Gaute Tomas Einevoll

• Hagen, Espen; Chambers, Anna; Pettersen, Klas H.; Einevoll, Gaute; Enger, Rune & Stasik, Alexander Johannes (2021). RippleNet: a Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection. Neuroinformatics.  ISSN 1539-2791. . doi: 10.1007/s12021-020-09496-2 Fulltekst i vitenarkiv. Vis sammendrag

  Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. Understanding their underlying mechanisms in healthy and pathological brain function and behaviour rely on accurate SPW-R detection. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) detection method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The approach contrasts conventional routines that typically relies on hand-crafted, heuristic feature extraction and often laborious manual curation. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events obtained under controlled conditions. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. Its output predictions can be interpreted as time-varying probabilities of SPW-R events for the duration of the inputs. A simple thresholding applied to the output probabilities is found to identify times of SPW-R events with high precision. The non-causal, or bidirectional variant of the proposed algorithm demonstrates consistently better accuracy compared to the causal, or unidirectional counterpart. Reference implementations of the algorithm, named ‘RippleNet’, are open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.

• Næss, Solveig; Halnes, Geir; Hagen, Espen; Hagler, Donald J.; Dale, Anders M.; Einevoll, Gaute & Ness, Torbjørn Vefferstad (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 Fulltekst i vitenarkiv.
• Buccino, Alessio Paolo & Einevoll, Gaute (2020). MEArec: A fast and customizable testbench simulator for ground-truth extracellular spiking activity. Neuroinformatics.  ISSN 1539-2791.  19, s 185- 204 . doi: 10.1007/s12021-020-09467-7 Fulltekst i vitenarkiv.
• Dai, Kael; Gratiy, Sergey L.; Billeh, Yazan; Xu, Richard; Cai, Binghuang; Cain, Nicholas; Rimehaug, Atle Eskeland; Stasik, Alexander Johannes; Einevoll, Gaute; Mihalas, Stefan; Koch, Christof & Arkhipov, Anton (2020). Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits. PLoS Computational Biology.  ISSN 1553-734X.  16(11) . doi: 10.1371/journal.pcbi.1008386 Fulltekst i vitenarkiv.
• 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, s 1- 18 . doi: 10.3389/fninf.2020.00011 Fulltekst i vitenarkiv.
• Geddes, Justen; Einevoll, Gaute; Acar, Evrim & Stasik, Alexander Johannes (2020). Multi-Linear Population Analysis (MLPA) of LFP Data Using Tensor Decompositions. Frontiers in Applied Mathematics and Statistics.  ISSN 2297-4687. . doi: 10.3389/fams.2020.00041 Fulltekst i vitenarkiv.
• Hagen, Espen; Chambers, Anna; Einevoll, Gaute; Pettersen, Klas Henning; Enger, Rune & Stasik, Alexander Johannes (2020). RippleNet: A Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection. bioRxiv - the preprint server for biology. . doi: 10.1101/2020.05.11.087874 Vis sammendrag

  Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. SPW-R detection typically relies on hand-crafted feature extraction, and laborious manual curation is often required. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. The output prediction can be interpreted as the time-varying probability of SPW-R events for the duration of the input. A simple thresholding applied to the output probabilities is found to identify times of events with high precision. The reference implementation of the algorithm, named ‘RippleNet’, is open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.

• Mäki-Marttunen, Tuomo; Iannella, Nicolangelo Libero; Edwards, Andrew; Einevoll, Gaute & Blackwell, Kim T. (2020). A unified computational model for cortical post-synaptic plasticity. eLIFE.  ISSN 2050-084X.  9, s 1- 37 . doi: 10.7554/eLife.55714 Fulltekst i vitenarkiv.
• Ness, Torbjørn Vefferstad; Halnes, Geir; Næss, Solveig; Pettersen, Klas Henning & Einevoll, Gaute (2020). Computing extracellular electric potentials from neuronal simulations. arXiv.org.  ISSN 2331-8422.
• Næss, Solveig; Halnes, Geir; Hagen, Espen; Hagler, Donald J.; Dale, Anders M.; Einevoll, Gaute & Ness, Torbjørn Vefferstad (2020). Biophysical modeling of the neural origin of EEG and MEG signals. BioRxiv.  ISSN 0362-4331. . doi: 10.1101/2020.07.01.181875
• Skaar, Jan-Eirik Welle; Stasik, Alexander Johannes; Hagen, Espen; Ness, Torbjørn V & Einevoll, Gaute (2020). Estimation of neural network model parameters from local field potentials (LFPs). PLoS Computational Biology.  ISSN 1553-734X.  16(3) . doi: 10.1371/journal.pcbi.1007725 Fulltekst i vitenarkiv.
• 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), s 1- 36 . doi: 10.1371/journal.pcbi.1007661 Fulltekst i vitenarkiv.
• Sætra, Marte Julie; Solbrå, Andreas Våvang; Devor, Anna; Sakadžić, Sava; Dale, Anders M. & Einevoll, Gaute (2020). Spatially Resolved Estimation of Metabolic Oxygen Consumption From Optical Measurements in Cortex. Neurophotonics.  ISSN 2329-423X.  7(3) . doi: 10.1117/1.NPh.7.3.035005 Fulltekst i vitenarkiv.
• Valstad, Mathias; Moberget, Torgeir; Roelfs, Daniël Thomas Heimen; Slapø, Nora Berz; Timpe, Clara Marie Fides; Beck, Dani; Richard, Geneviève; Sæther, Linn Sofie; Haatveit, Beathe Christin; Skaug, Knut-André; Nordvik, Jan Egil; Hatlestad-Hall, Christoffer; Einevoll, Gaute; Mäki-Marttunen, Tuomo; Westlye, Lars Tjelta; Jönsson, Erik Gunnar; Andreassen, Ole Andreas & Elvsåshagen, Torbjørn (2020). Experience-dependent modulation of the visual evoked potential: Testing effect sizes, retention over time, and associations with age in 415 healthy individuals. NeuroImage.  ISSN 1053-8119. . doi: 10.1016/j.neuroimage.2020.117302 Fulltekst i vitenarkiv.
• Einevoll, Gaute; Destexhe, Alain; Diesmann, Markus; Grün, Sonja; Jirsa, Viktori; de Kamps, Marc; Migliore, Michele; Ness, Torbjørn Vefferstad; Plesser, Hans Ekkehard & Schürmann, Felix (2019). The scientific case for brain simulations. Neuron.  ISSN 0896-6273.  102(4), s 735- 744 . doi: 10.1016/j.neuron.2019.03.027 Vis sammendrag

  A key element of the EU Human Brain Project (HBP) and other large-scale brain research projects is simulation of large-scale model networks of neurons. Here we argue why such simulations will likely be indispensable for bridging the scales between the neuron and system levels in the brain, and a set of brain simulators based on neuron models at different levels of biological detail should thus be developed. To allow for systematic refinement of candidate network models by comparison with experiments, the simulations should be multimodal in the sense that they should not only predict action potentials, but also electric, magnetic, and optical signals measured at the population and system levels.

• Halnes, Geir; Pettersen, Klas Henning; Øyehaug, Leiv; Rognes, Marie Elisabeth & Einevoll, Gaute (2019). Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow, In Hugues Berry & Maurizio De Pittà (ed.),  Computational Glioscience.  Springer Nature.  ISBN 978-3-030-00817-8.  Chapter.  s 363 - 391
• 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), s 1- 28 . doi: 10.1371/journal.pcbi.1006662 Fulltekst i vitenarkiv. Vis sammendrag

  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.

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• Einevoll, Gaute (2020, 30. januar). Deltagelse i Abels Tårn. [Radio].  NRK.
• Einevoll, Gaute (2020, 15. mai). Deltagelse i Abels Tårn. [Radio].  NRK.
• Einevoll, Gaute (2020, 04. september). Deltagelse i Abels Tårn. [Radio].  NRK.
• Einevoll, Gaute (2020, 27. november). Deltagelse i Abels Tårn. [Radio].  NRK.
• Einevoll, Gaute (2020, 30. juli). Deltagelse i Reiseradioen. [Radio].  NRK.
• Einevoll, Gaute (2020). Deltagelse i UNGFORSK,Vitenparken/NMBU (virtual).
• Einevoll, Gaute (2020, 06. januar). Deltagelse i podcasten Romkapsel. [Internett].  Podcast.
• Einevoll, Gaute (2020, 09. oktober). Deltager i podcasten Teknokratiet. [Internett].  Podcast: Teknokratiet.
• Einevoll, Gaute (2020, 01. august). Det har aldri vært mer aktuelt med en norsk astronaut enn n ̊a. [Fagblad].  Tekna Magasinet.
• Einevoll, Gaute (2020, 19. mars). Digital brains are key in understanding how the human brain works, and how it can be fixed when broken. [Internett].  Science Norway.
• Einevoll, Gaute (2020, 15. august). Kan du tenke deg tynn?. [Internett].  forskning.no.
• Einevoll, Gaute (2020, 25. september). Kan hjernen gå tom for plass?. [Internett].  forskning.no.
• Einevoll, Gaute (2020). Kan vi regne ut hvordan vi tenker?.
• Einevoll, Gaute (2020). Leveraging data, tools and models to gain new insights in mouse visual cortex.
• Einevoll, Gaute (2020, 14. januar). Nei, det er ingen krise i fysikken. [Internett].  forskning.no.
• Einevoll, Gaute (2020, 31. januar). Tar mikrofonen i egne hender. [Fagblad].  Forskerforum.
• Einevoll, Gaute (2020). Towards a multipurpose cortical network model.
• Einevoll, Gaute (2020). Towards multipurpose biophysics-based mathematical models of cortical circuits.
• Einevoll, Gaute (2020). Towards multipurpose biophysics-based mathematical models of cortical circuits.
• Einevoll, Gaute (2020). Towards multipurpose biophysics-based mathematical models of cortical circuits.
• Einevoll, Gaute (2020). Why model brain signals?.
• Einevoll, Gaute; Bjaalie, Jan G. & Plesser, Hans Ekkehard (2020, 12. oktober). Om hjerneforskning og Human Brain Project. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Carroll, Sean M (2020, 19. april). On the physics world view and the interpretation of quantum mechanics. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Egeland, Kjølv (2020, 23. august). Om faren for atomkrig. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Elgarøy, Øystein (2020, 03. mai). Om universet og Big Bang teorien. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Grødeland, Gunnveig (2020, 06. desember). Om vaksiner, spesielt koronavaksiner. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Grøn, Øyvind (2020, 06. juni). Om Einstein og relativitetsteoriene hans. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Grøn, Øyvind (2020, 27. september). Om Einstein og resten av fysikken hans. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Lönn-Stensrud, Jessica (2020, 17. mai). Om bakterier. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & McFadden, Johnjoe (2020, 14. juni). On quantum biology. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Newth, Eirik (2020, 24. januar). Om romfart. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Nyborg, Karine (2020, 22. mars). Om klimaøkonomi. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Pettersen, Klas Henning (2020, 05. juli). Deltagelse i podcasten NORDE. [Internett].  Podcast.
• Einevoll, Gaute & Pettersen, Klas Henning (2020, 31. august). Deltagelse i podcasten NORDE. [Internett].  Podcast.
• Einevoll, Gaute & Raklev, Are (2020, 12. juli). Om partikkelfysikk og jakten på Higgs-bosonet. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Rose, Sunniva (2020, 13. januar). Om kjernekraft og forskningsformiding. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Røyne, Anja (2020, 27. desember). Om løsninger på klimakrisen. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Samset, Bjørn Hallvard (2020, 08. mars). Om klimafysikk. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute; Samset, Bjørn Hallvard; Sverdrup-Thygeson, Anne; Svihus, Birger; Østby, Hilde; Røyne, Anja & Øygard, Svein Harald (2020, 10. februar). Om å gi alle jordas mennesker gode liv uten å ødelegge miljøet. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Sejnowski, Terrence J. (2020, 21. februar). On AI and the underlying algorithms. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Spurkland, Anne (2020, 26. juni). Om coronaviruset. En oppdatering – med Anne Spurkland #21. [Internett].  Vett og Viten.
• Einevoll, Gaute & Spurkland, Anne (2020, 26. mars). Om koronaviruset – Med Anne Spurkland #14. [Internett].  Vett og Viten.
• Einevoll, Gaute & Støstad, Hanna Nyborg (2020, 09. august). Om evolusjonsteorien og naturens mangfold. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute; Tunstad, Erik & Riiser-Larsen, Vibeke (2020, 29. november). Om neandertalerne. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Einevoll, Gaute & Østby, Hilde (2020, 31. mai). Om kreativitet. [Internett].  Podcast: Vett og vitenskap med Gaute Einevoll.
• Iannella, Nicolangelo Libero; Prydz, Kristian; Malthe-Sørensen, Anders; Einevoll, Gaute & Fyhn, Marianne (2020). A framework for modelling neuronal-ECM signalling.
• Mäki-Marttunen, Tuomo; Edwards, Andrew G; Einevoll, Gaute & Blackwell, Kim T (2020). Biochemically detailed single compartmental model for neocortical postsynaptic long term plasticity.
• Berthet, Pierre; Einevoll, Gaute & Ness, Torbjørn V (2019). Excitability of cortical neurons by electrical stimulation from the cortical surface.
• Cañada, Pablo Martinez; Ness, Torbjørn V; Einevoll, Gaute; Fellin, Tommaso & Panzeri, Stefano (2019). Computing the Electroencephalogram (EEG) from Point-Neuron Networks.
• Einevoll, Gaute (2019, 26. februar). Deltagelse i Abels Tårn (NRK P2, NRK2). [TV].  NRK.
• Einevoll, Gaute (2019, 13. september). Deltagelse i Abels Tårn, NRK P2. [Radio].  NRK.
• Einevoll, Gaute (2019, 08. mai). Deltagelse i Slettan & Martin tar helg i NRK P1. [Radio].  NRK.
• Einevoll, Gaute (2019). Deltagelse i paneldebatt om hjernen og den nevrovitenskapelige revolusjon.
• Einevoll, Gaute (2019, 16. mai). Deltagelse i podcasten Mentaltrener. [Internett].  Podcast.
• Einevoll, Gaute (2019, 24. september). Dommer i Forsker Grand Prix. [TV].  NRK.
• Einevoll, Gaute (2019). Evaluating the merit of candidate brain models with brain simulations.
• Einevoll, Gaute (2019, 07. mai). Hjerneforsker: Du lager din egen, personlige modell av virkeligheten. [Internett].  forskning.no.
• Einevoll, Gaute (2019, 01. juni). Kunstig syn - hjelper blinde å se igjen. [Fagblad].  Optikeren.
• Einevoll, Gaute (2019, 28. april). Lager kunstig tale av hjernesignaler. [Internett].  NRK Viten.
• Einevoll, Gaute (2019). Modeling brain signals.
• Einevoll, Gaute (2019). Neuroscience with both hands: Bridging scales with mathematics.
• Einevoll, Gaute (2019). Physics of the mind.
• Einevoll, Gaute (2019, 31. oktober). Podcast #1: Splitter ny podcast i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Einevoll, Gaute (2019). The scientific case for brain simulations.
• Einevoll, Gaute (2019). The too large role of statistics in neuroscience.
• Einevoll, Gaute (2019). Towards a brain theory.
• Einevoll, Gaute (2019). Towards biophysical psychiatry – basic principles and transformative potential.
• Einevoll, Gaute (2019). Towards multipurpose biophysics-based mathematical models of cortical circuits.
• Einevoll, Gaute (2019). Using AI to interpret electrical brain signals. Bernstein Feature 2019.
• Einevoll, Gaute & Hagen, Espen (2019). Tutorial: Biophysical modeling of extracellular potentials (using LFPy).
• Einevoll, Gaute & Nordengen, Kaja (2019, 06. november). Podcast #2 om hjernen i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Einevoll, Gaute & Sverdrup-Thygeson, Anne (2019, 28. november). Podcast #6 om insekter i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Einevoll, Gaute & Svihus, Birger (2019, 11. november). Podcast #3 om mat i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Einevoll, Gaute & Østby, Hilde (2019, 17. november). Podcast #5 om hukommelse i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Einevoll, Gaute & Øygard, Svein Harald (2019, 11. desember). Podcast #7 om å være Islands sentralbanksjef i podcasten Vett og vitenskap med Gaute Einevoll. [Internett].  Podcast.
• Fyhn, Marianne & Einevoll, Gaute (2019). Hjernen digitaliseres - hvordan moderne datateknologi brukes til å forstå biologiske mekanismer i hjernen.
• Hagen, Espen; Næss, Solveig; Ness, Torbjørn V & Einevoll, Gaute (2019). LFPy: Multimodal Modeling of Extracellular Neuronal Recordings in Python.
• Hagen, Espen; Stasik, Alexander Johannes; Billeh, Yazan N.; Siegle, Joshua H.; Dai, Kael; Rimehaug, Atle Eskeland; Ness, Torbjørn V; Røe, Malin Benum; Fyhn, Marianne; Hafting, Torkel; Koch, Christof; Olsen, Shawn R.; Einevoll, Gaute & Arkhipov, Anton (2019). Comparing spikes and the local field potential (LFP) in V1 between experimental data and a comprehensive biophysical model.
• Hagen, Espen; Stasik, Alexander Johannes; Billeh, Yazan; Siegle, Joshua H.; Dai, Kael; Rimehaug, Atle Eskeland; Ness, Torbjørn V; Røe, Malin Benum; Fyhn, Marianne; Hafting, Torkel; Koch, Christof; Olsen, Shawn R.; Einevoll, Gaute & Arkhipov, Anton (2019). Comparing spikes and the local field potential (LFP) in V1 between experimental data and a comprehensive biophysical model.
• Halnes, Geir & Einevoll, Gaute (2019). LFPy - exercises.
• 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.
• Iannella, Nicolangelo Libero; Prydz, Kristian; Malthe-Sørensen, Anders; Einevoll, Gaute & Fyhn, Marianne (2019). A new framework for modelling neural-ECM signaling.
• Iannella, Nicolangelo Libero; Prydz, Kristian; Malthe-Sørensen, Anders; Einevoll, Gaute & Fyhn, Marianne (2019). A new framework for modelling neural-ECM signalling and interaction.

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