 contributors for this article] (2021). Biophysically detailed forward modeling of the neural origin of EEG and MEG signals. NeuroImage. ISSN 1053-8119. 225. doi: 10.1016/j.neuroimage.2020.117467. Full text in Research Archive
• Næss, Solveig; Halnes, Geir; Hagen, Espen; Hagler, Donald J.; Dale, Anders M. & Einevoll, Gaute [Show all 7 contributors for this article] (2020). Biophysical modeling of the neural origin of EEG and MEG signals. bioRxiv. ISSN 2692-8205. doi: 10.1101/2020.07.01.181875.
• Ellingsrud, Ada Johanne; Solbrå, Andreas Våvang; Einevoll, Gaute; Halnes, Geir & Rognes, Marie Elisabeth (2020). Finite element simulation of ionic electrodiffusion in cellular geometries. Frontiers in Neuroinformatics. ISSN 1662-5196. 14, p. 1–18. doi: 10.3389/fninf.2020.00011. Full text in Research Archive
• Sætra, Marte Julie; Einevoll, Gaute & Halnes, Geir (2020). An electrodiffusive, ion conserving Pinsky-Rinzel model with homeostatic mechanisms. PLoS Computational Biology. ISSN 1553-734X. 16(4), p. 1–36. doi: 10.1371/journal.pcbi.1007661. Full text in Research Archive
• Halnes, Geir; Pettersen, Klas Henning; Øyehaug, Leiv; Rognes, Marie Elisabeth & Einevoll, Gaute (2019). Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow. In Berry, Hugues & De Pittà, Maurizio (Ed.), Computational Glioscience. Springer Nature. ISSN 978-3-030-00817-8. p. 363–391. doi: 10.1007/978-3-030-00817-8_14. Full text in Research Archive
• Mäki-Marttunen, Tuomo; Kaufmann, Tobias; Elvsåshagen, Torbjørn; Devor, Anna; Djurovic, Srdjan & Westlye, Lars Tjelta [Show all 23 contributors for this article] (2019). Biophysical Psychiatry—How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders. Frontiers in Psychiatry. ISSN 1664-0640. 10. doi: 10.3389/fpsyt.2019.00534. Full text in Research Archive
• Tennøe, Simen; Hodne, Kjetil; Haug, Trude; Weltzien, Finn-Arne; Einevoll, Gaute & Halnes, Geir (2019). [Re] Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study. ReScience. ISSN 2430-3658. 5(1). doi: 10.5281/zenodo.2611252. Full text in Research Archive
• Halnes, Geir; Tennøe, Simen; Haug, Trude; Einevoll, Gaute; Weltzien, Finn-Arne & Hodne, Kjetil (2019). A computational model for gonadotropin releasing cells in the teleost fish medaka. PLoS Computational Biology. ISSN 1553-734X. 15(8), p. 1–28. doi: 10.1371/journal.pcbi.1006662. Full text in Research Archive Show summary

  Pituitary endocrine cells fire action potentials (APs) to regulate their cytosolic Ca2+ concentration and hormone secretion rate. Depending on animal species, cell type, and biological conditions, pituitary APs are generated either by TTX-sensitive Na+ currents (INa), high-voltage activated Ca2+ currents (ICa), or by a combination of the two. Previous computational models of pituitary cells have mainly been based on data from rats, where INa is largely inactivated at the resting potential, and spontaneous APs are predominantly mediated by ICa. Unlike in rats, spontaneous INa-mediated APs are consistently seen in pituitary cells of several other animal species, including several species of fish. In the current work we develop a computational model of gonadotropin releasing cells in the teleost fish medaka (Oryzias latipes). The model stands out from previous modeling efforts by being (1) the first model of a pituitary cell in teleosts, (2) the first pituitary cell model that fires sponateous APs that are predominantly mediated by INa, and (3) the first pituitary cell model where the kinetics of the depolarizing currents, INa and ICa, are directly fitted to voltage-clamp data. We explore the firing properties of the model, and compare it to the properties of previous models that fire ICa-based APs. We put a particular focus on how the big conductance K+ current (IBK) modulates the AP shape. Interestingly, we find that IBK can prolong AP duration in models that fire ICa-based APs, while it consistently shortens the duration of the predominantly INa-mediated APs in the medaka gonadotroph model. Although the model is constrained to experimental data from gonadotroph cells in medaka, it may likely provide insights also into other pituitary cell types that fire INa-mediated APs.

• Solbrå, Andreas Våvang; Bergersen, Aslak Wigdahl; van den Brink, Jonas; Malthe-Sørenssen, Anders; Einevoll, Gaute & Halnes, Geir (2018). A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons. PLoS Computational Biology. ISSN 1553-734X. 14(10), p. 1–26. doi: 10.1371/journal.pcbi.1006510. Full text in Research Archive
• Tennøe, Simen; Halnes, Geir & Einevoll, Gaute (2018). Uncertainpy: A Python toolbox for uncertainty quantification and sensitivity analysis in computational neuroscience. Frontiers in Neuroinformatics. ISSN 1662-5196. 12:49, p. 1–29. doi: 10.3389/fninf.2018.00049. Full text in Research Archive
• Mobarhan, Milad; Halnes, Geir; Martínez-Cañada, Pablo; Hafting, Torkel; Fyhn, Marianne & Einevoll, Gaute (2018). Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells. PLoS Computational Biology. ISSN 1553-734X. 14(5). doi: 10.1371/journal.pcbi.1006156. Full text in Research Archive
• Martínez-Cañada, Pablo; Mobarhan, Milad; Halnes, Geir; Fyhn, Marianne; Morillas, Christian & Pelayo, Francisco [Show all 7 contributors for this article] (2018). Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells. PLoS Computational Biology. ISSN 1553-734X. 14(1), p. 1–45. doi: 10.1371/journal.pcbi.1005930. Full text in Research Archive
• Mäki-Marttunen, Tuomo; Halnes, Geir; Devor, Anna; Metzner, Christoph; Dale, Anders M. & Andreassen, Ole Andreas [Show all 7 contributors for this article] (2018). A stepwise neuron model fitting procedure designed for recordings with high spatial resolution: Application to layer 5 pyramidal cells. Journal of Neuroscience Methods. ISSN 0165-0270. 293, p. 264–283. doi: 10.1016/j.jneumeth.2017.10.007. Full text in Research Archive
• Gratiy, Sergey L.; Halnes, Geir; Denman, Daniel; Hawrylycz, Michael J; Koch, Christof & Einevoll, Gaute [Show all 7 contributors for this article] (2017). From Maxwell's equations to the theory of current-source density analysis. European Journal of Neuroscience. ISSN 0953-816X. 45(8), p. 1013–1023. doi: 10.1111/ejn.13534. Full text in Research Archive
• Tveito, Aslak; Jæger, Karoline Horgmo; Lines, Glenn Terje; Paszkowski, Lukasz; Sundnes, Joakim & Edwards, Andrew [Show all 9 contributors for this article] (2017). An evaluation of the accuracy of classical models for computing the membrane potential and extracellular potential for neurons. Frontiers in Computational Neuroscience. ISSN 1662-5188. 11. doi: 10.3389/fncom.2017.00027. Full text in Research Archive
• Halnes, Geir; Mäki-Marttunen, Tuomo; Pettersen, Klas; Andreassen, Ole Andreas & Einevoll, Gaute (2017). Ion diffusion may introduce spurious current sources in current-source density (CSD) analysis. Journal of Neurophysiology. ISSN 0022-3077. 118(1), p. 114–120. doi: 10.1152/jn.00976.2016. Full text in Research Archive
• Halnes, Geir; Mäki-Marttunen, Tuomo; Keller, Daniel; Pettersen, Klas; Andreassen, Ole Andreas & Einevoll, Gaute (2016). Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue. PLoS Computational Biology. ISSN 1553-734X. 12(11). doi: 10.1371/journal.pcbi.1005193. Full text in Research Archive
• Heiberg, Thomas; Hagen, Espen; Halnes, Geir & Einevoll, Gaute (2016). Biophysical Network Modelling of the dLGN Circuit: Different Effects of Triadic and Axonal Inhibition on Visual Responses of Relay Cells. PLoS Computational Biology. ISSN 1553-734X. 12(5). doi: 10.1371/journal.pcbi.1004929. Full text in Research Archive
• Mäki-Marttunen, Tuomo; Halnes, Geir; Devor, Anna; Witoelar, Aree; Bettella, Francesco & Djurovic, Srdjan [Show all 10 contributors for this article] (2016). Functional effects of schizophrenia-linked genetic variants on intrinsic single-neuron excitability: a modeling study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. ISSN 2451-9022. 1(1), p. 49–59. doi: 10.1016/j.bpsc.2015.09.002. Show summary

  BACKGROUND: Recent genome-wide association studies have identified a large number of genetic risk factors for schizophrenia (SCZ) featuring ion channels and calcium transporters. For some of these risk factors, independent prior investigations have examined the effects of genetic alterations on the cellular electrical excitability and calcium homeostasis. In the present proof-of-concept study, we harnessed these experimental results for modeling of computational properties on layer V cortical pyramidal cells and identified possible common alterations in behavior across SCZ-related genes. METHODS: We applied a biophysically detailed multicompartmental model to study the excitability of a layer V pyramidal cell. We reviewed the literature on functional genomics for variants of genes associated with SCZ and used changes in neuron model parameters to represent the effects of these variants. RESULTS: We present and apply a framework for examining the effects of subtle single nucleotide polymorphisms in ion channel and calcium transporter-encoding genes on neuron excitability. Our analysis indicates that most of the considered SCZ-related genetic variants affect the spiking behavior and intracellular calcium dynamics resulting from summation of inputs across the dendritic tree. CONCLUSIONS: Our results suggest that alteration in the ability of a single neuron to integrate the inputs and scale its excitability may constitute a fundamental mechanistic contributor to mental disease, alongside the previously proposed deficits in synaptic communication and network behavior. Keywords: Biophysical modeling, Functional genomics, Genome-wide association studies, Layer V pyramidal cell, Neuron excitability, Schizophrenia

• Halnes, Geir; Østby, Ivar; Pettersen, Klas; Omholt, Stig William & Einevoll, Gaute (2015). An Electrodiffusive Formalism for Ion Concentration Dynamics in Excitable Cells and the Extracellular Space Surrounding Them. In Liljenstrøm, Hans (Eds.), Advances in Cognitive Neurodynamic (IV). Proceedings of the Fourth International Conference on Cognitive Neurodynamics - 2013. Springer Science+Business Media B.V.. ISSN 978-94-017-9548-7. p. 353–360. doi: 10.1007/978-94-017-9548-7_50.
• Allken, Vaneeda; Chepkoech, Joy-Loi; Einevoll, Gaute & Halnes, Geir (2014). The Subcellular Distribution of T-Type Ca2+ Channels in Interneurons of the Lateral Geniculate Nucleus. PLOS ONE. ISSN 1932-6203. 9(9). doi: 10.1371/journal.pone.0107780. Full text in Research Archive
• Halnes, Geir; Østby, Ivar; Pettersen, Klas; Omholt, Stig W & Einevoll, Gaute Tomas (2013). Electrodiffusive Model for Astrocytic and Neuronal Ion Concentration Dynamics. PLoS Computational Biology. ISSN 1553-734X. 9(12). doi: 10.1371/journal.pcbi.1003386. Full text in Research Archive
• Halnes, Geir; Augustinaite, Sigita; Heggelund, Paul; Einevoll, Gaute Tomas & Migliore, Michele (2011). A Multi-Compartment Model for Interneurons in the Dorsal Lateral Geniculate Nucleus. PLoS Computational Biology. ISSN 1553-734X. 7(9). doi: 10.1371/journal.pcbi.1002160.

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• Halnes, Geir (2017). MOR ROM. Forlaget Oktober. ISBN 9788249517664. 62 p.

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• Halnes, Geir (2022). Biophysical modeling of brain tissue.
• Hagen, Espen; Ness, Torbjørn Vefferstad; Halnes, Geir & Einevoll, Gaute (2022). Brain signal predictions from multi-scale networks using a linearized framework.
• Ness, Torbjørn V; Halnes, Geir; Næss, Solveig; Pettersen, Klas Henning & Einevoll, Gaute (2022). Computing Extracellular Electric Potentials from Neuronal Simulations. In Negrello, M (Eds.), Computational Modelling of the Brain.. Springer. ISSN 978-3-030-89439-9. p. 179–199. doi: 10.1007/978-3-030-89439-9_8.
• Halnes, Geir (2021). Ion concentration dynamics in brain tissue: Effects on neurodynamics and extracellular potentials.
• Halnes, Geir; Tennøe, Simen; Einevoll, Gaute; Haug, Trude; Weltzien, Finn-Arne & Hodne, Kjetil (2019). A computational model of the spontaneous activity of gonadotrophin-releasing cells in the teleost fish models.
• Næss, Solveig; Halnes, Geir; Hagen, Espen; Hagler, Donald J.; Dale, Anders M. & Einevoll, Gaute [Show all 7 contributors for this article] (2019). Biophysical modelling of EEG signals.
• Sætra, Marte Julie; Einevoll, Gaute & Halnes, Geir (2019). A two-compartment neuron model with ion conservation and ion pumps.
• Halnes, Geir & Einevoll, Gaute (2019). LFPy - exercises.
• Halnes, Geir (2019). Modeling astrocytic regulation of extracellular ion concentrations and extracellular fields.
• Sætra, Marte Julie; Einevoll, Gaute T. & Halnes, Geir (2019). A two-compartment neuron model with ion conservation and ion pumps.
• Halnes, Geir; Tennøe, Simen; Haug, Trude Marie; Einevoll, Gaute T.; Weltzien, Finn-Arne & Hodne, Kjetil (2019). A computational model of the spontaneous activity of gonadotropin-releasing cells in the teleost fish medaka.
• Solbrå, Andreas Våvang; Bergersen, Aslak Wigdahl; van den Brink, Jonas; Malthe-Sørenssen, Anders; Einevoll, Gaute & Halnes, Geir (2018). Modeling electrodiffusion in the extracellular space around a morphologically detailed neuron.
• Halnes, Geir (2018). An electrodiffusive framework for large scale ion concentration dynamics in neural tissue. .
• Tennøe, Simen; Halnes, Geir & Einevoll, Gaute (2018). Uncertainpy: A Python toolbox for uncertainty quantification and sensitivity analysis of computational neuroscience models.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2017). Biophysical modeling of single neuron contributions to ECoG and EEG signals.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2017). Biophysical modeling of single-neuron contributions to ECoG and EEG signals.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders & Einevoll, Gaute (2017). Biophysical modeling of single-neuron contributions toECoG, EEG and MEG signals.
• Mobarhan, Milad; Halnes, Geir; Martínez-Cañada, Pablo; Hafting, Torkel; Fyhn, Marianne & Einevoll, Gaute (2017). Firing-rate Based Network Modeling of the dLGN Circuit: Effects of Cortical Feedback on Spatiotemporal Response Properties of Relay Cells .
• Halnes, Geir (2017). Naturvitenskapsmystikken. [Journal]. Oktoberjournal.
• Halnes, Geir (2017). Hjerneforskning.
• Halnes, Geir; Solbrå, Andreas Våvang; Mäki-Marttunen, Tuomo; Pettersen, Klas; Andreassen, Ole Andreas & Malthe-Sørensen, Anders [Show all 7 contributors for this article] (2017). Modelling electrical and chemical dynamics in brain tissue.
• Halnes, Geir; Mäki-Marttunen, Tuomo; Pettersen, Klas; Andreassen, Ole Andreas & Einevoll, Gaute T. (2017). Extracellular diffusion can introduce errors in current source density estimates.
• Halnes, Geir (2017). An electrodiffusive formalism for ion concentration dynamics and liquid flow in brain tissue.
• Solbrå, Andreas Våvang; Einevoll, Gaute; Malthe-Sørenssen, Anders & Halnes, Geir (2016). A novel electrodiffusive scheme for modeling ion dynamics in neural tissue.
• Næss, Solveig; Ness, Torbjørn Vefferstad; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2016). Biophysical modeling of single-neuron contributions to EEG and ECoG signals.
• Solbrå, Andreas Våvang; Malthe-Sørenssen, Anders; Einevoll, Gaute & Halnes, Geir (2016). A novel electrodiffusive scheme for modeling ion dynamics in neural tissue.
• Halnes, Geir; Mäki-Marttunen, Tuomo; Pettersen, Klas; Keller, Daniel; Andreassen, Ole Andreas & Einevoll, Gaute (2016). Effects of ionic diffusion on power spectra of local field potentials (LFP).
• Tennøe, Simen; Feinberg, Jonathan; Langtangen, Hans Petter; Einevoll, Gaute & Halnes, Geir (2016). UncertainPy: A Python toolbox for uncertainty quantification of computational neuroscience models.
• Tennøe, Simen; Halnes, Geir; Lepperød, Mikkel Elle; Feinberg, Jonathan; Einevoll, Gaute & Langtangen, Hans Petter (2016). UncertainPy: A Python toolbox for uncertainty quantification in neural and neural-network models.
• Tennøe, Simen; Langtangen, Hans Petter; Einevoll, Gaute & Halnes, Geir (2015). How uncertain are predictions from neuroscience models?
• Tennøe, Simen; Langtangen, Hans Petter; Einevoll, Gaute & Halnes, Geir (2015). When things go wrong: Uncertainty in neuroscience.
• Mäki-Marttunen, Tuomo; Halnes, Geir; Devor, Anna; Witoelar, Aree; Bettella, Francesco & Djurovic, Srdjan [Show all 10 contributors for this article] (2015). Towards biophysical psychiatry: A modeling approach for studying effects of schizophrenia-linked gens on single-neuron excitability.
• Halnes, Geir; Mäki-Marttunen, Tuomo; Pettersen, Klas Henning; Keller, Daniel; Andreassen, Ole Andreas & Einevoll, Gaute (2015). Can ionic diffusion have an effect on extracellular potentials?
• Mäki-Marttunen, Tuomo; Halnes, Geir; Devor, Anna; Witoelar, Aree; Bettella, Francesco & Djurovic, Srdjan [Show all 10 contributors for this article] (2015). Towards biophysical psychiatry: A modeling approach for studying effects of schizophrenia-linked genes on single-neuron excitability.
• Einevoll, Gaute & Halnes, Geir (2013). LGN Models. In Jaeger, Dieter & Jung, Ranu (Ed.), Encyclopedia of Computational Neuroscience. Springer Science+Business Media B.V.. ISSN 978-1461466741.
• Heiberg, Thomas; Hagen, Espen; Halnes, Geir; Plesser, Hans Ekkehard & Einevoll, Gaute Tomas (2013). Biophysically detailed network model for area summation in LGN relay cells.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas; Omholt, Stig W & Einevoll, Gaute Tomas (2013). An electrodiffusive model for neuronal and astrocytic ion concentration dynamics.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas; Omholt, Stig W & Einevoll, Gaute Tomas (2013). Electrodiffusive model for neuronal and astrocytic ion concentration dynamics.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas; Omholt, Stig W & Einevoll, Gaute Tomas (2013). An electrodiffusive model for neuronal and astrocytic ion concentration dynamics.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas Henning; Omholt, Stig W & Einevoll, Gaute Tomas (2012). Electrodiffusion in neural tissue at long timescales.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas Henning; Omholt, Stig W & Einevoll, Gaute Tomas (2012). Electrodiffusion in neural tissue at long timescales.
• Halnes, Geir; Østby, Ivar; Pettersen, Klas Henning; Omholt, Stig W & Einevoll, Gaute Tomas (2012). An electrodiffusive model for investigation of spatial buffering of potassium by glial cells.
• Halnes, Geir (2011). A multi-compartment model for interneurons in the dorsal lateral geniculate nucleus.
• Halnes, Geir; Augustinaite, Sigita; Heggelund, Paul; Einevoll, Gaute Tomas & Migliore, Michele (2011). A multi-compartment model for interneurons in the dorsal lateral geniculate nucleus.
• Halnes, Geir; Augustinaite, Sigita; Heggelund, Paul; Einevoll, Gaute & Migliore, Michele (2010). A compartmental model of an LGN interneuron.
• Halnes, Geir; Augustinaite, Sigita; Heggelund, Paul; Migliore, Michele & Einevoll, GT (2009). Compartmental modeling of LGN interneurons. Scandinavian Journal of Optometry and Visual Science. ISSN 1891-0882. 2.

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