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Published online by Cambridge University Press:  30 May 2024

Geir Halnes
Affiliation:
Norwegian University of Life Sciences
Torbjørn V. Ness
Affiliation:
Norwegian University of Life Sciences
Solveig Næss
Affiliation:
Universitetet i Oslo
Espen Hagen
Affiliation:
Universitetet i Oslo
Klas H. Pettersen
Affiliation:
The Norwegian Artificial Intelligence Research Consortium
Gaute T. Einevoll
Affiliation:
Norwegian University of Life Sciences
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Chapter
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Electric Brain Signals
Foundations and Applications of Biophysical Modeling
, pp. 343 - 374
Publisher: Cambridge University Press
Print publication year: 2024

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References

Aberra, A. S., Wang, B., Grill, W. M. & Peterchev, A. V. (2020), ‘Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons’, Brain Stimulation 13(1), 175189.CrossRefGoogle ScholarPubMed
Adrian, E. (1928), The Basis of Sensation, W. W. Norton & Co, New York.Google Scholar
Adrian, E. D. & Moruzzi, G. (1939), ‘Impulses in the pyramidal tract’, The Journal of Physiology 97(2), 153199.CrossRefGoogle ScholarPubMed
Agudelo-Toro, A. & Neef, A. (2013), ‘Computationally efficient simulation of electrical activity at cell membranes interacting with self-generated and externally imposed electric fields’, Journal of Neural Engineering 10(2), 026019.CrossRefGoogle ScholarPubMed
Aguilella, V., Mafé, S. & Pellicer, J. (1987), ‘On the nature of the diffusion potential derived from Nernst-Planck flux equations by using the electroneutrality assumption’, Electrochimica Acta 32(3), 483488.CrossRefGoogle Scholar
Ahlfors, S. P. & Wreh, C. II (2015), ‘Modeling the effect of dendritic input location on MEG and EEG source dipoles’, Medical & Biological Engineering & Computing 53(9), 879887.CrossRefGoogle ScholarPubMed
Akalin Acar, Z. & Makeig, S. (2013), ‘Effects of forward model errors on EEG source localization’, Brain Topography 26(3), 378396.CrossRefGoogle ScholarPubMed
Akar, N. A., Cumming, B., Karakasis, V., Kusters, A., Klijn, W., Peyser, A. & Yates, S. (2019), ‘Arbor – a morphologically-detailed neural network simulation library for contemporary high-performance computing architectures’, in 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), IEEE.Google Scholar
Alcaraz, A., Nestorovich, E. M., López, M. L., García-Giménez, E., Bezrukov, S. M. & Aguilella, V. M. (2009), ‘Diffusion, exclusion, and specific binding in a large channel: a study of ompf selectivity inversion’, Biophysical Journal 96(1), 5666.CrossRefGoogle Scholar
Allken, V., Chepkoech, J.-L., Einevoll, G. T. & Halnes, G. (2014), ‘The subcellular distribution of T-type Ca2+ channels in interneurons of the lateral geniculate nucleus’, PLoS ONE 9(9), e107780.CrossRefGoogle ScholarPubMed
Almog, M. & Korngreen, A. (2014), ‘A quantitative description of dendritic conductances and its application to dendritic excitation in layer 5 pyramidal neurons’, Journal of Neuroscience 34(1), 182196.CrossRefGoogle ScholarPubMed
Almog, M. & Korngreen, A. (2016), ‘Is realistic neuronal modeling realistic?’, Journal of Neurophysiology 116(5), 21802209.CrossRefGoogle ScholarPubMed
Amari, S. (1977), ‘Dynamics of pattern formation in lateral-inhibition type neural fields’, Biological Cybernetics 27, 7787.CrossRefGoogle ScholarPubMed
Amini, M., Hisdal, J. & Kalvøy, H. (2018), ‘Applications of bioimpedance measurement techniques in tissue engineering’, Journal of Electrical Bioimpedance 9(1), 142158.CrossRefGoogle ScholarPubMed
Amit, D. J. & Brunel, N. (1997), ‘Dynamics of a recurrent network of spiking neurons before and following learning’, Network: Computation in Neural Systems 8(4), 373404.CrossRefGoogle Scholar
Amsalem, O., Eyal, G., Rogozinski, N., Gevaert, M., Kumbhar, P., Schürmann, F. & Segev, I. (2020), ‘An efficient analytical reduction of detailed nonlinear neuron models’, Nature Communications 11(1), 113.CrossRefGoogle ScholarPubMed
Anastassiou, C. A., Buzsaki, C., Koch, C., Quiroga, R. & Panzeri, S. (2013), ‘Biophysics of extracellular spikes’, Principles of Neural Coding 15, 146.Google Scholar
Anastassiou, C. A. & Koch, C. (2015), ‘Ephaptic coupling to endogenous electric field activity: why bother?’, Current Opinion in Neurobiology 31, 95103.CrossRefGoogle ScholarPubMed
Anastassiou, C. A., Perin, R., Buzsáki, G., Markram, H. & Koch, C. (2015), ‘Cell type- and activity-dependent extracellular correlates of intracellular spiking’, Journal of Neurophysiology 114(1), 608623.CrossRefGoogle ScholarPubMed
Andersen, R. A., Musallam, S. & Pesaran, B. (2004), ‘Selecting the signals for a brain-machine interface’, Current Opinion in Neurobiology 14(6), 720726.CrossRefGoogle ScholarPubMed
Anderson, T. R., Huguenard, J. R. & Prince, D. A. (2010), ‘Differential effects of Na+–K+ atpase blockade on cortical layer V neurons’, The Journal of Physiology 588(22), 44014414.CrossRefGoogle ScholarPubMed
Antic, S. D., Zhou, W.-L., Moore, A. R., Short, S. M. & Ikonomu, K. D. (2010), ‘The decade of the dendritic NMDA spike’, Journal of Neuroscience Research 88(14), 29913001.CrossRefGoogle ScholarPubMed
Antonio, L. L., Anderson, M. L., Angamo, E. A., Gabriel, S., Klaft, Z.-J., Liotta, A., Salar, S., Sandow, N. & Heinemann, U. (2016), ‘In vitro seizure like events and changes in ionic concentration’, Journal of Neuroscience Methods 260, 3344.CrossRefGoogle ScholarPubMed
Avery, J., Dowrick, T., Faulkner, M., Goren, N. & Holder, D. (2017), ‘A versatile and reproducible multi-frequency electrical impedance tomography system’, Sensors 17(2), 280.CrossRefGoogle ScholarPubMed
Ayata, C. & Lauritzen, M. (2015), ‘Spreading depression, spreading depolarizations, and the cerebral vasculature’, Physiological Reviews 95(3), 953993.CrossRefGoogle ScholarPubMed
Azevedo, F. A., Carvalho, L. R., Grinberg, L. T., Farfel, J. M., Ferretti, R. E., Leite, R. E., Filho, W. J., Lent, R. & Herculano-Houzel, S. (2009), ‘Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain’, The Journal of Comparative Neurology 513(5), 532541.CrossRefGoogle Scholar
Bakkum, D. J., Obien, M. E. J., Radivojevic, M., Jäckel, D., Frey, U., Takahashi, H. & Hierlemann, A. (2018), ‘The axon initial segment is the dominant contributor to the neuron’s extracellular electrical potential landscape’, Advanced Biosystems 3(2), 1800308.CrossRefGoogle Scholar
Bangera, N. B., Schomer, D. L., Dehghani, N., Ulbert, I., Cash, S., Papavasiliou, S., Eisenberg, S. R., Dale, A. M. & Halgren, E. (2010), ‘Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution’, Journal of Computational Neuroscience 29(3), 371387.CrossRefGoogle ScholarPubMed
Baranauskas, G., Maggiolini, E., Vato, A., Angotzi, G., Bonfanti, A., Zambra, G., Spinelli, A. & Fadiga, L. (2012), ‘Origins of 1/f2 scaling in the power spectrum of intracortical local field potential’, Journal of Neurophysiology 107(3), 984994.CrossRefGoogle ScholarPubMed
Baratham, V. L., Dougherty, M. E., Hermiz, J., Ledochowitsch, P., Maharbiz, M. M. & Bouchard, K. E. (2022), ‘Columnar localization and laminar origin of cortical surface electrical potentials’, The Journal of Neuroscience 42(18), 37333748.CrossRefGoogle ScholarPubMed
Barker, A. T., Jalinous, R. & Freeston, I. L. (1985), ‘Non-invasive magnetic stimulation of human motor cortex’, Lancet 1(8437), 11061107.CrossRefGoogle ScholarPubMed
Barry, P. H. & Lynch, J. W. (1991), ‘Liquid junction potentials and small cell effects in patch-clamp analysis’, The Journal of Membrane Biology 121(2), 101117.CrossRefGoogle ScholarPubMed
Barthó, P., Hirase, H., Monconduit, L., Zugaro, M., Harris, K. D. & Buzsaki, G. (2004), ‘Characterization of neocortical principal cells and interneurons by network interactions and extracellular features’, Journal of Neurophysiology 92(1), 600608.CrossRefGoogle ScholarPubMed
Baumann, S. B., Wozny, D. R., Kelly, S. K. & Meno, F. M. (1997), ‘The electrical conductivity of human cerebrospinal fluid at body temperature’, IEEE Transactions on Biomedical Engineering 44(3), 220223.CrossRefGoogle ScholarPubMed
Bazelot, M., Dinocourt, C., Cohen, I. & Miles, R. (2010), ‘Unitary inhibitory field potentials in the CA3 region of rat hippocampus’, Journal of Physiology 588(12), 20772090.CrossRefGoogle ScholarPubMed
Beaulieu, C. (1993), ‘Numerical data on neocortical neurons in adult rat, with special reference to the GABA population’, Brain Research 609(1–2), 284292.CrossRefGoogle Scholar
Bechhoefer, J. (2011), ‘Kramers–Kronig, Bode, and the meaning of zero’, American Journal of Physics 79(10), 10531059.CrossRefGoogle Scholar
Bédard, C. & Destexhe, A. (2008), ‘A modified cable formalism for modeling neuronal membranes at high frequencies’, Biophysical Journal 94(4), 11331143.CrossRefGoogle ScholarPubMed
Bédard, C. & Destexhe, A. (2009), ‘Macroscopic models of local field potentials and the apparent 1/f noise in brain activity’, Biophysical Journal 96(7), 25892603.CrossRefGoogle ScholarPubMed
Bedárd, C. & Destexhe, A. (2012), Local field potentials, in Brette, R. & Destexhe, A., eds., Handbook of Neural Activity Measurement, Cambridge University Press, Cambridge, pp. 136191.CrossRefGoogle Scholar
Bédard, C., Kröger, H. & Destexhe, A. (2006), ‘Does the 1/f frequency scaling of brain signals reflect self-organized critical states?’, Physical Review Letters 97(11), 118102.CrossRefGoogle ScholarPubMed
Beggs, J. M. & Plenz, D. (2003), ‘Neuronal avalanches in neocortical circuits’, The Journal of Neuroscience 23(35), 1116711177.CrossRefGoogle ScholarPubMed
Belitski, A., Gretton, A., Magri, C., Murayama, Y., Montemurro, M. A., Logothetis, N. K. & Panzeri, S. (2008), ‘Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information’, Journal of Neuroscience 28(22), 56965709.CrossRefGoogle ScholarPubMed
Beltrachini, L. (2019), ‘A finite element solution of the forward problem in EEG for multipolar sources’, IEEE Transactions on Neural Systems and Rehabilitation Engineering 27(3), 368377.CrossRefGoogle ScholarPubMed
Benabid, A. L., Chabardes, S., Mitrofanis, J. & Pollak, P. (2009), ‘Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson’s disease’, The Lancet Neurology 8(1), 6781.CrossRefGoogle ScholarPubMed
Bender, K. J. & Trussell, L. O. (2012), ‘The physiology of the axon initial segment’, Annual Review of Neuroscience 35, 249265.CrossRefGoogle ScholarPubMed
Berens, P., Keliris, G. A., Ecker, A. S., Logothetis, N. K. & Tolias, A. S. (2008), ‘Comparing the feature selectivity of the gamma-band of the local field potential and the underlying spiking activity in primate visual cortex’, Frontiers in Systems Neuroscience 2, 2.CrossRefGoogle ScholarPubMed
Bereshpolova, Y., Amitai, Y., Gusev, A. G., Stoelzel, C. R. & Swadlow, H. A. (2007), ‘Dendritic backpropagation and the state of the awake neocortex’, Journal of Neuroscience 27(35), 93929399.CrossRefGoogle ScholarPubMed
Berger, H. (1929), ‘Über das Elektrenkephalogramm des Menschen’, Archiv für Psychiatrie und Nervenkrankheiten 87(35), 527570.CrossRefGoogle Scholar
Biasiucci, A., Franceschiello, B. & Murray, M. M. (2019), ‘Electroencephalography’, Current Biology 29(3), R80R85.CrossRefGoogle ScholarPubMed
Billeh, Y. N., Cai, B., Gratiy, S. L., Dai, K., Iyer, R., Gouwens, N. W., Abbasi-Asl, R., Jia, X., Siegle, J. H., Olsen, S. R., Koch, C., Mihalas, S. & Arkhipov, A. (2020), ‘Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex’, Neuron 106(3), 388403.CrossRefGoogle ScholarPubMed
Birbaumer, N., Elbert, T., Canavan, A. G. & Rockstroh, B. (1990), ‘Slow potentials of the cerebral cortex and behavior’, Physiological Reviews 70(1), 141.CrossRefGoogle ScholarPubMed
Bishop, C., Powell, S., Rutt, D. & Browse, N. (1986), ‘Transcranial doppler measurement of middle cerebral artery blood flow velocity: a validation study’, Stroke 17(5), 913915.CrossRefGoogle ScholarPubMed
Blagoev, K., Mihaila, B., Travis, B., Alexandrov, L., Bishop, A., Ranken, D., Posse, S., Gasparovic, C., Mayer, A., Aine, C., Ulbert, I., Morita, M., Müller, W., Connor, J. & Halgren, E. (2007), ‘Modelling the magnetic signature of neuronal tissue’, NeuroImage 37(1), 137148.CrossRefGoogle ScholarPubMed
Bliss, T. V. & Lømo, T. (1973), ‘Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path’, The Journal of Physiology 232(2), 331356.CrossRefGoogle ScholarPubMed
Blomquist, P., Devor, A., Indahl, U. G., Ulbert, I., Einevoll, G. T. & Dale, A. M. (2009), ‘Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminar-electrode recordings in the rat barrel system’, PLoS Computational Biology 5(3), e1000328.CrossRefGoogle ScholarPubMed
Bloomfield, S., Hamos, J. & Sherman, S. (1987), ‘Passive cable properties and morphological correlates of neurones in the lateral geniculate nucleus of the cat’, The Journal of Physiology 383(1), 653692.CrossRefGoogle ScholarPubMed
Bojak, I., Oostendorp, T. F., Reid, A. T. & Kötter, R. (2010), ‘Connecting mean field models of neural activity to EEG and fMRI data’, Brain Topography 23(2), 139149.CrossRefGoogle ScholarPubMed
Bokil, H., Laaris, N., Blinder, K., Ennis, M. & Keller, A. (2001), ‘Ephaptic interactions in the mammalian olfactory system’, The Journal of Neuroscience 21(20), RC173.CrossRefGoogle ScholarPubMed
Borges, F. S., Moreira, J. V. S., Takarabe, L. M., Lytton, W. W. & Dura-Bernal, S. (2022), ‘Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE’, Frontiers in Neuroinformatics 16: 884245.CrossRefGoogle ScholarPubMed
Bos, H., Diesmann, M. & Helias, M. (2016), ‘Identifying anatomical origins of coexisting oscillations in the cortical microcircuit’, PLoS Computational Biology 12(10), e1005132.CrossRefGoogle ScholarPubMed
Bossetti, C. A., Birdno, M. J. & Grill, W. M. (2008), ‘Analysis of the quasi-static approximation for calculating potentials generated by neural stimulation’, Journal of Neural Engineering 5(1), 4453.CrossRefGoogle ScholarPubMed
Bowen, W. R. & Welfoot, J. S. (2002), ‘Modelling the performance of membrane nanofiltration—critical assessment and model development’, Chemical Engineering Science 57(7), 11211137.CrossRefGoogle Scholar
Bower, J. M. & Beeman, D. (1998), The Book of GENESIS, Springer, New York.CrossRefGoogle Scholar
Brazier, M. A. B. (1949), ‘The electrical fields at the surface of the head during sleep’, Electroencephalography and Clinical Neurophysiology 1(1–4), 195204.CrossRefGoogle Scholar
Brazier, M. A. B. (1963), The Discoverers of the Steady Potentials of the Brain: Caton and Beck, University of California. Brain Research Institute, Los Angeles.Google Scholar
Brazier, M. A. B. (1966), ‘A study of the electrical fields at the surface of the head’, American Journal of EEG Technology 6(4), 114128.CrossRefGoogle Scholar
Bregman, H. (2021), The Hidden Life of the Basal Ganglia: At the Base of Brain and Mind, MIT Press, Cambridge, MA.CrossRefGoogle Scholar
Brette, R. & Destexhe, A., eds. (2012), Handbook of Neural Activity Measurement, Cambridge University Press, Cambridge.CrossRefGoogle Scholar
Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J. M., Diesmann, M., Morrison, A., Goodman, P. H., Harris, F. C., Zirpe, M., Natschläger, T., Pecevski, D., Ermentrout, B., Djurfeldt, M., Lansner, A., Rochel, O., Vieville, T., Muller, E., Davison, A. P., El Boustani, S. & Destexhe, A. (2007), ‘Simulation of networks of spiking neurons: a review of tools and strategies’, Journal of Computational Neuroscience 23(3), 349398.CrossRefGoogle ScholarPubMed
Brinchmann, C. (2021), Exploring the effect of ionic diffusion on extracellular potentials in the brain, Master’s thesis, Norwegian University of Life Sciences, Ås.Google Scholar
Brunel, N. (2000), ‘Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons’, Journal of Computational Neuroscience 8, 183208.CrossRefGoogle ScholarPubMed
Brunel, N. (2013), Modeling point neurons: From Hodgkin-Huxley to integrate-and-fire, in Schutter, E. D., ed., ‘Computational Modeling Methods for Neuroscientists’, MIT Press, Cambridge, MA, pp. 161186.Google Scholar
Brunel, N. & van Rossum, M. C. W. (2007), ‘Lapicque’s 1907 paper: from frogs to integrate-and-fire’, Biological Cybernetics 97(5–6), 337339.CrossRefGoogle ScholarPubMed
Bruyns-Haylett, M., Luo, J., Kennerley, A. J., Harris, S., Boorman, L., Milne, E., Vautrelle, N., Hayashi, Y., Whalley, B. J., Jones, M., Berwick, J., Riera, J. & Zheng, Y. (2017), ‘The neurogenesis of P1 and N1: a concurrent EEG/LFP study’, NeuroImage 146, 575588.CrossRefGoogle ScholarPubMed
Buccino, A. P., Damart, T., Bartram, J., Mandge, D., Xue, X., Zbili, M., Gänswein, T., Jaquier, A., Emmenegger, V., Markram, H., Hierlemann, A. & Geit, W. V. (2022), ‘A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays’, bioRxiv.CrossRefGoogle Scholar
Buccino, A. P. & Einevoll, G. T. (2021), ‘Mearec: A fast and customizable testbench simulator for ground-truth extracellular spiking activity’, Neuroinformatics 19(1), 185204.CrossRefGoogle ScholarPubMed
Buccino, A. P., Garcia, S. & Yger, P. (2022), ‘Spike sorting: new trends and challenges of the era of high-density probes’, Progress in Biomedical Engineering 4(2), 022005.CrossRefGoogle Scholar
Buccino, A. P., Kordovan, M., Ness, T. V., Merkt, B., Häfliger, P. D., Fyhn, M., Cauwenberghs, G., Rotter, S. & Einevoll, G. T. (2018), ‘Combining biophysical modeling and deep learning for multi-electrode array neuron localization and classification’, Journal of Neurophysiology 120(3), 12121232.CrossRefGoogle Scholar
Buccino, A. P., Kuchta, M., Jæger, K. H., Ness, T. V., Berthet, P., Mardal, K.-A., Cauwenberghs, G. & Tveito, A. (2019), ‘How does the presence of neural probes affect extracellular potentials?’, Journal of Neural Engineering 16(2), 026030.CrossRefGoogle ScholarPubMed
Buccino, A. P., Yuan, X., Emmenegger, V., Xue, X., Gänswein, T. & Hierlemann, A. (2022), ‘An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays’, Journal of Neural Engineering 19(2), 026026.CrossRefGoogle ScholarPubMed
Buitenweg, J. R., Rutten, W. L. C. & Marani, E. (2003), ‘Geometry-based finite-element modeling of the electrical contact between a cultured neuron and a microelectrode’, IEEE Transactions on Biomedical Engineering 50(4), 501509.CrossRefGoogle Scholar
Butson, C. R. & McIntyre, C. C. (2008), ‘Current steering to control the volume of tissue activated during deep brain stimulation’, Brain Stimulation 1(1), 715.CrossRefGoogle ScholarPubMed
Buzsáki, G., Anastassiou, C. A. & Koch, C. (2012), ‘The origin of extracellular fields and currents–EEG, ECoG, LFP and spikes’, Nature Reviews. Neuroscience 13(6), 40720.CrossRefGoogle ScholarPubMed
Buzsaki, G., Bickford, R. G., Ponomareff, G., Thal, L. J., Mandel, R. & Gage, F. H. (1988), ‘Nucleus basalis and thalamic control of neocortical activity in the freely moving rat’, The Journal of Neuroscience 8(11), 40074026.CrossRefGoogle ScholarPubMed
Cagnan, H., Denison, T., McIntyre, C. & Brown, P. (2019), ‘Emerging technologies for improved deep brain stimulation’, Nature Biotechnology 37(9), 10241033.CrossRefGoogle ScholarPubMed
Cain, N., Iyer, R., Koch, C. & Mihalas, S. (2016), ‘The computational properties of a simplified cortical column model’, PLoS Computational Biology 12(9), e1005045.CrossRefGoogle ScholarPubMed
Campagnola, L., Seeman, S. C., Chartrand, T., Kim, L., Hoggarth, A., Gamlin, C., Ito, S., Trinh, J., Davoudian, P., Radaelli, C., Kim, M.-H., Hage, T., Braun, T., Alfiler, L., Andrade, J., Bohn, P., Dalley, R., Henry, A., Kebede, S., Mukora, A., Sandman, D., Williams, G., Larsen, R., Teeter, C., Daigle, T. L., Berry, K., Dotson, N., Enstrom, R., Gorham, M., Hupp, M., Lee, S. D., Ngo, K., Nicovich, R., Potekhina, L., Ransford, S., Gary, A., Goldy, J., McMillen, D., Pham, T., Tieu, M., Siverts, L. A., Walker, M., Farrell, C., Schroedter, M., Slaughterbeck, C., Cobb, C., Ellenbogen, R., Gwinn, R. P., Keene, C. D., Ko, A. L., Ojemann, J. G., Silbergeld, D. L., Carey, D., Casper, T., Crichton, K., Clark, M., Dee, N., Ellingwood, L., Gloe, J., Kroll, M., Sulc, J., Tung, H., Wadhwani, K., Brouner, K., Egdorf, T., Maxwell, M., McGraw, M., Pom, C. A., Ruiz, A., Bomben, J., Feng, D., Hejazinia, N., Shi, S., Szafer, A., Wakeman, W., Phillips, J., Bernard, A., Esposito, L., D’Orazi, F. D., Sunkin, S., Smith, K., Tasic, B., Arkhipov, A., Sorensen, S., Lein, E., Koch, C., Murphy, G., Zeng, H. & Jarsky, T. (2022), ‘Local connectivity and synaptic dynamics in mouse and human neocortex’, Science 375, eabj5861.CrossRefGoogle ScholarPubMed
Camuñas-Mesa, L. A. & Quiroga, R. Q. (2013), ‘A detailed and fast model of extracellular recordings’, Neural Computation 25(5), 11911212.CrossRefGoogle ScholarPubMed
Carnevale, T. & Hines, M. L. (2009), The Neuron Book, Cambridge University Press, Cambridge.Google Scholar
Caspers, H., Speckmann, E.-J. & Lehmenkühler, A. (1984), ‘Electrogenesis of slow potentials of the brain’, in Elbert, T., Rockstroh, B., Lutzenberger, W. & Birbaumer, N., eds., Self-Regulation of the Brain and Behavior, Springer Berlin, Heidelberg, pp. 2641.CrossRefGoogle Scholar
Caton, R. (1875), ‘The electric currents of the brain’, British Medical Journal 2, 278.Google Scholar
Catterall, W. A., Raman, I. M., Robinson, H. P., Sejnowski, T. J. & Paulsen, O. (2012), ‘The Hodgkin-Huxley heritage: from channels to circuits’, Journal of Neuroscience 32(41), 1406414073.CrossRefGoogle ScholarPubMed
Cavallari, S., Panzeri, S. & Mazzoni, A. (2014), ‘Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks’, Frontiers in Neural Circuits 8, 12.CrossRefGoogle ScholarPubMed
Chatzikalymniou, A. P. & Skinner, F. K. (2018), ‘Deciphering the contribution of oriens-lacunosum/moleculare (OLM) cells to intrinsic theta rhythms using biophysical local field potential (LFP) models’, eNeuro 5(4), ENEURO.0146–18.2018.CrossRefGoogle ScholarPubMed
Chen, D. & Eisenberg, R. (1993), ‘Charges, currents, and potentials in ionic channels of one conformation’, Biophysical Journal 64(5), 14051421.CrossRefGoogle ScholarPubMed
Chen, K. C. & Nicholson, C. (2000), ‘Spatial buffering of potassium ions in brain extracellular space’, Biophysical Journal 78(6), 27762797.CrossRefGoogle ScholarPubMed
Clark, G. M., Black, R., Dewhurst, D. J., Forster, I. C., Patrick, J. F. & Tong, Y. C. (1977), ‘A multiple-electrode hearing prosthesis for cochlea implantation in deaf patients’, Medical Progress through Technology 5(3), 127140.Google ScholarPubMed
Clark, J. W. & Plonsey, R. (1970), ‘A mathematical study of nerve fiber interaction’, Biophysical Journal 10(10), 937957.CrossRefGoogle ScholarPubMed
Cohen, D. (1968), ‘Magnetoencephalography: evidence of magnetic fields produced by alpha-rhythm currents’, Science 161(3843), 784786.CrossRefGoogle ScholarPubMed
Cohen, D. (1972), ‘Magnetoencephalography: detection of the brain’s electrical activity with a superconducting magnetometer’, Science 175(4022), 664666.CrossRefGoogle ScholarPubMed
Cohen, M. X. (2017), ‘Where Does EEG Come From and What Does It Mean?’, Trends in Neurosciences 40(4), 208218.CrossRefGoogle ScholarPubMed
Coombes, S., beim Graben, P., Potthast, R. & Wright, J. (2014), Neural Fields: Theory and Applications, Springer Berlin, Heidelberg.CrossRefGoogle Scholar
Cooper, R. (1946), ‘The electrical properties of salt-water solutions over the frequency range 1–4000 mc/s’, Journal of the Institution of Electrical Engineers-Part III: Radio and Communication Engineering 93(22), 6975.Google Scholar
Cordingley, G. & Somjen, G. (1978), ‘The clearing of excess potassium from extracellular space in spinal cord and cerebral cortex’, Brain Research 151(2), 291306.CrossRefGoogle ScholarPubMed
Cressman, J. R., Ullah, G., Ziburkus, J., Schiff, S. J. & Barreto, E. (2009), ‘The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dynamics’, Journal of Computational Neuroscience 26(2), 15970.CrossRefGoogle ScholarPubMed
Cserpan, D., Meszéna, D., Wittner, L., Tóth, K., Ulbert, I., Somogyvári, Z. & Wójcik, D. K. (2017), ‘Revealing the distribution of transmembrane currents along the dendritic tree of a neuron from extracellular recordings’, eLife 6, e29384.CrossRefGoogle ScholarPubMed
Dai, K., Gratiy, S. L., Billeh, Y. N., Xu, R., Cai, B., Cain, N., Rimehaug, A. E., Stasik, A. J., Einevoll, G. T., Mihalas, S., Koch, C. & Arkhipov, A. (2020), ‘Brain Modeling ToolKit: an open source software suite for multiscale modeling of brain circuits’, PLoS Computational Biology 16(11), e1008386.CrossRefGoogle ScholarPubMed
Dale, A. M., Fischl, B. & Sereno, M. I. (1999), ‘Cortical surface-based analysis: I. Segmentation and Surface Reconstruction’, NeuroImage 9(2), 179194.CrossRefGoogle ScholarPubMed
Darbas, M. & Lohrengel, S. (2019), ‘Review on mathematical modelling of electroencephalography (EEG)’, Jahresbericht der Deutschen Mathematiker-Vereinigung 121(1), 339.CrossRefGoogle Scholar
David, O. & Friston, K. J. (2003), ‘A neural mass model for MEG/EEG: coupling and neuronal dynamics’, NeuroImage 20(3), 17431755.CrossRefGoogle ScholarPubMed
Davison, A. P., Brüderle, D., Eppler, J. Kremkow, J., Muller, E., Pecevski, D., Perrinet, L. & Yger, P. (2008), ‘PyNN: a common interface for neuronal network simulators’, Frontiers in Neuroinformatics 2, 388.CrossRefGoogle Scholar
Dayan, P. & Abbott, L. F. (2001), Theoretical Neuroscience, MIT Press, Cambridge, MA.Google Scholar
de Curtis, M., Uva, L., Gnatkovsky, V. & Librizzi, L. (2018), ‘Potassium dynamics and seizures: why is potassium ictogenic?’, Epilepsy Research 143, 5059.CrossRefGoogle ScholarPubMed
de Kamps, M. (2013), ‘A generic approach to solving jump diffusion equations with applications to neural populations’. arXiv. https://doi.org/10.48550/arXiv.1309.1654.CrossRefGoogle Scholar
de Munck, J. C. & Peters, M. J. (1993), ‘A fast method to compute the potential in the multisphere model’, IEEE Transactions on Biomedical Engineering 40(11), 11661174.CrossRefGoogle ScholarPubMed
De Schutter, E. (2009), Computational Modeling Methods for Neuroscientists, MIT Press, Cambridge, MA.CrossRefGoogle Scholar
Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M. & Friston, K. (2008), ‘The dynamic brain: from spiking neurons to neural masses and cortical fields’, PLoS Computational Biology 4, e1000092.CrossRefGoogle ScholarPubMed
Denker, M., Einevoll, G., Franke, F., Grün, S., Hagen, E., Kerr, J., Nawrot, M., Ness, T. B. & Wójcik, T. W. D. (2012), ‘Report from 1st INCF workshop on validation of analysis methods’, Technical report, International Neuroinformatics Coordinating Facility (INCF).Google Scholar
Derksen, H. E. & Verveen, A. A. (1966), ‘Fluctuations of resting neural membrane potential’, Science 151(716), 13881389.CrossRefGoogle ScholarPubMed
Destexhe, A., Contreras, D. & Steriade, M. (1999), ‘Spatiotemporal analysis of local field potentials and unit discharges in cat cerebral cortex during natural wake and sleep states’, Journal of Neuroscience 19(11), 45954608.CrossRefGoogle ScholarPubMed
Destexhe, A. & Huguenard, J. R. (2009), ‘Modeling voltage-dependent channels’, in Schutter, E. D., ed., Computational Modeling Methods for Neuroscientists MIT Press, Cambridge, MA, pp. 107138.CrossRefGoogle Scholar
Destexhe, A., Mainen, Z. F. & Sejnowski, T. J. (1994), ‘Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism’, Journal of Computational Neuroscience 1(3), 195230.CrossRefGoogle ScholarPubMed
Deweese, M. R. & Zador, A. M. (2011), ‘Whole cell recordings from neurons in the primary auditory cortex of rat in response to pure tones of different frequency and amplitude, along with recordings of nearby local field potential (lfp)’ CRCNS. https://crcns.org/data-sets/ac/ac-2.Google Scholar
Diba, K., Lester, H. A. & Koch, C. (2004), ‘Intrinsic noise in cultured hippocampal neurons: experiment and modeling.’, Journal of Neuroscience 24(43), 97239733.CrossRefGoogle ScholarPubMed
Dietzel, I., Heinemann, U., Hofmeier, G. & Lux, H. (1982), ‘Stimulus-induced changes in extracellular Na+ and Cl- concentration in relation to changes in the size of the extracellular space’, Experimental Brain Research 46(1), 7384.CrossRefGoogle ScholarPubMed
Dietzel, I., Heinemann, U. & Lux, H. (1989), ‘Relations between slow extracellular potential changes, glial potassium buffering, and electrolyte and cellular volume changes during neuronal hyperactivity in cat’, Glia 2(1), 2544.CrossRefGoogle ScholarPubMed
Donahue, M. J., Kaszas, A., Turi, G. F., Rózsa, B., Slézia, A., Vanzetta, I., Katona, G., Bernard, C., Malliaras, G. G. & Williamson, A. (2018), ‘Multimodal characterization of neural networks using highly transparent electrode arrays’, eNeuro 5(6), ENEURO.0187-18.2018.CrossRefGoogle ScholarPubMed
Dowrick, T., Blochet, C. & Holder, D. (2015), ‘In vivo bioimpedance measurement of healthy and ischaemic rat brain: implications for stroke imaging using electrical impedance tomography’, Physiological Measurement 36(6), 12731282.CrossRefGoogle ScholarPubMed
Druckmann, S., Banitt, Y., Gidon, A., Schuermann, F., Markram, H. & Segev, I. (2007), ‘A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data’, Frontiers in Neurosci 1(1), 718.CrossRefGoogle ScholarPubMed
Drukarch, B., Holland, H. A., Velichkov, M., Geurts, J. J., Voorn, P., Glas, G. & de Regt, H. W. (2018), ‘Thinking about the nerve impulse: a critical analysis of the electricity-centered conception of nerve excitability’, Progress in Neurobiology 169, 172185.CrossRefGoogle ScholarPubMed
Dubey, A. & Ray, S. (2016), ‘Spatial spread of local field potential is band-pass in the primary visual cortex’, Journal of Neurophysiology 116(4), 19861999.CrossRefGoogle ScholarPubMed
Dubey, A. & Ray, S. (2019), ‘Cortical electrocorticogram (ECoG) is a local signal’, Journal of Neuroscience 39(22), 42994311.CrossRefGoogle ScholarPubMed
Dubey, A. & Ray, S. (2020), ‘Comparison of tuning properties of gamma and high-gamma power in local field potential (LFP) versus electrocorticogram (ECoG) in visual cortex’, Scientific Reports 10(1), 5422.CrossRefGoogle Scholar
Dura-Bernal, S., Griffith, E. Y., Barczak, A., O’Connell, M. N., McGinnis, T., Schroeder, C. E., Lytton, W. W., Lakatos, P. & Neymotin, S. A. (2023), ‘Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics’, Cell Reports 42(11), 113378.CrossRefGoogle ScholarPubMed
Dura-Bernal, S., Neymotin, S. A., Suter, B. A., Dacre, J., Moreira, J. V., Urdapilleta, E., Schiemann, J., Duguid, I., Shepherd, G. M. & Lytton, W. W. (2023), ‘Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics’, Cell Reports 42(6), 112574.CrossRefGoogle ScholarPubMed
Dura-Bernal, S., Suter, B. A., Gleeson, P., Cantarelli, M., Quintana, A., Rodriguez, F., Kedziora, D. J., Chadderdon, G. L., Kerr, C. C., Neymotin, S. A., McDougal, R. A., Hines, M., Shepherd, G. M. & Lytton, W. W. (2019), ‘NetPyNE, a tool for data-driven multiscale modeling of brain circuits’, eLife 8: e44494.CrossRefGoogle ScholarPubMed
Ecker, A. S., Berens, P., Keliris, G. A., Bethge, M., Logothetis, N. K. & Tolias, A. S. (2010), ‘Decorrelated neuronal firing in cortical microcircuits’, Science 327(5965), 584587.CrossRefGoogle ScholarPubMed
Einevoll, G. T., Destexhe, A., Diesmann, M., Grün, S., Jirsa, V., de Kamps, M., Migliore, M., Ness, T. V., Plesser, H. E. & Schürmann, F. (2019), ‘The scientific case for brain simulations’, Neuron 102(4), 735744.CrossRefGoogle ScholarPubMed
Einevoll, G. T., Franke, F., Hagen, E., Pouzat, C. & Harris, K. D. (2012), ‘Towards reliable spike-train recordings from thousands of neurons with multielectrodes’, Current Opinion in Neurobiology 22(1), 1117.CrossRefGoogle ScholarPubMed
Einevoll, G. T., Kayser, C., Logothetis, N. K. & Panzeri, S. (2013), ‘Modelling and analysis of local field potentials for studying the function of cortical circuits’, Nature Reviews Neuroscience 14(11), 770785.CrossRefGoogle ScholarPubMed
Einevoll, G. T., Lindén, H., Tetzlaff, T., Łęski, S. & Pettersen, K. H. (2013), ‘Local field potential: biophysical origin and analysis’, in Quiroga, R. Q. & Panzeri, S., eds., Principles of Neural Coding, CRC Press, Taylor & Francis Group, Boca Raton, pp. 3759.Google Scholar
Einevoll, G. T., Pettersen, K. H., Devor, A., Ulbert, I., Halgren, E. & Dale, A. M. (2007), ‘Laminar population analysis: estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex’, Journal of Neurophysiology 97(3), 21742190.CrossRefGoogle ScholarPubMed
Eisenberg, R. S. & Johnson, E. A. (1970), ‘Three-dimensional electrical field problems in physiology’, Progress in Biophysics and Molecular Biology 20, 165.CrossRefGoogle Scholar
Eisinger, R. S., Cernera, S., Gittis, A., Gunduz, A. & Okun, M. S. (2019), ‘A review of basal ganglia circuits and physiology: application to deep brain stimulation’, Parkinsonism and Related Disorders 59, 920.CrossRefGoogle ScholarPubMed
Elbohouty, M. (2013), Electrical conductivity of brain cortex slices in seizing and non-seizing states, PhD thesis, The University of Waikato.Google Scholar
Ellingsrud, A. J., Dukefoss, D. B., Enger, R., Halnes, G., Pettersen, K. & Rognes, M. E. (2022), ‘Validating a computational framework for ionic electrodiffusion with cortical spreading depression as a case study’, eNeuro 9(2), ENEURO.0408-21.2022.Google ScholarPubMed
Ellingsrud, A. J., Solbrå, A., Einevoll, G. T., Halnes, G. & Rognes, M. E. (2020), ‘Finite element simulation of ionic electrodiffusion in cellular geometries’, Frontiers in Neuroinformatics 14, 11.CrossRefGoogle ScholarPubMed
Emmenegger, V., Obien, M. E. J., Franke, F. & Hierlemann, A. (2019), ‘Technologies to study action potential propagation with a focus on hd-meas’, Frontiers in Cellular Neuroscience 13, 159.CrossRefGoogle ScholarPubMed
Enger, R., Tang, W., Vindedal, G. F., Jensen, V., Helm, P. J., Sprengel, R., Looger, L. L. & Nagelhus, E. A. (2015), ‘Dynamics of ionic shifts in cortical spreading depression’, Cerebral Cortex 25(11), 44694476.CrossRefGoogle ScholarPubMed
Ermentrout, G. B. & Terman, D. H. (2010), Mathematical Foundations of Neuroscience, Springer-Verlag GmbH, New York.CrossRefGoogle Scholar
Eyal, G., Verhoog, M. B., Testa-Silva, G., Deitcher, Y., Lodder, J. C., Benavides-Piccione, R., Morales, J., DeFelipe, J., de Kock, C. P., Mansvelder, H. D. & Segev, I. (2016), ‘Unique membrane properties and enhanced signal processing in human neocortical neurons’, eLife 5: e16553.CrossRefGoogle ScholarPubMed
Fee, M. S., Mitra, P. P. & Kleinfeld, D. (1996), ‘Variability of extracellular spike waveforms of cortical neurons’, Journal of Neurophysiology 76(6), 38233833.CrossRefGoogle ScholarPubMed
Feldberg, S. (2000), ‘On the dilemma of the use of the electroneutrality constraint in electrochemical calculations’, Electrochemistry Communications 2(7), 453456.CrossRefGoogle Scholar
Ferguson, K. A., Chatzikalymniou, A. P. & Skinner, F. K. (2017), ‘Combining theory, model, and experiment to explain how intrinsic theta rhythms are generated in an in vitro whole hippocampus preparation without oscillatory inputs’, eNeuro 4: ENEURO.0131–17.2017.CrossRefGoogle Scholar
Ferguson, K. A., Huh, C. Y. L., Amilhon, B., Manseau, F., Williams, S. & Skinner, F. K. (2015), ‘Network models provide insights into how oriens-lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations’, Frontiers in Systems Neuroscience 9, 110.CrossRefGoogle ScholarPubMed
Fernández-Ruiz, A., Muñoz, S., Sancho, M., Makarova, J., Makarov, V. A. & Herreras, O. (2013), ‘Cytoarchitectonic and dynamic origins of giant positive local field potentials in the dentate gyrus’, The Journal of Neuroscience 33(39), 1551815532.CrossRefGoogle ScholarPubMed
Fishman, H. M. (1973), ‘Relaxation spectra of potassium channel noise from squid axon membranes’, Proceedings of the National Academy of Sciences of the United States of America 70(3), 876879.CrossRefGoogle ScholarPubMed
Foster, K. & Schwan, H. (1989), ‘Dielectric properties of tissues and biological materials: a critical review’, Critical Reviews in Biomedical Engineering 17(1), 25104.Google ScholarPubMed
Franks, W., Schenker, I., Schmutz, P. & Hierlemann, A. (2005), ‘Impedance characterization and modeling of electrodes for biomedical applications’, IEEE Transactions on Biomedical Engineering 52(7), 12951302.CrossRefGoogle ScholarPubMed
Fransson, P., Metsäranta, M., Blennow, M., Åden, U., Lagercrantz, H. & Vanhatalo, S. (2012), ‘Early development of spatial patterns of power-law frequency scaling in fMRI resting-state and EEG data in the newborn brain’, Cerebral Cortex 23(3), 638646.CrossRefGoogle ScholarPubMed
Freeman, J. & Nicholson, C. (1975), ‘Experimental optimization of current source-density technique for anuran cerebellum’, Journal of Neurophysiology 38(2), 369382.CrossRefGoogle ScholarPubMed
Freeman, W. J. (2009), ‘Deep analysis of perception through dynamic structures that emerge in cortical activity from self-regulated noise’, Cognitive Neurodynamics 3(1), 105116.CrossRefGoogle ScholarPubMed
Freeman, W. J., Holmes, M. D., Burke, B. C. & Vanhatalo, S. (2003), ‘Spatial spectra of scalp EEG and EMG from awake humans’, Clinical Neurophysiology 114(6), 10531068.CrossRefGoogle ScholarPubMed
Freeman, W. J., Rogers, L. J., Holmes, M. D. & Silbergeld, D. L. (2000), ‘Spatial spectral analysis of human electrocorticograms including the alpha and gamma bands’, Journal of Neuroscience Methods 95(2), 111121.CrossRefGoogle ScholarPubMed
Freestone, D. R., Karoly, P. J., Peterson, A. D., Kuhlmann, L., Lai, A., Goodarzy, F. & Cook, M. J. (2015), ‘Seizure prediction: science fiction or soon to become reality?’, Current Neurology and Neuroscience Reports 15(11), 73.CrossRefGoogle ScholarPubMed
Fröhlich, F. & McCormick, D. A. (2010), ‘Endogenous electric fields may guide neocortical network activity’, Neuron 67(1), 12943.CrossRefGoogle ScholarPubMed
Fujisawa, S., Amarasingham, A., Harrison, M. T. & Buzsáki, G. (2008), ‘Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex’, Nature Neuroscience 11(7), 823833.CrossRefGoogle ScholarPubMed
Gabriel, C. (1996), ‘Compilation of the dielectric properties of body tissues at rf and microwave frequencies’, Technical report, King’s College London (United Kingdom) Department of Physics.CrossRefGoogle Scholar
Gabriel, S., Lau, R. W. & Gabriel, C. (1996), ‘The dielectric properties of biological tissues: II. measurements in the frequency range 10 Hz to 20 GHz’, Physics in Medicine and Biology 41(11), 22512269.CrossRefGoogle ScholarPubMed
Gardner-Medwin, A. (1980), ‘Membrane transport and solute migration affecting the brain cell microenvironment’, Neurosciences Research Program Bulletin 18, 208226.Google Scholar
Gardner-Medwin, A. (1983), ‘Analysis of potassium dynamics in mammalian brain tissue’, The Journal of Physiology 335, 393426.CrossRefGoogle ScholarPubMed
Gardner-Medwin, A., Coles, J., Tsacopoulos, M. (1981), ‘Clearance of extracellular potassium: evidence for spatial buffering by glial cells in the retina of the drone’, Brain Research 209(2), 452457.CrossRefGoogle ScholarPubMed
Geisler, C. D. & Gerstein, G. L. (1961), ‘The surface EEG in relation to its sources’, Electroencephalography and Clinical Neurophysiology 13(6), 927934.CrossRefGoogle Scholar
Gentet, L. J., Avermann, M., Matyas, F., Staiger, J. F. & Petersen, C. C. (2010), ‘Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice’, Neuron 65(3), 422435.CrossRefGoogle ScholarPubMed
Gentet, L. J., Stuart, G. J. & Clements, J. D. (2000), ‘Direct measurement of specific membrane capacitance in neurons’, Biophysical Journal 79(1), 314320.CrossRefGoogle ScholarPubMed
Gerstein, G. L. (1960), ‘Analysis of firing patterns in single neurons’, Science 131(3416), 18111812.CrossRefGoogle ScholarPubMed
Gerstner, W., Kistler, W. M., Naud, R. & Paninsky, L. (2014), Neuronal Dynamics, Cambridge University Press, Cambridge.CrossRefGoogle Scholar
Geselowitz, D. B. (1970), ‘On the magnetic field generated outside an inhomogeneous volume conductor by internal current sources’, IEEE Transactions on Magnetics 6(2), 346347.CrossRefGoogle Scholar
Geselowitz, D. B. (1967), ‘On bioelectric potentials in an inhomogeneous volume conductor’, Biophysical Journal 7(1), 111.CrossRefGoogle Scholar
Głąbska, H., Chintaluri, C. & Wójcik, D. K. (2017), ‘Collection of simulated data from a thalamocortical network model’, Neuroinformatics 15(1), 8799.CrossRefGoogle Scholar
Głąbska, H., Potworowski, J., Łęski, S. & Wójcik, D. K. (2014), ‘Independent components of neural activity carry information on individual populations’, PLoS ONE 9(8), e105071.CrossRefGoogle ScholarPubMed
Głąbska, H. T., Norheim, E., Devor, A., Dale, A. M., Einevoll, G. T. & Wójcik, D. K. (2016), ‘Generalized laminar population analysis (gLPA) for interpretation of multielectrode data from cortex’, Frontiers in Neuroinformatics 10, 1.CrossRefGoogle ScholarPubMed
Glomb, K., Cabral, J., Cattani, A., Mazzoni, A., Raj, A. & Franceschiello, B. (2022), ‘Computational models in electroencephalography’, Brain Topography 35(1), 142161.CrossRefGoogle ScholarPubMed
Goethals, S. & Brette, R. (2020), ‘Theoretical relation between axon initial segment geometry and excitability’, eLife 9: e53432.CrossRefGoogle ScholarPubMed
Gold, C., Girardin, C. C., Martin, K. A. C. & Koch, C. (2009), ‘High-amplitude positive spikes recorded extracellularly in cat visual cortex’, Journal of Neurophysiology 102(6), 33403351.CrossRefGoogle ScholarPubMed
Gold, C., Henze, D. A. & Koch, C. (2007), ‘Using extracellular action potential recordings to constrain compartmental models’, Journal of Computational Neuroscience 23(1), 3958.CrossRefGoogle ScholarPubMed
Gold, C., Henze, D. A., Koch, C. & Buzsáki, G. (2006), ‘On the origin of the extracellular action potential waveform: a modeling study’, Journal of Neurophysiology 95(5), 31133128.CrossRefGoogle ScholarPubMed
Goldman, D. E. (1943), ‘Potential, impedance, and rectification in membranes’, The Journal of General Physiology 27(1), 3760.CrossRefGoogle ScholarPubMed
Goldwyn, J. H. & Rinzel, J. (2016), ‘Neuronal coupling by endogenous electric fields: cable theory and applications to coincidence detector neurons in the auditory brain stem’, Journal of Neurophysiology 115(4), 20332051.CrossRefGoogle Scholar
Goto, T., Hatanaka, R., Ogawa, T., Sumiyoshi, A., Riera, J. & Kawashima, R. (2010), ‘An evaluation of the conductivity profile in the somatosensory barrel cortex of Wistar rats’, Journal of Neurophysiology 104(6), 33883412.CrossRefGoogle ScholarPubMed
Gouwens, N. W., Berg, J., Feng, D., Sorensen, S. A., Zeng, H., Hawrylycz, M. J., Koch, C. & Arkhipov, A. (2018), ‘Systematic generation of biophysically detailed models for diverse cortical neuron types’, Nature Communications 9(1), 710.CrossRefGoogle ScholarPubMed
Gramfort, A., Papadopoulo, T., Olivi, E. & Clerc, M. (2010), ‘OpenMEEG: opensource software for quasistatic bioelectromagnetics’, BioMedical Engineering OnLine 9: 45.CrossRefGoogle ScholarPubMed
Gratiy, S. L., Halnes, G., Denman, D., Hawrylycz, M. J., Koch, C., Einevoll, G. T. & Anastassiou, C. A. (2017), ‘From Maxwell’s equations to the theory of current-source density analysis’, European Journal of Neuroscience 45(8), 10131023.CrossRefGoogle Scholar
Grodzinsky, F. (2011), Fields, Forces, and Flows in Biological Systems., Garland Science, Taylor & Francis Group, London & New York.CrossRefGoogle Scholar
Grynszpan, F. & Geselowitz, D. B. (1973), ‘Model studies of the magnetocardiogram’, Biophysical Journal 13(9), 911925.CrossRefGoogle ScholarPubMed
Hagen, E., Dahmen, D., Stavrinou, M. L., Lindén, H., Tetzlaff, T., Van Albada, S. J., Grün, S., Diesmann, M. & Einevoll, G. T. (2016), ‘Hybrid scheme for modeling local field potentials from point-neuron networks’, Cerebral Cortex 26(12), 44614496.CrossRefGoogle ScholarPubMed
Hagen, E., Fossum, J. C., Pettersen, K. H., Alonso, J. M., Swadlow, H. A. & Einevoll, G. T. (2017), ‘Focal local field potential signature of the single-axon monosynaptic thalamocortical connection’, Journal of Neuroscience 37(20), 51235143.CrossRefGoogle ScholarPubMed
Hagen, E., Magnusson, S. H., Ness, T. V., Halnes, G., Babu, P. N., Linssen, C., Morrison, A. & Einevoll, G. T. (2022), ‘Brain signal predictions from multi-scale networks using a linearized framework’, PLOS Computational Biology 18(8), e1010353.CrossRefGoogle ScholarPubMed
Hagen, E., Næss, S., Ness, T. V. & Einevoll, G. T. (2018), ‘Multimodal modeling of neural network activity: computing LFP, ECoG, EEG, and MEG signals with LFPy 2.0’, Frontiers in Neuroinformatics 12, 92.CrossRefGoogle ScholarPubMed
Hagen, E. & Ness, T. V. (2023), ‘LFPy/ElectricBrainSignals: ElectricBrainSignals-1.0.0rc1’. Zenodo. https://doi.org/10.5281/zenodo.8255422.CrossRefGoogle Scholar
Hagen, E., Ness, T. V., Khosrowshahi, A., Sørensen, C., Fyhn, M., Hafting, T., Franke, F. & Einevoll, G. T. (2015), ‘ViSAPy: A Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms’, Journal of Neuroscience Methods 245, 182204.CrossRefGoogle ScholarPubMed
Haj-Yasein, N. N., Jensen, V., Østby, I., Omholt, S. W., Voipio, J., Kaila, K., Ottersen, O. P., Hvalby, Ø. & Nagelhus, E. A. (2012), ‘Aquaporin-4 regulates extracellular space volume dynamics during high-frequency synaptic stimulation: a gene deletion study in mouse hippocampus’, Glia 60(6), 867874.CrossRefGoogle ScholarPubMed
Hallermann, S., de Kock, C. P. J., Stuart, G. J. & Kole, M. H. P. (2012), ‘State and location dependence of action potential metabolic cost in cortical pyramidal neurons’, Nature Neuroscience 15(7), 10071014.CrossRefGoogle Scholar
Hallett, M. (2007), ‘Transcranial magnetic stimulation: a primer’, Neuron 55(2), 187199.CrossRefGoogle ScholarPubMed
Halnes, G., Augustinaite, S., Heggelund, P., Einevoll, G. T. & Migliore, M. (2011), ‘A multi-compartment model for interneurons in the dorsal lateral geniculate nucleus’, PLoS Computational Biology 7(9), e1002160.CrossRefGoogle ScholarPubMed
Halnes, G., Mäki-Marttunen, T., Keller, D., Pettersen, K. H., Andreassen, O. A. & Einevoll, G. T. (2016), ‘Effect of ionic diffusion on extracellular potentials in neural tissue’, PLoS Computational Biology 12(11), e1005193.CrossRefGoogle ScholarPubMed
Halnes, G., Mäki-Marttunen, T., Pettersen, K. H., Andreassen, O. A. & Einevoll, G. T. (2017), ‘Ion diffusion may introduce spurious current sources in current-source density (CSD) analysis’, Journal of Neurophysiology 118(1), 114120.CrossRefGoogle ScholarPubMed
Halnes, G., Østby, I., Pettersen, K. H., Omholt, S. W. & Einevoll, G. T. (2013), ‘Electrodiffusive model for astrocytic and neuronal ion concentration dynamics’, PLoS Computational Biology 9(12), e1003386.CrossRefGoogle ScholarPubMed
Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J. & Lounasmaa, O. V. (1993), ‘Magnetoencephalography – theory, instrumentation, and applications to noninvasive studies of the working human brain’, Reviews of Modern Physics 65(413), 414460.CrossRefGoogle Scholar
Hansen, A. J. & Zeuthen, T. (1981), ‘Extracellular ion concentrations during spreading depression and ischemia in the rat brain cortex’, Acta Physiologica Scandinavica 113(4), 437445.CrossRefGoogle ScholarPubMed
Hari, R. & Ilmoniemi, R. J. (1986), ‘Cerebral magnetic fields’, Critical Reviews in Biomedical Engineering 14(2), 93126.Google ScholarPubMed
Harnett, M. T., Magee, J. C. & Williams, S. R. (2015), ‘Distribution and function of HCN channels in the apical dendritic tuft of neocortical pyramidal neurons’, Journal of Neuroscience 35(3), 10241037.CrossRefGoogle ScholarPubMed
Harris, K. D., Henze, D. A., Csicsvari, J., Hirase, H. & Buzsaki, G. (2000), ‘Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements’, Journal of Neurophysiology 84(1), 401414.CrossRefGoogle ScholarPubMed
Harris, K. D. & Shepherd, G. M. G. (2015), ‘The neocortical circuit: themes and variations’, Nature Neuroscience 18(2), 170181.CrossRefGoogle ScholarPubMed
Hasted, J., Ritson, D. & Collie, C. (1948), ‘Dielectric properties of aqueous ionic solutions. parts I and II’, The Journal of Chemical Physics 16(1), 121.CrossRefGoogle Scholar
Havstad, J. W. (1976), Electrical Impedance of Cerebral Cortex: An Experimental and Theoretical Investigation, Stanford University.Google Scholar
Hay, E., Hill, S., Schürmann, F., Markram, H. & Segev, I. (2011), ‘Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties’, PLoS Computational Biology 7(7), e1002107.CrossRefGoogle ScholarPubMed
Heinemann, U., Schaible, H. G. & Schmidt, R. F. (1990), ‘Changes in extracellular potassium concentration in cat spinal cord in response to innocuous and noxious stimulation of legs with healthy and inflamed knee joints’, Experimental Brain Research 79(2), 283292.CrossRefGoogle ScholarPubMed
Helias, M., Kunkel, S., Masumoto, G., Igarashi, J., Eppler, J. M., Ishii, S., Fukai, T., Morrison, A. & Diesmann, M. (2012), ‘Supercomputers ready for use as discovery machines for neuroscience’, Frontiers in Neuroinformatics 6, 26.CrossRefGoogle ScholarPubMed
Helias, M., Tetzlaff, T. & Diesmann, M. (2013), ‘Echoes in correlated neural systems’, New Journal of Physics 15(2), 023002.CrossRefGoogle Scholar
Helmholtz, H. (1853), ‘Ueber einige gesetze der vertheilung elektrischer ströme in körperlichen leitern, mit anwendung auf die thierisch-elektrischen versuche (schluss.)’, Annalen der Physik und Chemie 165(7), 353377.CrossRefGoogle Scholar
Henderson, P. (1907), ‘An equation for the calculation of potential difference at any liquid junction boundary’, Zeitschrift für Physikalische Chemie 59, 118127.CrossRefGoogle Scholar
Henriquez, C. S. (1993), ‘Simulating the electrical behavior of cardiac tissue using the bidomain model’, Critical Reviews in Biomedical Engineering 21(1), 177.Google ScholarPubMed
Henze, D. A., Borhegy, Z., Csicsvari, J., Mamiya, A., Harris, K. D. & Buzsaki, G. (2000), ‘Intracellular features predicted by extracellular recordings in the hippocampus in vivo’, Journal of Neuroscience 84(1), 390400.Google ScholarPubMed
Herculano-Houzel, S. (2009), ‘The human brain in numbers: a linearly scaled-up primate brain’, Frontiers in Human Neuroscience 3, 31.CrossRefGoogle Scholar
Herrera, B., Sajad, A., Woodman, G. F., Schall, J. D. & Riera, J. J. (2020), ‘A minimal biophysical model of neocortical pyramidal cells: implications for frontal cortex microcircuitry and field potential generation’, Journal of Neuroscience 40(44), 85138529.CrossRefGoogle ScholarPubMed
Herrera, B., Westerberg, J. A., Schall, M. S., Maier, A., Woodman, G. F., Schall, J. D. & Riera, J. J. (2022), ‘Resolving the mesoscopic missing link: biophysical modeling of eeg from cortical columns in primates’, NeuroImage 263, 119593.CrossRefGoogle ScholarPubMed
Herreras, O. & Makarova, J. (2020), ‘Mechanisms of the negative potential associated with Leão’s spreading depolarization: a history of brain electrogenesis’, Journal of Cerebral Blood Flow & Metabolism 40(10), 19341952.CrossRefGoogle ScholarPubMed
Herreras, O. & Somjen, G. (1993), ‘Analysis of potential shifts associated with recurrent spreading depression and prolonged unstable spreading depression induced by microdialysis of elevated K+ in hippocampus of anesthetized rats’, Brain Research 610(2), 283294.CrossRefGoogle ScholarPubMed
Hill, M., Rios, E., Sudhakar, S. K., Roossien, D. H., Caldwell, C., Cai, D., Ahmed, O. J., Lempka, S. F. & Chestek, C. A. (2018), ‘Quantitative simulation of extracellular single unit recording from the surface of cortex’, Journal of Neural Engineering 15(5), 056007.CrossRefGoogle ScholarPubMed
Hille, B. (2001), Ion Channels of Excitable Membranes, 3rd ed., Sinauer Associates: Sunderland, MA.Google Scholar
Hines, M. L. & Carnevale, N. T. (1997), ‘The NEURON simulation environment’, Neural Computation 9(6), 11791209.CrossRefGoogle ScholarPubMed
Hines, M. L. & Carnevale, N. T. (2001), ‘Neuron: a tool for neuroscientists’, The Neuroscientist 7(2), 123135.CrossRefGoogle ScholarPubMed
Hines, M. L., Davison, A. P. & Muller, E. (2009), ‘NEURON and Python’, Frontiers in Neuroinformatics 3, 1.CrossRefGoogle ScholarPubMed
Hines, M. L., Morse, T., Migliore, M., Carnevale, N. T. & Shepherd, G. M. (2004), ‘ModelDB: a database to support computational neuroscience’, Journal of Computational Neuroscience 17(1), 711.CrossRefGoogle ScholarPubMed
Hjorth, J., Hellgren Kotaleski, J. & Kozlov, A. (2021), ‘Predicting synaptic connectivity for large-scale microcircuit simulations using Snudda’, Neuroinformatics 19(4), 685701.CrossRefGoogle ScholarPubMed
Hladky, S. B. & Barrand, M. A. (2014), ‘Mechanisms of fluid movement into, through and out of the brain: evaluation of the evidence’, Fluids and Barriers of the CNS 11(1), 132.CrossRefGoogle ScholarPubMed
Hodgkin, A. L. & Huxley, A. F. (1952 a), ‘A quantitative description of membrane current and its application to conduction and excitation in nerve’, The Journal of Physiology 117(4), 500544.CrossRefGoogle ScholarPubMed
Hodgkin, A. L. & Huxley, A. F. (1952 b), ‘The components of membrane conductance in the giant axon of loligo’, The Journal of Physiology 116(4), 473496.CrossRefGoogle ScholarPubMed
Hodgkin, A. L. & Katz, B. (1949), ‘The effect of sodium ions on the electrical activity of the giant axon of the squid’, The Journal of Physiology 108(1), 37.CrossRefGoogle ScholarPubMed
Hoeltzell, P. B. & Dykes, R. W. (1979), ‘Conductivity in the somatosensory cortex of the cat–evidence for cortical anisotropy’, Brain Research 177(1), 6182.CrossRefGoogle ScholarPubMed
Holt, G. & Koch, C. (1999), ‘Electrical interactions via the extracellular potential near cell bodies’, Journal of Computational Neuroscience 6, 169184.CrossRefGoogle ScholarPubMed
Holt, G. R. (1998), A critical reexamination of some assumptions and implications of cable theory in neurobiology, PhD thesis, California Institute of Technology.Google Scholar
Holter, K. E., Kehlet, B., Devor, A., Sejnowski, T. J., Dale, A. M., Omholt, S. W., Ottersen, O. P., Nagelhus, E. A., Mardal, K.-A. & Pettersen, K. H. (2017), ‘Interstitial solute transport in 3d reconstructed neuropil occurs by diffusion rather than bulk flow’, Proceedings of the National Academy of Sciences 114(37), 98949899.CrossRefGoogle ScholarPubMed
Hu, H., Vervaeke, K., Graham, L. J. & Storm, J. F. (2009), ‘Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons’, The Journal of Neuroscience 29(46), 1447214483.CrossRefGoogle ScholarPubMed
Hu, H., Vervaeke, K. & Storm, J. F. (2007), ‘M-channels (kv7/kcnq channels) that regulate synaptic integration, excitability, and spike pattern of CA1 pyramidal cells are located in the perisomatic region’, The Journal of Neuroscience 27(8), 18531867.CrossRefGoogle ScholarPubMed
Huang, Y., Dmochowski, J. P., Su, Y., Datta, A., Rorden, C. & Parra, L. C. (2013), ‘Automated MRI segmentation for individualized modeling of current flow in the human head’, Journal of Neural Engineering 10(6), 9971003.CrossRefGoogle ScholarPubMed
Huang, Y. & Parra, L. C. (2015), ‘Fully automated whole-head segmentation with improved smoothness and continuity, with theory reviewed’, PLoS ONE 10(5), 134.Google ScholarPubMed
Huang, Y., Parra, L. C. & Haufe, S. (2016), ‘The New York Head – A precise standardized volume conductor model for EEG source localization and tES targeting’, NeuroImage 140, 150162.CrossRefGoogle Scholar
Hubel, D. H. & Wiesel, T. N. (1959), ‘Receptive fields of single neurones in the cat’s striate cortex’, The Journal of Physiology 148(3), 574591.CrossRefGoogle ScholarPubMed
Hübel, N., Schöll, E. & Dahlem, M. A. (2014), ‘Bistable dynamics underlying excitability of ion homeostasis in neuron models’, PLoS Computational Biology 10(5), e1003551.CrossRefGoogle ScholarPubMed
Hunt, M. J., Falinska, M., Łęski, S., Wójcik, D. K. & Kasicki, S. (2010), ‘Differential effects produced by ketamine on oscillatory activity recorded in the rat hippocampus, dorsal striatum and nucleus accumbens’, Journal of Psychopharmacology 25(6), 808821.CrossRefGoogle ScholarPubMed
Ilmoniemi, R., Hämäläinen, M. & Knuutila, J. (1985), ‘The forward and inverse problems in the spherical model’, in Weinberg, H., Stroink, G. & Katila, T. W., eds., Biomagnetism: Applications & Theory, Pergamon Press, New York, pp. 278282.Google Scholar
Ilmoniemi, R. J., Mäki, H., Saari, J., Salvador, R. & Miranda, P. C. (2016), ‘The frequency-dependent neuronal length constant in transcranial magnetic stimulation’, Frontiers in Cellular Neuroscience 10, 194.CrossRefGoogle ScholarPubMed
Ilmoniemi, R. J. & Sarvas, J. (2019), Brain Signals: Physics and Mathematics of MEG and EEG, MIT Press, Cambridge, MA.CrossRefGoogle Scholar
Ishai, P. B., Talary, M. S., Caduff, A., Levy, E. & Feldman, Y. (2013), ‘Electrode polarization in dielectric measurements: a review’, Measurement Science and Technology 24(10), 102001.CrossRefGoogle Scholar
Izhikevich, E. M. (2007), Dynamical Systems in Neuroscience, MIT Press, Cambridge, MA.Google Scholar
Jackson, J. D. (1998), Classical Electrodynamics, 3rd ed., John Wiley & Sons, Inc., New York.Google Scholar
Jacobson, G. A., Diba, K., Yaron-Jakoubovitch, A., Oz, Y., Koch, C., Segev, I. & Yarom, Y. (2005), ‘Subthreshold voltage noise of rat neocortical pyramidal neurones’, Journal of Physiology 564(Pt 1), 145160.CrossRefGoogle ScholarPubMed
Jankowski, M. M., Islam, M. N. & O’Mara, S. M. (2017), ‘Dynamics of spontaneous local field potentials in the anterior claustrum of freely moving rats’, Brain Research 1677, 101117.CrossRefGoogle ScholarPubMed
Jansen, B. H. & Rit, V. G. (1995), ‘Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns’, Biological Cybernetics 73(4), 357366.CrossRefGoogle Scholar
Jasielec, J. J. (2021), ‘Electrodiffusion phenomena in neuroscience and the Nernst–Planck–Poisson equations’, Electrochem 2(2), 197215.CrossRefGoogle Scholar
Jatoi, M. A. & Kamel, N. (2017), Brain Source Localization Using EEG Signal Analysis, CRC Press, Taylor & Francis Group, Boca Raton.CrossRefGoogle Scholar
Jirsa, V. K., Jantzen, K. J., Fuchs, A. & Kelso, J. A. (2002), ‘Spatiotemporal forward solution of the EEG and MEG using network modeling’, IEEE Transactions on Medical Imaging 21(5), 493504.CrossRefGoogle ScholarPubMed
Johnston, D. & Wu, S. M.-S. (1994), Foundations of cellular neurophysiology, MIT Press, Cambridge, MA.Google Scholar
Jolivet, R., Lewis, T. J. & Gerstner, W. (2004), ‘Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy’, Journal of Neurophysiology 92(2), 959976.CrossRefGoogle ScholarPubMed
Jones, S. R., Pritchett, D. L., Sikora, M. A., Stufflebeam, S. M., Hämäläinen, M. & Moore, C. I. (2009), ‘Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses’, Journal of Neurophysiology 102(6), 355472.CrossRefGoogle ScholarPubMed
Jones, S. R., Pritchett, D. L., Stufflebeam, S. M., Hämäläinen, M. & Moore, C. I. (2007), ‘Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study’, Journal of Neuroscience 27(40), 1075110764.CrossRefGoogle ScholarPubMed
Jordan, J., Ippen, T., Helias, M., Kitayama, I., Sato, M., Igarashi, J., Diesmann, M. & Kunkel, S. (2018), ‘Extremely scalable spiking neuronal network simulation code: from laptops to exascale computers’, Frontiers in Neuroinformatics 12, 2.CrossRefGoogle ScholarPubMed
Joucla, S. & Yvert, B. (2012), ‘Modeling extracellular electrical neural stimulation: from basic understanding to MEA-based applications’, Journal of Physiology 106(3–4), 146158.Google ScholarPubMed
Joucla, S., Yvert, B., Glière, A. & Yvert, B. (2014), ‘Current approaches to model extracellular electrical neural microstimulation’, Frontiers in Neuroscience 8, 112.Google ScholarPubMed
Jun, J. J., Steinmetz, N. A., Siegle, J. H., Denman, D. J., Bauza, M., Barbarits, B., Lee, A. K., Anastassiou, C. A., Andrei, A., Aydın, Ç., Barbic, M., Blanche, T. J., Bonin, V., Couto, J., Dutta, B., Gratiy, S. L., Gutnisky, D. A., Häusser, M., Karsh, B., Ledochowitsch, P., Lopez, C. M., Mitelut, C., Musa, S., Okun, M., Pachitariu, M., Putzeys, J., Rich, P. D., Rossant, C., Sun, W.-L., Svoboda, K., Carandini, M., Harris, K. D., Koch, C., O’Keefe, J. & Harris, T. D. (2017), ‘Fully integrated silicon probes for high-density recording of neural activity’, Nature 551(7679), 232236.CrossRefGoogle ScholarPubMed
Kager, H., Wadman, W. J. & Somjen, G. G. (2000), ‘Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations’, Journal of Neurophysiology 84(1), 495512.CrossRefGoogle Scholar
Kajikawa, Y. & Schroeder, C. E. (2011), ‘How local is the local field potential?’, Neuron 72(5), 847858.CrossRefGoogle ScholarPubMed
Kalmbach, B. E., Buchin, A., Long, B., Close, J., Nandi, A., Miller, J. A., Bakken, T. E., Hodge, R. D., Chong, P., de Frates, R., Dai, K., Maltzer, Z., Nicovich, P. R., Keene, C. D., Silbergeld, D. L., Gwinn, R. P., Cobbs, C. Ko, A. L., Ojemann, J. G., Koch, C., Anastassiou, C. A., Lein, E. S. & Ting, J. T. (2018), ‘h-channels contribute to divergent intrinsic membrane properties of supragranular pyramidal neurons in human versus mouse cerebral cortex’, Neuron 100(5), 11941208.CrossRefGoogle ScholarPubMed
Katzner, S., Nauhaus, I., Benucci, A., Bonin, V., Ringach, D. L. & Carandini, M. (2009), ‘Local origin of field potentials in visual cortex’, Neuron 61(1), 3541.CrossRefGoogle ScholarPubMed
Khodagholy, D., Gelinas, J. N., Thesen, T., Doyle, W., Devinsky, O., Malliaras, G. G. & Buzsáki, G. (2015), ‘Neurogrid: recording action potentials from the surface of the brain’, Nature Neuroscience 18(2), 310315.CrossRefGoogle ScholarPubMed
Kiebel, S. J., Garrido, M. I., Moran, R. J. & Friston, K. J. (2008), ‘Dynamic causal modelling for EEG and MEG’, Cognitive Neurodynamics 2(2), 121136.CrossRefGoogle ScholarPubMed
Kinney, J. P., Spacek, J., Bartol, T. M., Bajaj, C. L., Harris, K. M. & Sejnowski, T. J. (2013), ‘Extracellular sheets and tunnels modulate glutamate diffusion in hippocampal neuropil’, Journal of Comparative Neurology 521(2), 448464.CrossRefGoogle ScholarPubMed
Klimesch, W., Doppelmayr, M., Russegger, H., Pachinger, T. & Schwaiger, J. (1998), ‘Induced alpha band power changes in the human EEG and attention’, Neuroscience Letters 244(2), 7376.CrossRefGoogle ScholarPubMed
Koch, C. (1984), ‘Cable theory in neurons with active, linearized membranes’, Biological Cybernetics 50(1), 1533.CrossRefGoogle ScholarPubMed
Koch, C. (1999), Biophysics of Computation: Information Processing in Single Neurons., 1st ed., Oxford University Press: New York.Google Scholar
Koch, C. & Hepp, K. (2006), ‘Quantum mechanics in the brain’, Nature 440(7084), 611611.CrossRefGoogle ScholarPubMed
Koch, C., Rapp, M. & Segev, I. (1996), ‘A brief history of time (constants)’, Cerebral Cortex 6(2), 93101.CrossRefGoogle ScholarPubMed
Koch, C. & Segev, I. (1998), Methods in Neuronal Modeling: From Ions to Networks, 2nd ed., MIT Press, Cambridge, MA.Google Scholar
Koessler, L., Colnat-Coulbois, S., Cecchin, T., Hofmanis, J., Dmochowski, J. P., Norcia, A. M. & Maillard, L. G. (2017), ‘In-vivo measurements of human brain tissue conductivity using focal electrical current injection through intracerebral multicontact electrodes’, Human Brain Mapping 38(2), 974986.CrossRefGoogle ScholarPubMed
Kohl, C., Parviainen, T. & Jones, S. R. (2022), ‘Neural mechanisms underlying human auditory evoked responses revealed by human neocortical neurosolver’, Brain Topography 35(1), 1935.CrossRefGoogle ScholarPubMed
Kole, M. H. P., Hallermann, S. & Stuart, G. J. (2006), ‘Single Ih channels in pyramidal neuron dendrites: properties, distribution, and impact on action potential output’, Journal of Neuroscience 26(6), 16771687.CrossRefGoogle ScholarPubMed
Kovac, S., Speckmann, E.-J. & Gorji, A. (2018), ‘Uncensored EEG: the role of DC potentials in neurobiology of the brain’, Progress in Neurobiology 165–167, 5165.CrossRefGoogle ScholarPubMed
Kraig, R. & Nicholson, C. (1978), ‘Extracellular ionic variations during spreading depression’, Neuroscience 3(11), 10451059.Google ScholarPubMed
Krassowska, W. & Neu, J. C. (1994), ‘Response of a single cell to an external electric field’, Biophysical Journal 66(6), 17681776.CrossRefGoogle Scholar
Kreiman, G., Hung, C. P., Kraskov, A., Quiroga, R. Q., Poggio, T. & DiCarlo, J. J. (2006), ‘Object selectivity of local field potentials and spikes in the macaque inferior temporal cortex’, Neuron 49(3), 433445.CrossRefGoogle ScholarPubMed
Kreyszig, E. (1993), Advanced Engineering Mathematics, 7th ed., John Wiley & Sons, New York.Google Scholar
Kriener, B., Enger, H., Tetzlaff, T., Plesser, H. E., Gewaltig, M.-O. & Einevoll, G. T. (2014), ‘Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses’, Frontiers in Computational Neuroscience 8, 136.CrossRefGoogle ScholarPubMed
Krishnaswamy, P., Obregon-Henao, G., Ahveninen, J., Khan, S., Babadi, B., Iglesias, J. E., Hämäläinen, M. S. & Purdon, P. L. (2017), ‘Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG’, Proceedings of the National Academy of Sciences of the United States of America 114, E10465E10474.Google ScholarPubMed
Krív, N., Syková, E. & Vyklicky`, L. (1975), ‘Extracellular potassium changes in the spinal cord of the cat and their relation to slow potentials, active transport and impulse transmission’, The Journal of Physiology 249(1), 167182.CrossRefGoogle Scholar
Kubota, Y., Sohn, J. & Kawaguchi, Y. (2018), ‘Large volume electron microscopy and neural microcircuit analysis’, Frontiers in Neural Circuits 12, 98.CrossRefGoogle ScholarPubMed
Kumar, S. S., Gänswein, T., Buccino, A. P., Xue, X., Bartram, J., Emmenegger, V. & Hierlemann, A. (2022), ‘Tracking axon initial segment plasticity using high-density microelectrode arrays: a computational study’, Frontiers in Neuroinformatics 16: 957255.CrossRefGoogle ScholarPubMed
Kunkel, S., Schmidt, M., Eppler, J. M., Plesser, H. E., Masumoto, G., Igarashi, J., Ishii, S., Fukai, T., Morrison, A., Diesmann, M. & Helias, M. (2014), ‘Spiking network simulation code for petascale computers’, Frontiers in Neuroinformatics 8, 78.CrossRefGoogle ScholarPubMed
Kuokkanen, P. T., Ashida, G., Kraemer, A., McColgan, T., Funabiki, K., Wagner, H., Köppl, C., Carr, C. E. & Kempter, R. (2018), ‘Contribution of action potentials to the extracellular field potential in the nucleus laminaris of barn owl’, Journal of Neurophysiology 119(4), 14221436.CrossRefGoogle Scholar
Lapicque, L. (1907), ‘Recherches quantitatives sur l’excitation électrique des nerfs traitée comme une polarisation’, Journal of Physiol Pathol Générale 9, 620635.Google Scholar
Larkum, M. (2013), ‘A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex’, Trends in Neurosciences 36, 141151.CrossRefGoogle ScholarPubMed
Larkum, M. E., Kaiser, K. M. M. & Sakmann, B. (1999), ‘Calcium electrogenesis in distal apical dendrites of layer 5 pyramidal cells at a critical frequency of back-propagating action potentials’, Proceedings of the National Academy of Sciences 96(25), 1460014604.CrossRefGoogle Scholar
Larkum, M. E., Nevian, T., Sandler, M., Polsky, A. & Schiller, J. (2009), ‘Synaptic integration in tuft dendrites of layer 5 pyramidal neurons: a new unifying principle’, Science 325(5941), 756760.CrossRefGoogle ScholarPubMed
Larsen, B. R., Stoica, A. & MacAulay, N. (2016), ‘Managing brain extracellular K+ during neuronal activity: the physiological role of the Na+/K+-ATPase subunit isoforms’, Frontiers in Physiology 7, 141.CrossRefGoogle ScholarPubMed
Lauritzen, M. & Hansen, A. J. (1992), ‘The effect of glutamate receptor blockade on anoxic depolarization and cortical spreading depression’, Journal of Cerebral Blood Flow and Metabolism 12(2), 223229.CrossRefGoogle ScholarPubMed
Lemon, R. N., Baker, S. N. & Kraskov, A. (2021), ‘Classification of cortical neurons by spike shape and the identification of pyramidal neurons’, Cerebral Cortex 31(11): 51315138.CrossRefGoogle ScholarPubMed
Lempka, S. F., Johnson, M. D., Moffitt, M. A., Otto, K. J., Kipke, D. R. & McIntyre, C. C. (2011), ‘Theoretical analysis of intracortical microelectrode recordings’, Journal of Neural Engineering 8(4), 045006.CrossRefGoogle ScholarPubMed
Lempka, S. F. & McIntyre, C. C. (2013), ‘Theoretical analysis of the local field potential in deep brain stimulation applications’, PLoS ONE 8(3), e59839.CrossRefGoogle ScholarPubMed
Léonetti, M. & Dubois-Violette, E. (1998), ‘Theory of electrodynamic instabilities in biological cells’, Physical Review Letters 81(9), 19771980.CrossRefGoogle Scholar
Łęski, S., Lindén, H., Tetzlaff, T., Pettersen, K. H. & Einevoll, G. T. (2013), ‘Frequency dependence of signal power and spatial reach of the local field potential’, PLoS Computational Biology 9(7), e1003137.CrossRefGoogle ScholarPubMed
Light, G. A. & Näätänen, R. (2013), ‘Mismatch negativity is a breakthrough biomarker for understanding and treating psychotic disorders’, Proceedings of the National Academy of Sciences 110(38), 1517515176.CrossRefGoogle ScholarPubMed
Lindén, H., Hagen, E., Łęski, S., Norheim, E. S., Pettersen, K. H. & Einevoll, G. T. (2014), ‘LFPy: a tool for biophysical simulation of extracellular potentials generated by detailed model neurons’, Frontiers in Neuroinformatics 7(41), 115.CrossRefGoogle ScholarPubMed
Lindén, H., Pettersen, K. H. & Einevoll, G. T. (2010), ‘Intrinsic dendritic filtering gives low-pass power spectra of local field potentials’, Journal of Computational Neuroscience 29(3), 42344.CrossRefGoogle ScholarPubMed
Lindén, H., Tetzlaff, T., Potjans, T. C., Pettersen, K. H., Grün, S., Diesmann, M. & Einevoll, G. T. (2011), ‘Modeling the spatial reach of the LFP’, Neuron 72(5), 859872.CrossRefGoogle ScholarPubMed
Lindsay, K. A., Rosenberg, J. R. & Tucker, G. (2004), ‘From Maxwell’s equations to the cable equation and beyond’, Progress in Biophysics and Molecular Biology 85(1), 71116.CrossRefGoogle Scholar
Liu, J. & Newsome, W. T. (2006), ‘Local field potential in cortical area MT: stimulus tuning and behavioral correlations’, Journal of Neuroscience 26(30), 77797790.CrossRefGoogle ScholarPubMed
Logg, A., Mardal, K.-A. & Wells, G. N. (2012), Automated Solution of Differential Equations by the Finite Element Method, Vol. 84 of Lecture Notes in Computational Science and Engineering, Springer Berlin Heidelberg, Berlin, Heidelberg.CrossRefGoogle Scholar
Logothetis, N. K., Kayser, C. & Oeltermann, A. (2007), ‘In vivo measurement of cortical impedance spectrum in monkeys: implications for signal propagation’, Neuron 55(5), 809823.CrossRefGoogle ScholarPubMed
Lopes da Silva, F. (2013), ‘EEG and MEG: Relevance to neuroscience’, Neuron 80(5), 11121128.CrossRefGoogle ScholarPubMed
Lopreore, C. L., Bartol, T. M., Coggan, J. S., Keller, D. X., Sosinsky, G. E., Ellisman, M. H. & Sejnowski, T. J. (2008), ‘Computational modeling of three-dimensional electrodiffusion in biological systems: application to the node of Ranvier’, Biophysical Journal 95(6), 26242635.CrossRefGoogle ScholarPubMed
Luo, J., Macias, S., Ness, T. V., Einevoll, G. T., Zhang, K. & Moss, C. F. (2018), ‘Neural timing of stimulus events with microsecond precision’, PLoS Biology 16(10), 122.CrossRefGoogle ScholarPubMed
Lyshevski, S. (2007), Nano and Molecular Electronics Handbook, CRC Press, Taylor and Francis Group, Boca Raton.Google Scholar
Lytton, W. H. (2002), From Computer to Brain – Foundations of Computational Neuroscience, Springer, New York.Google Scholar
Magee, J. C. (1998), ‘Dendritic hyperpolarization-activated currents modify the integrative properties of hippocampal CA1 pyramidal neurons’, The Journal of Neuroscience 18(19), 76137624.CrossRefGoogle ScholarPubMed
Magee, J. C. & Grienberger, C. (2020), ‘Synaptic plasticity forms and functions’, Annual Review of Neuroscience 43, 95117.CrossRefGoogle ScholarPubMed
Mainen, Z. F. & Sejnowski, T. J. (1995), ‘Reliability of spike timing in neocortical neurons’, Science 268(5216), 15031506.CrossRefGoogle ScholarPubMed
Mäki-Marttunen, T., Kaufmann, T., Elvsåshagen, T., Devor, A., Djurovic, S., Westlye, L. T., Linne, M.-L., Rietschel, M., Schubert, D., Borgwardt, S., Efrim-Budisteanu, M., Bettella, F., Halnes, G. & Hagen, E. (2019), ‘Biophysical psychiatry – how computational neuroscience can help to understand the complex mechanisms of mental disorders’, Frontiers in Psychiatry 10(534), 114.CrossRefGoogle Scholar
Mäki-Marttunen, T., Krull, F., Bettella, F., Hagen, E., Næss, S., Ness, T. V., Moberget, T., Elvsåshagen, T., Metzner, C., Devor, A., Edwards, A. G., Fyhn, M., Djurovic, S., Anders, M. D., Andreassen, O. A. & Einevoll, G. T. (2019), ‘Alterations in schizophrenia-associated genes can lead to increased power in delta oscillations’, Cerebral Cortex 29(2), 875891.CrossRefGoogle ScholarPubMed
Manita, S., Suzuki, T., Homma, C., Matsumoto, T., Odagawa, M., Yamada, K., Ota, K., Matsubara, C., Inutsuka, A., Sato, M., Ohkura, M., Yamanaka, A., Yanagawa, Y., Nakai, J., Hayashi, Y., Larkum, M. E. & Murayama, M. (2015), ‘A top-down cortical circuit for accurate sensory perception’, Neuron 86(5), 13041316.CrossRefGoogle ScholarPubMed
Markram, H., Muller, E., Ramaswamy, S., Reimann, M. W., Abdellah, M., Sanchez, C. A., Ailamaki, A., Alonso-Nanclares, L., Antille, N., Arsever, S., Kahou, G. A. A., Berger, T. K., Bilgili, A., Buncic, N., Chalimourda, A., Chindemi, G., Courcol, J.-D., Delalondre, F., Delattre, V., Druckmann, S., Dumusc, R., Dynes, J., Eilemann, S., Gal, E., Gevaert, M. E., Ghobril, J.-P., Gidon, A., Graham, J. W., Gupta, A., Haenel, V., Hay, E., Heinis, T., Hernando, J. B., Hines, M., Kanari, L., Keller, D., Kenyon, J., Khazen, G., Kim, Y., King, J. G., Kisvarday, Z., Kumbhar, P., Lasserre, S., Le Bé, J.-V., Magalhães, B. R. C., Merchán-Pérez, A., Meystre, J., Morrice, B. R., Muller, J., Muñoz-Céspedes, A., Muralidhar, S., Muthurasa, K., Nachbaur, D., Newton, T. H., Nolte, M., Ovcharenko, A., Palacios, J., Pastor, L., Perin, R., Ranjan, R., Riachi, I., Rodríguez, J.-R., Riquelme, J. L., Rössert, C., Sfyrakis, K., Shi, Y., Shillcock, J. C., Silberberg, G., Silva, R., Tauheed, F., Telefont, M., Toledo-Rodriguez, M., Tränkler, T., Van Geit, W., Díaz, J. V., Walker, R., Wang, Y., Zaninetta, S. M., DeFelipe, J., Hill, S. L., Segev, I. & Schürmann, F. (2015), ‘Reconstruction and simulation of neocortical microcircuitry’, Cell 163(2), 456492.CrossRefGoogle ScholarPubMed
Markram, H., Toledo-Rodriguez, M., Wang, Y., Gupta, A., Silberberg, G. & Wu, C. (2004), ‘Interneurons of the neocortical inhibitory system’, Nature Reviews Neuroscience 5(10), 793807.CrossRefGoogle ScholarPubMed
Martínez-Cañada, P., Ness, T. V., Einevoll, G. T., Fellin, T. & Panzeri, S. (2021), ‘Computation of the electroencephalogram (EEG) from network models of point neurons’, PLoS Computational Biology 17(4), e1008893.CrossRefGoogle ScholarPubMed
Martinez, J., Pedreira, C., Ison, M. J. & Quiroga, R. Q. (2009), ‘Realistic simulation of extracellular recordings’, Journal of Neuroscience Methods 184(2), 285293.CrossRefGoogle ScholarPubMed
Martinsen, Ø. G. & Grimnes, S. (2015), Bioimpedance and Bioelectricity Basics, Academic Press (Elsevier), Cambridge, MA.Google Scholar
Mauro, A., Conti, F., Dodge, F. & Schor, R. (1970), ‘Subthreshold behavior and phenomenological impedance of the squid giant axon’, The Journal of General Physiology 55(4), 497523.CrossRefGoogle ScholarPubMed
Mazzoni, A., Brunel, N., Cavallari, S., Logothetis, N. K. & Panzeri, S. (2011), ‘Cortical dynamics during naturalistic sensory stimulations: experiments and models’, Journal of Physiology 105(1–3), 215.Google ScholarPubMed
Mazzoni, A., Lindèn, H., Cuntz, H., Lansner, A., Panzeri, S. & Einevoll, G. T. (2015), ‘Computing the local field potential (LFP) from integrate-and-fire network models’, PLoS Computational Biology 11(12), e1004584.CrossRefGoogle ScholarPubMed
McCann, H., Pisano, G. & Beltrachini, L. (2019), ‘Variation in reported human head tissue electrical conductivity values’, Brain Topography 32(5), 825858.CrossRefGoogle ScholarPubMed
McColgan, T., Liu, J., Kuokkanen, P. T., Carr, C. E., Wagner, H. & Kempter, R. (2017), ‘Dipolar extracellular potentials generated by axonal projections’, eLife 6: e26106.CrossRefGoogle ScholarPubMed
McCreery, D. B. & Agnew, W. F. (1983), ‘Changes in extracellular potassium and calcium concentration and neural activity during prolonged electrical stimulation of the cat cerebral cortex at defined charge densities’, Experimental Neurology 79(2), 371396.CrossRefGoogle ScholarPubMed
McCulloch, W. S. & Pitts, W. (1943), ‘A logical calculus of the ideas immanent in nervous activity’, The Bulletin of Mathematical Biophysics 5(4), 115133.CrossRefGoogle Scholar
McIntyre, C. C. & Grill, W. M. (2001), ‘Finite element analysis of the current-density and electric field generated by metal microelectrodes’, Annals of Biomedical Engineering 29(3), 227235.CrossRefGoogle ScholarPubMed
Mechler, F. & Victor, J. D. (2012), ‘Dipole characterization of single neurons from their extracellular action potentials’, Journal of Computational Neuroscience 32(1), 73100.CrossRefGoogle ScholarPubMed
Mechler, F., Victor, J. D., Ohiorhenuan, I., Schmid, A. M. & Hu, Q. (2011), ‘Three-dimensional localization of neurons in cortical tetrode recordings’, Journal of Neurophysiology 106(2), 828848.CrossRefGoogle ScholarPubMed
Meffin, H., Tahayori, B., Grayden, D. B. & Burkitt, A. N. (2012), ‘Modeling extracellular electrical stimulation: I. derivation and interpretation of neurite equations’, Journal of Neural Engineering 9(6), 065005.CrossRefGoogle ScholarPubMed
Meffin, H., Tahayori, B., Sergeev, E. N., Mareels, I. M. Y., Grayden, D. B. & Burkitt, A. N. (2014), ‘Modelling extracellular electrical stimulation: III. derivation and interpretation of neural tissue equations’, Journal of Neural Engineering 11(6), 065004.CrossRefGoogle Scholar
Meunier, C. & Segev, I. (2002), ‘Playing the devil’s advocate: is the Hodgkin–Huxley model useful?’, Trends in Neurosciences 25(11), 558563.CrossRefGoogle ScholarPubMed
Miceli, S., Ness, T. V., Einevoll, G. T. & Schubert, D. (2017), ‘Impedance spectrum in cortical tissue: implications for propagation of LFP signals on the microscopic level’, eNeuro 4(1), ENEURO.0291-16.2016.CrossRefGoogle ScholarPubMed
Migliore, M., Cook, E., Jaffe, D., Turner, D. & Johnston, D. (1995), ‘Computer simulations of morphologically reconstructed CA3 hippocampal neurons’, Journal of Neurophysiology 73(3), 11571168.CrossRefGoogle ScholarPubMed
Migliore, M. & Shepherd, G. M. (2002), ‘Emerging rules for the distributions of active dendritic conductances’, Nature Reviews Neuroscience 3(5), 362370.CrossRefGoogle ScholarPubMed
Miller, K. J., Sorensen, L. B., Ojemann, J. G. & den Nijs, M. (2009), ‘Power-law scaling in the brain surface electric potential’, PLoS Computational Biology 5(12), e1000609.CrossRefGoogle ScholarPubMed
Miller, P. (2018), An Introductory Course in Computational Neuroscience, MIT Press, Cambridge, MA.Google Scholar
Milstein, J., Mormann, F., Fried, I. & Koch, C. (2009), ‘Neuronal shot noise and brownian 1/f 2 behavior in the local field potential’, PLoS ONE 4(2), e4338.CrossRefGoogle ScholarPubMed
Milton, J. G. (2012), ‘Neuronal avalanches, epileptic quakes and other transient forms of neurodynamics’, European Journal of Neuroscience 36(2), 21562163.CrossRefGoogle ScholarPubMed
Miranda, P. C., Callejón-Leblic, M. A., Salvador, R. & Ruffini, G. (2018), ‘Realistic modeling of transcranial current stimulation: the electric field in the brain’, Current Opinion in Biomedical Engineering 8, 2027.CrossRefGoogle Scholar
Mitzdorf, U. (1985), ‘Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena’, Physiological Reviews 65(1), 37100.CrossRefGoogle ScholarPubMed
Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. (2009), ‘Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop’, Neuron 64(2), 267280.CrossRefGoogle ScholarPubMed
Moffitt, M. A. & McIntyre, C. C. (2005), ‘Model-based analysis of cortical recording with silicon microelectrodes’, Clinical Neurophysiology 116(9), 22402250.CrossRefGoogle ScholarPubMed
Molina-Martínez, B., Jentsch, L.-V., Ersoy, F., van der Moolen, M., Donato, S., Ness, T. V., Heutink, P., Jones, P. D. & Cesare, P. (2022), ‘A multimodal 3D neuro-microphysiological system with neurite-trapping microelectrodes’, Biofabrication 14(2), 025004.CrossRefGoogle ScholarPubMed
Monai, H., Inoue, M., Miyakawa, H. & Aonishi, T. (2012), ‘Low-frequency dielectric dispersion of brain tissue due to electrically long neurites’, Physical Review E 86(6), 061911.CrossRefGoogle ScholarPubMed
Mondragón-González, S. L. & Burguière, E. (2017), ‘Bio-inspired benchmark generator for extracellular multi-unit recordings’, Scientific Reports 7, 43253.CrossRefGoogle Scholar
Monfared, O., Tahayori, B., Freestone, D., Nešić, D., Grayden, D. B. & Meffin, H. (2020), ‘Determination of the electrical impedance of neural tissue from its microscopic cellular constituents’, Journal of Neural Engineering 17(1), 016037.CrossRefGoogle ScholarPubMed
Mori, Y. (2006), A three-dimensional model of cellular electrical activity, PhD thesis, New York University.Google Scholar
Mori, Y. (2015), ‘A multidomain model for ionic electrodiffusion and osmosis with an application to cortical spreading depression’, Physica D: Nonlinear Phenomena 308, 94108.CrossRefGoogle Scholar
Mori, Y., Fishman, G. I. & Peskin, C. S. (2008), ‘Ephaptic conduction in a cardiac strand model with 3D electrodiffusion’, Proceedings of the National Academy of Sciences of the United States of America 105(17), 64636468.CrossRefGoogle Scholar
Mori, Y. & Peskin, C. (2009), ‘A numerical method for cellular electrophysiology based on the electrodiffusion equations with internal boundary conditions at membranes’, Communications in Applied Mathematics and Computational Science 4(1), 85134.CrossRefGoogle Scholar
Moulin, C., Glière, A., Barbier, D., Joucla, S., Yvert, B., Mailley, P. & Guillemaud, R. (2008), ‘A new 3-D finite-element model based on thin-film approximation for microelectrode array recording of extracellular action potential’, IEEE Transactions on Biomedical Engineering 55(2 Pt 1), 683692.CrossRefGoogle ScholarPubMed
Mukamel, R. & Fried, I. (2012), ‘Human intracranial recordings and cognitive neuroscience’, Annual Review of Psychology 63, 511537.CrossRefGoogle ScholarPubMed
Murakami, S., Hirose, A. & Okada, Y. C. (2003), ‘Contribution of ionic currents to magnetoencephalography (MEG) and electroencephalography (EEG) signals generated by guinea-pig CA3 slices’, The Journal of Physiology 553(Pt 3), 975985.CrossRefGoogle ScholarPubMed
Murakami, S. & Okada, Y. (2006), ‘Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals’, The Journal of Physiology 575(Pt 3), 925936.CrossRefGoogle ScholarPubMed
Murakami, S., Zhang, T., Hirose, A. & Okada, Y. C. (2002), ‘Physiological origins of evoked magnetic fields and extracellular field potentials produced by guinea-pig CA3 hippocampal slices’, The Journal of Physiology 544(1), 237251.CrossRefGoogle ScholarPubMed
Næss, S., Chintaluri, C., Ness, T. V., Dale, A. M., Einevoll, G. T. & Wójcik, D. K. (2017), ‘Corrected four-sphere head model for EEG signals’, Frontiers in Human Neuroscience 11, 17.CrossRefGoogle ScholarPubMed
Næss, S., Halnes, G., Hagen, E., Hagler, D. J., Dale, A. M., Einevoll, G. T. & Ness, T. V. (2021), ‘Biophysically detailed forward modeling of the neural origin of EEG and MEG signals’, NeuroImage 225(117467), 2020.07.01.181875.CrossRefGoogle ScholarPubMed
Nagarajan, S. S. & Durand, D. M. (1996), ‘A generalized cable equation for magnetic stimulation of axons’, IEEE Transactions on Biomedical Engineering 43(3), 304312.CrossRefGoogle ScholarPubMed
Nair, J., Klaassen, A.-L., Arato, J., Vyssotski, A. L., Harvey, M. & Rainer, G. (2018), ‘Basal forebrain contributes to default mode network regulation’, Proceedings of the National Academy of Sciences 115(6), 13521357.CrossRefGoogle ScholarPubMed
Neher, E. (1992), ‘Correction for liquid junction potentials in patch clamp experiments’, Methods in Enzymology 207, 123131.CrossRefGoogle ScholarPubMed
Nelson, M. J. & Pouget, P. (2010), ‘Do electrode properties create a problem in interpreting local field potential recordings?’, Journal of Neurophysiology 103(5), 23152317.CrossRefGoogle ScholarPubMed
Nelson, M. J., Pouget, P., Nilsen, E. A., Patten, C. D. & Schall, J. D. (2008), ‘Review of signal distortion through metal microelectrode recording circuits and filters’, Journal of Neuroscience Methods 169(1), 141157.CrossRefGoogle ScholarPubMed
Ness, T. V., Chintaluri, C., Potworowski, J., Łęski, S., Głąbska, H., Wójcik, D. K. & Einevoll, G. T. (2015), ‘Modelling and analysis of electrical potentials recorded in microelectrode arrays (MEAs)’, Neuroinformatics 13(4), 403426.CrossRefGoogle ScholarPubMed
Ness, T. V., Remme, M. W. H. & Einevoll, G. T. (2016), ‘Active subthreshold dendritic conductances shape the local field potential’, Journal of Physiology 594(13), 38093825.CrossRefGoogle ScholarPubMed
Ness, T. V., Remme, M. W. H. & Einevoll, G. T. (2018), ‘h-type membrane current shapes the local field potential from populations of pyramidal neurons’, Journal of Neuroscience 38(26), 60116024.CrossRefGoogle ScholarPubMed
Neymotin, S. A., Daniels, D. S., Caldwell, B., McDougal, R. A., Carnevale, N. T., Jas, M., Moore, C. I., Hines, M. L., Hämäläinen, M. & Jones, S. R. (2020), ‘Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data’, eLife 9, e51214.CrossRefGoogle ScholarPubMed
Nicholson, C. (1973), ‘Theoretical analysis of field potentials in anisotropic ensembles of neuronal elements’, IEEE Transactions on Biomedical Engineering 20(4), 278288.CrossRefGoogle ScholarPubMed
Nicholson, C. (2001), ‘Diffusion and related transport mechanisms in brain tissue’, Reports on Progress in Physics 64(7), 815.CrossRefGoogle Scholar
Nicholson, C. & Freeman, J. A. (1975), ‘Theory of current source-density analysis and determination of conductivity tensor for anuran cerebellum’, Journal of Neurophysiology 38(2), 356368.CrossRefGoogle ScholarPubMed
Nicholson, C. & Llinas, R. (1971), ‘Field potentials in the alligator cerebellum and theory of their relationship to Purkinje cell dendritic spikes’, Journal of Neurophysiology 34(4), 509531.CrossRefGoogle ScholarPubMed
Nicholson, C. & Phillips, J. (1981), ‘Ion diffusion modified by tortuosity and volume fraction in the extracellular microenvironment of the rat cerebellum’, The Journal of Physiology 321(1), 225257.CrossRefGoogle ScholarPubMed
Nicholson, C. & Syková, E. (1998), ‘Extracellular space structure revealed by diffusion analysis’, Trends in Neurosciences 21(5), 207215.CrossRefGoogle ScholarPubMed
Nicholson, C., ten Bruggencate, G., Stockle, H. & Steinberg, R. (1978), ‘Calcium and potassium changes in extracellular microenvironment of cat cerebellar cortex’, Journal of Neurophysiology 41(4), 10261039.CrossRefGoogle ScholarPubMed
Nicholson, P. W. (1965), ‘Specific impedance of cerebral white matter’, Experimental Neurology 13(4), 386401.CrossRefGoogle ScholarPubMed
Niedermeyer, E. (2003), ‘The clinical relevance of EEG interpretation’, Clinical Electroencephalography 34(3), 9398.CrossRefGoogle ScholarPubMed
Normann, R. A., Maynard, E. M., Rousche, P. J. & Warren, D. J. (1999), ‘A neural interface for a cortical vision prosthesis’, Vision Research 39(15), 25772587.CrossRefGoogle ScholarPubMed
Nunez, P. L. (1974), ‘The brain wave equation: a model for the EEG’, Mathematical Biosciences 21(3–4), 279297.CrossRefGoogle Scholar
Nunez, P. L., Nunez, M. D. & Srinivasan, R. (2019), ‘Multi-scale neural sources of EEG: genuine, equivalent, and representative. A tutorial review’, Brain Topography 32(2), 193214.CrossRefGoogle ScholarPubMed
Nunez, P. L. & Srinivasan, R. (2006), Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, USA, New York.CrossRefGoogle Scholar
Obien, M. E. J., Hierlemann, A. & Frey, U. (2019), ‘Accurate signal-source localization in brain slices by means of high-density microelectrode arrays’, Scientific Reports 9(1), 119.CrossRefGoogle ScholarPubMed
O’Connell, R. & Mori, Y. (2016), ‘Effects of glia in a triphasic continuum model of cortical spreading depression’, Bulletin of Mathematical Biology 78(10), 19431967.CrossRefGoogle Scholar
Offner, F. F. (1991), ‘Ion flow through membranes and the resting potential of cells’, The Journal of Membrane Biology 123(2), 171182.CrossRefGoogle ScholarPubMed
Okada, Y. C., Huang, J.-C., Rice, M. E., Tranchina, D. & Nicholson, C. (1994), ‘Origin of the apparent tissue conductivity in the molecular and granular layers of the in vitro turtle cerebellum and the interpretation of current source-density analysis’, Journal of Neurophysiology 72(2), 742753.CrossRefGoogle ScholarPubMed
Okun, M. & Lampl, I. (2008), ‘Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities’, Nature Neuroscience 11(5), 535537.CrossRefGoogle ScholarPubMed
Olsson, T., Broberg, M., Pope, K., Wallace, A., Mackenzie, L., Blomstrand, F., Nilsson, M. & Willoughby, J. (2006), ‘Cell swelling, seizures and spreading depression: an impedance study’, Neuroscience 140(2), 505515.CrossRefGoogle ScholarPubMed
Orkand, R. K., Nicholls, J. G. & Kuffler, S. W. (1966), ‘Effect of nerve impulses on the membrane potential of glial cells in the central nervous system of amphibia’, Journal of Neurophysiology 29(4), 788806.CrossRefGoogle ScholarPubMed
Ostojic, S. (2014), ‘Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons’, Nature Neuroscience 17(4), 594600.CrossRefGoogle ScholarPubMed
Øyehaug, L., Østby, I., Lloyd, C. M., Omholt, S. W. & Einevoll, G. T. (2012), ‘Dependence of spontaneous neuronal firing and depolarisation block on astroglial membrane transport mechanisms’, Journal of Computational Neuroscience 32(1), 147165.CrossRefGoogle ScholarPubMed
Pakkenberg, B., Pelvig, D., Marner, L., Bundgaard, M. J., Gundersen, H. J. G., Nyengaard, J. R. & Regeur, L. (2003), ‘Aging and the human neocortex’, Experimental Gerontology 38(1–2), 9599.CrossRefGoogle ScholarPubMed
Palva, S. & Palva, J. M. (2011), ‘Functional roles of alpha-band phase synchronization in local and large-scale cortical networks’, Frontiers in Psychology 2(SEP), 115.CrossRefGoogle ScholarPubMed
Parasnis, D. S. (1986), Principles of Applied Geophysics, 4th ed., Chapman and Hall, New York.CrossRefGoogle Scholar
Pashut, T., Wolfus, S., Friedman, A., Lavidor, M., Bar-Gad, I., Yeshurun, Y. & Korngreen, A. (2011), ‘Mechanisms of magnetic stimulation of central nervous system neurons’, PLoS Computational Biology 7(3), e1002022.CrossRefGoogle ScholarPubMed
Pellerin, J. P. & Lamarre, Y. (1997), ‘Local field potential oscillations in primate cerebellar cortex during voluntary movement’, Journal of Neurophysiology 78(6), 35023507.CrossRefGoogle ScholarPubMed
Perelman, Y. & Ginosar, R. (2006), ‘Analog frontend for multichannel neuronal recording system with spike and LFP separation’, Journal of Neuroscience Methods 153(1), 2126.CrossRefGoogle ScholarPubMed
Perram, J. W. & Stiles, P. J. (2006), ‘On the nature of liquid junction and membrane potentials’, Physical Chemistry Chemical Physics 8(36), 42004213.CrossRefGoogle ScholarPubMed
Pesaran, B., Vinck, M., Einevoll, G. T., Sirota, A., Fries, P., Siegel, M., Truccolo, W., Schroeder, C. E. & Srinivasan, R. (2018), ‘Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation’, Nature Neuroscience 21(7), 903919.CrossRefGoogle ScholarPubMed
Petersen, C. C. (2017), ‘Whole-cell recording of neuronal membrane potential during behavior’, Neuron 95(6), 12661281.CrossRefGoogle ScholarPubMed
Pethig, R. (1987), ‘Dielectric properties of body tissues’, Clinical Physics and Physiological Measurement 8(4A), 5.CrossRefGoogle ScholarPubMed
Pettersen, K. H., Devor, A., Ulbert, I., Dale, A. M. & Einevoll, G. T. (2006), ‘Current-source density estimation based on inversion of electrostatic forward solution: effects of finite extent of neuronal activity and conductivity discontinuities’, Journal of Neuroscience Methods 154(1–2), 116133.CrossRefGoogle ScholarPubMed
Pettersen, K. H. & Einevoll, G. T. (2008), ‘Amplitude variability and extracellular low-pass filtering of neuronal spikes’, Biophysical Journal 94(3), 784802.CrossRefGoogle ScholarPubMed
Pettersen, K. H., Hagen, E. & Einevoll, G. T. (2008), ‘Estimation of population firing rates and current source densities from laminar electrode recordings’, Journal of Computational Neuroscience 24(3), 291313.CrossRefGoogle ScholarPubMed
Pettersen, K. H., Lindén, H., Dale, A. M. & Einevoll, G. T. (2012), ‘Extracellular spikes and CSD’, in Brette, R. & Destexhe, A., eds., Handbook of Neural Activity Measurements, Cambridge University Press, Cambridge, pp. 92135.CrossRefGoogle Scholar
Pettersen, K. H., Lindén, H., Tetzlaff, T. & Einevoll, G. T. (2014), ‘Power laws from linear neuronal cable theory: power spectral densities of the soma potential, soma membrane current and single-neuron contribution to the EEG’, PLoS Computational Biology 10(11), e1003928.CrossRefGoogle ScholarPubMed
Pfurtscheller, G. & Cooper, R. (1975), ‘Frequency dependence of the transmission of the EEG from cortex to scalp’, Electroencephalography and Clinical Neurophysiology 38(1), 9396.CrossRefGoogle Scholar
Piastra, M. C., Nüßing, A., Vorwerk, J., Clerc, M., Engwer, C. & Wolters, C. H. (2021), ‘A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources’, Human Brain Mapping 42(4), 978992.CrossRefGoogle Scholar
Pickard, W. F. (1976), ‘Generalizations of the Goldman-Hodgkin-Katz Equation’, Mathematical Biosciences 30(1–2), 99111.CrossRefGoogle Scholar
Pietrobon, D. & Moskowitz, M. A. (2014), ‘Chaos and commotion in the wake of cortical spreading depression and spreading depolarizations’, Nature Reviews Neuroscience 15(6), 379393.CrossRefGoogle ScholarPubMed
Pitts, W. (1952), ‘Investigation on synaptic transmission’, in von Foerster, H, ed., Cybernetics: Circular Causal and Feedback Mechanisms in Biological and Social Systems (Trans. 9th Conf.), Josiah Macy Jr. Foundation, New York, pp. 159166.Google Scholar
Planck, M. (1890), ‘Ueber die potentialdifferenz zwischen zwei verdünnten lösungen binärer electrolyte’, Annalen der Physik 276(8), 561576.CrossRefGoogle Scholar
Plesser, H. E., Eppler, J. M., Morrison, A., Diesmann, M. & Gewaltig, M.-O. (2007), ‘Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers’, inKermarrec, A.-M., Bougé, L. & Priol, T., eds., Euro-Par 2007 Parallel Processing, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 672681.CrossRefGoogle Scholar
Plonsey, R. & Barr, R. C. (2007), Bioelectricity: a Quantitative Approach, Springer Science & Business Media, New York.Google Scholar
Plonsey, R. & Heppner, D. B. (1967), ‘Considerations of quasi-stationarity in electrophysiological systems’, The Bulletin of Mathematical Biophysics 29(4), 657664.CrossRefGoogle ScholarPubMed
Pods, J. (2017), ‘A comparison of computational models for the extracellular potential of neurons’, Journal of Integrative Neuroscience 16(1), 1932.CrossRefGoogle ScholarPubMed
Pospischil, M., Toledo-Rodriguez, M., Monier, C., Piwkowska, Z., Bal, T., Frégnac, Y., Markram, H. & Destexhe, A. (2008), ‘Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons’, Biological Cybernetics 99(4–5), 427441.CrossRefGoogle ScholarPubMed
Potjans, T. C. & Diesmann, M. (2014), ‘The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model’, Cerebral Cortex 24(3), 785806.CrossRefGoogle Scholar
Potworowski, J., Jakuczun, W., Lęski, S. & Wójcik, D. (2012), ‘Kernel current source density method’, Neural Computation 24(2), 541575.CrossRefGoogle ScholarPubMed
Pozzorini, C., Mensi, S., Hagens, O., Naud, R., Koch, C. & Gerstner, W. (2015), ‘Automated high-throughput characterization of single neurons by means of simplified spiking models’, PLoS Computational Biology 11(6), e1004275.CrossRefGoogle ScholarPubMed
Qian, N. & Sejnowski, T. (1989), ‘An electro-diffusion model for computing membrane potentials and ionic concentrations in branching dendrites, spines and axons’, Biological Cybernetics 62(1), 115.CrossRefGoogle Scholar
Quiroga, R. Q. (2007), ‘Spike sorting’, Scholarpedia 2(12), 3583.CrossRefGoogle Scholar
Raimondo, J. V., Burman, R. J., Katz, A. A. & Akerman, C. J. (2015), ‘Ion dynamics during seizures’, Frontiers in Cellular Neuroscience 9, 419.CrossRefGoogle ScholarPubMed
Rall, W. (1959), ‘Branching dendritic trees and motoneuron membrane resistivity’, Experimental Neurology 1(5), 491527.CrossRefGoogle ScholarPubMed
Rall, W. (1962), ‘Electrophysiology of a dendritic neuron model’, Biophysical Journal 2(2 Pt 2), 145167.CrossRefGoogle ScholarPubMed
Rall, W. (1977), ‘Core conductor theory and cable properties of neurons’, in Brookhart, J. M. & Mountcastle, V. B., eds., Handbook of Physiology, American Physiological Society, Bethesda, pp. 3997.Google Scholar
Rall, W. (1989), ‘Cable theory for dendritic neurons’, in Koch, C. & Segev, I., eds., Methods in Neuronal Modeling, MIT Press, Cambridge, MA, pp. 992.Google Scholar
Rall, W. & Shepherd, G. M. (1968), ‘Theoretical reconstruction of field potentials and dendrodendritic synaptic interactions in olfactory bulb’, Journal of Neurophysiology 31(6), 884915.CrossRefGoogle ScholarPubMed
Ramaswamy, S., Courcol, J.-D., Abdellah, M., Adaszewski, S. R., Antille, N., Arsever, S., Atenekeng, G., Bilgili, A., Brukau, Y., Chalimourda, A., Chindemi, G., Delalondre, F., Dumusc, R., Eilemann, S., Gevaert, M. E., Gleeson, P., Graham, J. W., Hernando, J. B., Kanari, L., Katkov, Y., Keller, D., King, J. G., Ranjan, R., Reimann, M. W., Rössert, C., Shi, Y., Shillcock, J. C., Telefont, M., Geit, W. V., Diaz, J. V., Walker, R., Wang, Y., Zaninetta, S. M., DeFelipe, J., Hill, S. L., Muller, J., Segev, I., Schürmann, F., Muller, E. B. & Markram, H. (2015), ‘The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex’, Frontiers in Neural Circuits 9, 44.CrossRefGoogle Scholar
Ranck, J. B. (1963), ‘Specific impedance of rabbit cerebral cortex’, Experimental Neurology 7(2), 144152.CrossRefGoogle ScholarPubMed
Ranta, R., Le Cam, S., Tyvaert, L. & Louis-Dorr, V. (2017), ‘Assessing human brain impedance using simultaneous surface and intracerebral recordings’, Neuroscience 343, 411422.CrossRefGoogle ScholarPubMed
Rasmussen, R., Nicholas, E., Petersen, N. C., Dietz, A. G., Xu, Q., Sun, Q. & Nedergaard, M. (2019), ‘Cortex-wide changes in extracellular potassium ions parallel brain state transitions in awake behaving mice’, Cell Reports 28(5), 11821194.e4.CrossRefGoogle ScholarPubMed
Rasmussen, R., O’Donnell, J., Ding, F. & Nedergaard, M. (2020), ‘Interstitial ions: A key regulator of state-dependent neural activity?’, Progress in Neurobiology, 193, 101802.CrossRefGoogle ScholarPubMed
Rattay, F. (1999), ‘The basic mechanism for the electrical stimulation of the nervous system’, Neuroscience 89, 335346.CrossRefGoogle ScholarPubMed
Ray, S. & Bhalla, U. S. (2008), ‘PyMOOSE: Interoperable scripting in Python for MOOSE’, Frontiers in Neuroinformatics 2, 6.Google ScholarPubMed
Ray, S. & Maunsell, J. (2011), ‘Different origins of gamma rhythm and high-gamma activity in macaque visual cortex’, PLoS Biology 9(4), e10001610.CrossRefGoogle ScholarPubMed
Reimann, M., King, J., Muller, E., Ramaswamy, S. & Markram, H. (2015), ‘An algorithm to predict the connectome of neural microcircuits’, Frontiers in Computational Neuroscience 9, 120.CrossRefGoogle ScholarPubMed
Reimann, M. W., Anastassiou, C. A., Perin, R., Hill, S. L., Markram, H. & Koch, C. (2013), ‘A biophysically detailed model of neocortical local field potentials predicts the critical role of active membrane currents’, Neuron 79(2), 375390.CrossRefGoogle ScholarPubMed
Reitz, J. R., Milford, F. J. & Christy, R. W. (1993), Foundations of Electromagnetic Theory, 4th ed., Addison-Wesley Publishing Company, Reading, MA.Google Scholar
Remme, M. & Rinzel, J. (2011), ‘Role of active conductances in subthreshold input integration’, Journal of Compuational Neuroscience 31(1), 1330.CrossRefGoogle ScholarPubMed
Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A. & Harris, K. D. (2010), ‘The asynchronous state in cortical circuits’, Science 327(5965), 587590.CrossRefGoogle Scholar
Richardson, M. J. (2004), ‘Effects of synaptic conductance on the voltage distribution and firing rate of spiking neurons’, Physical Review E 69(5), 051918.CrossRefGoogle ScholarPubMed
Richter, F. & Lehmenkühler, A. (1993), ‘Spreading depression can be restricted to distinct depths of the rat cerebral cortex’, Neuroscience Letters 152(1–2), 6568.CrossRefGoogle ScholarPubMed
Rimehaug, A. E., Stasik, A. J., Hagen, E., Billeh, Y. N., Siegle, J. H., Dai, K., Olsen, S. R., Koch, C., Einevoll, G. T. & Arkhipov, A. (2023), ‘Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex’, eLife 12, e87169.CrossRefGoogle ScholarPubMed
Rinzel, J. (1990), ‘Discussion: electrical excitability of cells, theory and experiment: review of the Hodgkin-Huxley foundation and an update’, Bulletin of Mathematical Biology 52(1–2), 323.CrossRefGoogle Scholar
Ritter, P., Schirner, M., Mcintosh, A. R. & Jirsa, V. K. (2013), ‘The Virtual Brain Integrates computational modeling and multimodal neuroimaging’, Brain Connectivity 3(2), 121145.CrossRefGoogle ScholarPubMed
Robinson, D. A. (1968), ‘The electrical properties of metal microelectrodes’, Proceedings of the IEEE 56(6), 10651071.CrossRefGoogle Scholar
Robinson, R. A. & Stokes, R. H. (2002), Electrolyte Solutions, Courier Corporation, North Chelmsford, MA.Google Scholar
Rogers, N., Thunemann, M., Devor, A. & Gilja, V. (2020), ‘Impact of brain surface boundary conditions on electrophysiology and implications for electrocorticography’, Frontiers in Neuroscience 14(763).CrossRefGoogle ScholarPubMed
Romeni, S., Valle, G., Mazzoni, A. & Micera, S. (2020), ‘Tutorial: a computational framework for the design and optimization of peripheral neural interfaces’, Nature Protocols 15(10), 31293153.CrossRefGoogle ScholarPubMed
Rosanally, S., Mazza, F. & Hay, E. (2023), ‘Implications of reduced inhibition in schizophrenia on simulated human prefrontal microcircuit activity and EEG’. bioRxiv. https://doi.org/10.1101/2023.08.11.553052.CrossRefGoogle Scholar
Rosenberg, S. A. (1969), ‘A computer evaluation of equations for predicting the potential across biological membranes’, Biophysical Journal 9(4), 500.CrossRefGoogle ScholarPubMed
Rössert, C., Pozzorini, C., Chindemi, G., Davison, A. P., Eroe, C., King, J., Newton, T. H., Nolte, M., Ramaswamy, S., Reimann, M. W., Wybo, W., Gewaltig, M.-O., Gerstner, W., Markram, H., Segev, I. & Muller, E. (2016), ‘Automated point-neuron simplification of data-driven microcircuit models’. arXiv. https://doi.org/10.48550/arXiv.1604.00087.CrossRefGoogle Scholar
Roth, A. & van Rossum, M. C. W. (2009), ‘Modeling synapses’, in De Schutter, E., ed., Computational Modeling Methods for Neuroscientists, The MIT Press, Cambridge, MA, pp. 139160.CrossRefGoogle Scholar
Roth, B. & Basser, P. (1990), ‘A model of the stimulation of a nerve fiber by electromagnetic induction’, IEEE Transactions on Biomedical Engineering 37(6), 588597.CrossRefGoogle Scholar
Rotter, S. & Diesmann, M. (1999), ‘Exact digital simulation of time-invariant linear systems with applications to neuronal modeling’, Biological Cybernetics 81(5–6), 381402.CrossRefGoogle ScholarPubMed
Rudolph, M., Pelletier, J. G., Paré, D. & Destexhe, A. (2005), ‘Characterization of synaptic conductances and integrative properties during electrically induced EEG-activated states in neocortical neurons in vivo’, Journal of Neurophysiology 94(4), 28052821.CrossRefGoogle ScholarPubMed
Rush, S. & Driscoll, D. A. (1969), ‘EEG electrode sensitivity-an application of reciprocity’, IEEE Transactions on Biomedical Engineering 16(1), 1522.CrossRefGoogle ScholarPubMed
Sætra, M. J., Einevoll, G. T. & Halnes, G. (2020), ‘An electrodiffusive, ion conserving Pinsky-Rinzel model with homeostatic mechanisms’, PLoS Computational Biology 16(4), e1007661.CrossRefGoogle ScholarPubMed
Saha, S., Mamun, K. A., Ahmed, K., Mostafa, R., Naik, G. R., Darvishi, S., Khandoker, A. H. & Baumert, M. (2021), ‘Progress in brain computer interface: challenges and opportunities’, Frontiers in Systems Neuroscience 15, 578875.CrossRefGoogle ScholarPubMed
Sala, F. & Hernández-Cruz, A. (1990), ‘Calcium diffusion modeling in a spherical neuron. Relevance of buffering properties’, Biophysical Journal 57(2), 313324.CrossRefGoogle Scholar
Sanei, S. & Chambers, J. A. (2021), EEG Signal Processing and Machine Learning, John Wiley and Sons, Hoboken, NJ.CrossRefGoogle Scholar
Sanz-Leon, P., Knock, S. A., Spiegler, A. & Jirsa, V. K. (2015), ‘Mathematical framework for large-scale brain network modeling in The Virtual Brain’, NeuroImage 111, 385430.CrossRefGoogle ScholarPubMed
Sanz-Leon, P., Knock, S. A., Woodman, M. M., Domide, L., Mersmann, J., Mcintosh, A. R. & Jirsa, V. (2013), ‘The Virtual Brain: a simulator of primate brain network dynamics’, Frontiers in Neuroinformatics 7, 10.CrossRefGoogle Scholar
Sarvas, J. (1987), ‘Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem’, Physics in Medicine & Biology 32(1), 11.CrossRefGoogle ScholarPubMed
Savtchenko, L. P., Poo, M. M. & Rusakov, D. A. (2017), ‘Electrodiffusion phenomena in neuroscience: a neglected companion’, Nature Reviews Neuroscience 18(10), 598.CrossRefGoogle ScholarPubMed
Scheffer-Teixeira, R., Belchior, H., Leao, R., Ribeiro, S. & Tort, A. (2013), ‘On high-frequency field oscillations (>100 Hz) and the spectral leakage of spiking activity’, Journal of Neuroscience 33(4), 15351539.CrossRefGoogle ScholarPubMed
Schiller, J., Major, G., Koester, H. J. & Schiller, Y. (2000), ‘NMDA spikes in basal dendrites of cortical pyramidal neurons’, Nature 404(6775), 285289.CrossRefGoogle ScholarPubMed
Schomburg, E. W., Anastassiou, C. A., Buzsaki, G. & Koch, C. (2012), ‘The spiking component of oscillatory extracellular potentials in the rat hippocampus’, Journal of Neuroscience 32(34), 1179811811.CrossRefGoogle ScholarPubMed
Schroeder, C. E., Lindsley, R. W., Specht, C., Marcovici, A., Smiley, J. F. & Javitt, D. C. (2001), ‘Somatosensory input to auditory association cortex in the macaque monkey’, Journal of Neurophysiology 85, 13221327.CrossRefGoogle ScholarPubMed
Schroeder, C. E., Mehta, A. D. & Givre, S. J. (1998), ‘A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque’, Cerebral Cortex 8(7), 575592.CrossRefGoogle ScholarPubMed
Schuecker, J., Diesmann, M. & Helias, M. (2015), ‘Modulated escape from a metastable state driven by colored noise’, Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics 92, 052119.Google ScholarPubMed
Schwalger, T., Deger, M. & Gerstner, W. (2017), ‘Towards a theory of cortical columns: from spiking neurons to interacting neural populations of finite size’, PLoS Computational Biology 13(4), e1005507.CrossRefGoogle ScholarPubMed
Schwan, H. P. (1957), ‘Electrical properties of tissue and cell suspensions’, in Lawrence, J. & Tobias, C. A., eds., Advances in Biological and Medical Physics, Vol. 5, Academic Press (Elsevier), Cambridge, MA, pp. 147209.Google Scholar
Schwan, H. P. (1992), ‘Linear and nonlinear electrode polarization and biological materials’, Annals of Biomedical Engineering 20(3), 269288.CrossRefGoogle ScholarPubMed
Seeber, M., Cantonas, L. M., Hoevels, M., Sesia, T., Visser-Vandewalle, V. & Michel, C. M. (2019), ‘Subcortical electrophysiological activity is detectable with high-density EEG source imaging’, Nature Communications 10(1), 753.CrossRefGoogle ScholarPubMed
Segev, I., Rinzel, J. & Shepherd, G. M. E. (1995), The Theoretical Foundation of Dendritic Function - Selected Papers of Wilfrid Rall with Commentaries, MIT Press, Cambridge, MA.Google Scholar
Senk, J., Hagen, E., van Albada, S. J. & Diesmann, M. (2018), ‘Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space’. arXiv. https://doi.org/10.48550/arXiv.1805.10235.CrossRefGoogle Scholar
Senk, J., Korvasová, K., Schuecker, J., Hagen, E., Tetzlaff, T., Diesmann, M. & Helias, M. (2020), ‘Conditions for wave trains in spiking neural networks’, Physical Review Research 2(2), 023174.CrossRefGoogle Scholar
Shadlen, M. N. & Newsome, W. T. (1998), ‘The variable discharge of cortical neurons: implications for connectivity, computation, and information coding’, The Journal of Neuroscience 18(10), 38703896.CrossRefGoogle ScholarPubMed
Sharott, A. (2014), ‘Local field potential, methods of recording’, in Jaeger, D. & Jung, R., eds., Encyclopedia of Computational Neuroscience, Springer New York, New York, NY, pp. 13.Google Scholar
Sherman, M. A., Lee, S., Law, R., Haegens, S., Thorn, C. A., Hämäläinen, M. S., Moore, C. I. & Jones, S. R. (2016), ‘Neural mechanisms of transient neocortical beta rhythms: converging evidence from humans, computational modeling, monkeys, and mice’, Proceedings of the National Academy of Sciences 113(33): E48854894.CrossRefGoogle ScholarPubMed
Shifman, A. R. & Lewis, J. E. (2019), ‘Elfenn: a generalized platform for modeling ephaptic coupling in spiking neuron models’, Frontiers in Neuroinformatics 13, 35.CrossRefGoogle ScholarPubMed
Siegel, M., Donner, T. H. & Engel, A. K. (2012), ‘Spectral fingerprints of large-scale neuronal interactions’, Nature Reviews Neuroscience 13(2), 121134.CrossRefGoogle ScholarPubMed
Siegle, J. H., Jia, X., Durand, S., Gale, S., Bennett, C., Graddis, N., Heller, G., Ramirez, T. K., Choi, H., Luviano, J. A., Groblewski, P. A., Ahmed, R., Arkhipov, A., Bernard, A., Billeh, Y. N., Brown, D., Buice, M. A., Cain, N., Caldejon, S., Casal, L., Cho, A., Chvilicek, M., Cox, T. C., Dai, K., Denman, D. J., de Vries, S. E. J., Dietzman, R., Esposito, L., Farrell, C., Feng, D., Galbraith, J., Garrett, M., Gelfand, E. C., Hancock, N., Harris, J. A., Howard, R., Hu, B., Hytnen, R., Iyer, R., Jessett, E., Johnson, K., Kato, I., Kiggins, J., Lambert, S., Lecoq, J., Ledochowitsch, P., Lee, J. H., Leon, A., Li, Y., Liang, E., Long, F., Mace, K., Melchior, J., Millman, D., Mollenkopf, T., Nayan, C., Ng, L., Ngo, K., Nguyen, T., Nicovich, P. R., North, K., Ocker, G. K., Ollerenshaw, D., Oliver, M., Pachitariu, M., Perkins, J., Reding, M., Reid, D., Robertson, M., Ronellenfitch, K., Seid, S., Slaughterbeck, C., Stoecklin, M., Sullivan, D., Sutton, B., Swapp, J., Thompson, C., Turner, K., Wakeman, W., Whitesell, J. D., Williams, D., Williford, A., Young, R., Zeng, H., Naylor, S., Phillips, J. W., Reid, R. C., Mihalas, S., Olsen, S. R. & Koch, C. (2021), ‘Survey of spiking in the mouse visual system reveals functional hierarchy’, Nature 592(7852), 8692.CrossRefGoogle ScholarPubMed
Sinha, M. & Narayanan, R. (2015), ‘HCN channels enhance spike phase coherence and regulate the phase of spikes and lfps in the theta-frequency range’, Proceedings of the National Academy of Sciences of the United States of America 112(17), E2207E2216.Google ScholarPubMed
Sinha, M. & Narayanan, R. (2021), ‘Active dendrites and local field potentials: biophysical mechanisms and computational explorations’, Neuroscience 489, 111142.CrossRefGoogle ScholarPubMed
Siwy, Z. & Fuliński, A. (2002), ‘Origin of 1/fα noise in membrane channel currents’, Physical Review Letters 89(15), 158101.CrossRefGoogle Scholar
Skaar, J.-E. W., Stasik, A. J., Hagen, E., Ness, T. V. & Einevoll, G. T. (2020), ‘Estimation of neural network model parameters from local field potentials (LFPs)’, PLoS Computational Biology 16(3), e1007725.CrossRefGoogle ScholarPubMed
Skinner, F. K., Rich, S., Lunyov, A. R., Lefebvre, J. & Chatzikalymniou, A. P. (2021), ‘A hypothesis for theta rhythm frequency control in CA1 microcircuits’, Frontiers in Neural Circuits 15, 643360.CrossRefGoogle ScholarPubMed
Skou, J. C. (1957), ‘The influence of some cations on an adenosine triphosphatase from peripheral nerves’, Biochimica et Biophysica Acta 23(2), 394401.CrossRefGoogle Scholar
Softky, W. & Koch, C. (1993), ‘The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs’, The Journal of Neuroscience 13(1), 334350.CrossRefGoogle ScholarPubMed
Sokalski, T. & Lewenstam, A. (2001), ‘Application of Nernst–Planck and Poisson equations for interpretation of liquid-junction and membrane potentials in real-time and space domains’, Electrochemistry Communications 3(3), 107112.CrossRefGoogle Scholar
Solbrå, A., Bergersen, A. W., van den Brink, J., Malthe-Sørenssen, A., Einevoll, G. T. & Halnes, G. (2018), ‘A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons’, PLoS Computational Biology 14(10), 126.CrossRefGoogle ScholarPubMed
Somjen, G., Aitken, P., Giacchino, J. & McNamara, J. (1986), ‘Interstitial ion concentrations and paroxysmal discharges in hippocampal formation and spinal cord’, Advances in Neurology 44, 663680.Google ScholarPubMed
Somjen, G. G. (2004), Ions in the Brain: Normal Function, Seizures, and Stroke, Oxford University Press, Oxford.CrossRefGoogle Scholar
Somogyvari, Z., Cserpán, D., Ulbert, I. & Erdi, P. (2012), ‘Localization of single-cell current sources based on extracellular potential patterns: the spike csd method’, The European Journal of Neuroscience 36(10), 32993313.CrossRefGoogle ScholarPubMed
Song, Z., Cao, X. & Huang, H. (2018), ‘Electroneutral models for dynamic Poisson-Nernst-Planck systems’, Physical Review E 97(1), 012411.CrossRefGoogle ScholarPubMed
Speckmann, E.-J., Altrup, U., Lücke, A. & Köhling, R. (1994), ‘Principles of electrogenesis of slow field potentials in the brain’, in. Heinze, H.-J., Münte, T. F., Mangun, G. R., eds., Cognitive Electrophysiology, Birkhäuser Boston, Boston, MA, pp. 288299.CrossRefGoogle Scholar
Spruston, N. (2008), ‘Pyramidal neurons: dendritic structure and synaptic integration’, Nature Reviews Neuroscience 9(3), 206221.CrossRefGoogle ScholarPubMed
Srinivasan, R., Nunez, P. L. & Silberstein, R. B. (1998), ‘Spatial filtering and neocortical dynamics: estimates of EEG coherence’, IEEE Transactions on Biomedical Engineering 45(7), 814826.CrossRefGoogle ScholarPubMed
Stanton, M. (1983), ‘Origin and magnitude of transmembrane resting potential in living cells’, Philosophical Transactions of the Royal Society of London. B, Biological Sciences 301(1104), 85141.Google ScholarPubMed
Sterratt, D., Graham, B., Gillies, A., Einevoll, G. T. & Willshaw, D. (2023), Principles of Computational Modelling in Neuroscience, 2nd ed., Cambridge University Press, Cambridge.CrossRefGoogle Scholar
Stimberg, M., Brette, R. & Goodman, D. F. (2019), ‘Brian 2, an intuitive and efficient neural simulator’, eLife 8, e47314.CrossRefGoogle ScholarPubMed
Stuart, G., Spruston, N. & Häusser, M. (2007), Dendrites, Oxford University Press, Oxford.CrossRefGoogle Scholar
Stumpf, M. P. H. & Porter, M. A. (2012), ‘Critical truths about power laws’, Science 335(6069), 665666.CrossRefGoogle ScholarPubMed
Sundnes, J., Nielsen, B. F., Mardal, K. A., Cai, X., Lines, G. T. & Tveito, A. (2006), ‘On the computational complexity of the bidomain and the monodomain models of electrophysiology’, Annals of Biomedical Engineering 34(7), 10881097.CrossRefGoogle ScholarPubMed
Suzuki, M. & Larkum, M. E. (2017), ‘Dendritic calcium spikes are clearly detectable at the cortical surface’, Nature Communications 8(276), 110.CrossRefGoogle ScholarPubMed
Swadlow, H. A., Gusev, A. G. & Bezdudnaya, T. (2002), ‘Activation of a cortical column by a thalamocortical impulse’, Journal of Neuroscience 22(17), 77667773.CrossRefGoogle ScholarPubMed
Syková, E. & Nicholson, C. (2008), ‘Diffusion in brain extracellular space’, Physiological Reviews 88(4), 12771340.CrossRefGoogle ScholarPubMed
Sypert, G. & Ward, A. (1974), ‘Changes in extracellular potassium activity during neocortical propagated seizures’, Experimental Neurology 45(1), 1941.CrossRefGoogle ScholarPubMed
Sætra, M. J., Einevoll, G. T. & Halnes, G. (2021), ‘An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain’, PLoS Computational Biology 17(7), e1008143.CrossRefGoogle ScholarPubMed
Tahayori, B., Meffin, H., Dokos, S., Burkitt, A. N. & Grayden, D. B. (2012), ‘Modeling extracellular electrical stimulation: II. computational validation and numerical results’, Journal of Neural Engineering 9(6), 065006.CrossRefGoogle ScholarPubMed
Tahayori, B., Meffin, H., Sergeev, E. N., Mareels, I. M. Y., Burkitt, A. N. & Grayden, D. B. (2014), ‘Modelling extracellular electrical stimulation: IV. effect of the cellular composition of neural tissue on its spatio-temporal filtering properties’, Journal of Neural Engineering 11(6), 065005.CrossRefGoogle Scholar
Tao, A., Tao, L. & Nicholson, C. (2005), ‘Cell cavities increase tortuosity in brain extracellular space’, Journal of Theoretical Biology 234(4), 525536.CrossRefGoogle ScholarPubMed
Tao, L. & Nicholson, C. (2004), ‘Maximum geometrical hindrance to diffusion in brain extracellular space surrounding uniformly spaced convex cells’, Journal of Theoretical Biology 229(1), 5968.CrossRefGoogle ScholarPubMed
Taxidis, J., Anastassiou, C. A., Diba, K. & Koch, C. (2015), ‘Local field potentials encode place cell ensemble activation during hippocampal sharp wave ripples’, Neuron 87(3), 590604.CrossRefGoogle ScholarPubMed
Taylor, A. L., Goaillard, J.-M. & Marder, E. (2009), ‘How multiple conductances determine electrophysiological properties in a multicompartment model’, Journal of Neuroscience 29(17), 55735586.CrossRefGoogle Scholar
Teeter, C., Iyer, R., Menon, V., Gouwens, N., Feng, D., Berg, J., Szafer, A., Cain, N., Zeng, H., Hawrylycz, M., Koch, C. & Mihalas, S. (2018), ‘Generalized leaky integrate-and-fire models classify multiple neuron types’, Nature Communications 9(1), 709.CrossRefGoogle ScholarPubMed
Teleńczuk, B., Dehghani, N., Quyen, M. L. V., Cash, S. S., Halgren, E., Hatsopoulos, N. G. & Destexhe, A. (2017), ‘Local field potentials primarily reflect inhibitory neuron activity in human and monkey cortex’, Scientific Reports 7(1), 116.CrossRefGoogle ScholarPubMed
Teleńczuk, B., Teleńczuk, M. & Destexhe, A. (2020 a), ‘A kernel-based method to calculate local field potentials from networks of spiking neurons’, Journal of Neuroscience Methods 344, 108871.CrossRefGoogle ScholarPubMed
Telenczuk, M., Brette, R., Destexhe, A. & Telenczuk, B. (2018), ‘Contribution of the axon initial segment to action potentials recorded extracellularly’, eNeuro 5: ENEURO.0068–18.2018.CrossRefGoogle ScholarPubMed
Teleńczuk, M., Teleńczuk, B. & Destexhe, A. (2020 b), ‘Modelling unitary fields and the single-neuron contribution to local field potentials in the hippocampus’, Journal of Physiology 598(18), 39573972.CrossRefGoogle ScholarPubMed
Telkes, I., Jimenez-Shahed, J., Viswanathan, A., Abosch, A. & Ince, N. F. (2016), ‘Prediction of STN-DBS electrode implantation track in Parkinson’s disease by using local field potentials’, Frontiers in Neuroscience 10, 116.CrossRefGoogle ScholarPubMed
Telkes, I., Viswanathan, A., Jimenez-Shahed, J., Abosch, A., Ozturk, M., Gupte, A., Jankovic, J. & Ince, N. (2018), ‘Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson’s disease’, Proceedings of the National Academy of Sciences 115(36), E8567E8576.CrossRefGoogle ScholarPubMed
Tetzlaff, T., Helias, M., Einevoll, G. T. & Diesmann, M. (2012), ‘Decorrelation of neural-network activity by inhibitory feedback’, PLoS Computational Biology 8(8), e1002596.CrossRefGoogle ScholarPubMed
Thio, B. J., Aberra, A. S., Dessert, G. E. & Grill, W. M. (2022), ‘Ideal current dipoles are appropriate source representations for simulating neurons for intracranial recordings’, Clinical Neurophysiology 145, 2635.CrossRefGoogle ScholarPubMed
Thorbergsson, P. T., Garwicz, M., Schouenborg, J. & Johansson, A. J. (2012), ‘Computationally efficient simulation of extracellular recordings with multielectrode arrays’, Journal of Neuroscience Methods 211(1), 133144.CrossRefGoogle ScholarPubMed
Thunemann, M., Hossain, L., Ness, T. V., Rogers, N., Lee, K., Lee, S. H., Kılıç, K., Oh, H., Economo, M. N., Gilja, V., Einevoll, G. T., Dayeh, S. A. & Devor, A. (2022), ‘Imaging through windansee electrode arrays reveals a small fraction of local neurons following surface MUA’. bioRxiv. https://doi.org/10.1101/2022.09.01.506113.CrossRefGoogle Scholar
Thunemann, M., Ness, T. V., Kilic, K., Ferri, C. G., Sakadzic, S., Dale, A. M., Fainman, Y., Boas, D. A., Einevoll, G. T. & Devor, A. (2018), ‘Does light propagate better along pyramidal apical dendrites in cerebral cortex?’. Poster presentation. https://doi.org/10.1364/TRANSLATIONAL.2018.JW3A.56.CrossRefGoogle Scholar
Tivadar, R. I. & Murray, M. M. (2019), ‘A primer on electroencephalography and event-related potentials for organizational neuroscience’, Organizational Research Methods 22(1), 6994.CrossRefGoogle Scholar
Toll, J. S. (1956), ‘Causality and the dispersion relation: logical foundations’, Physical Review 104(6), 17601770.CrossRefGoogle Scholar
Tomsett, R. J., Ainsworth, M., Thiele, A., Sanayei, M., Chen, X., Gieselmann, M. A., Whittington, M. A., Cunningham, M. O. & Kaiser, M. (2015), ‘Virtual electrode recording tool for extracellular potentials (vertex): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue’, Brain Structure and Function 220(4), 23332353.CrossRefGoogle ScholarPubMed
Torres, D., Makarova, J., Ortuño, T., Benito, N., Makarov, V. A. & Herreras, O. (2019), ‘Local and volume-conducted contributions to cortical field potentials’, Cerebral Cortex 29(12), 52345254.CrossRefGoogle ScholarPubMed
Touboul, J. & Destexhe, A. (2017), ‘Power-law statistics and universal scaling in the absence of criticality’, Physical Review E 95(1), 012413.CrossRefGoogle ScholarPubMed
Tracey, B. & Williams, M. (2011), ‘Computationally efficient bioelectric field modeling and effects of frequency-dependent tissue capacitance’, Journal of Neural Engineering 8(3), 036017.CrossRefGoogle ScholarPubMed
Trainito, C., von Nicolai, C., Miller, E. K. & Siegel, M. (2019), ‘Extracellular spike waveform dissociates four functionally distinct cell classes in primate cortex’, Current Biology 29(18), 29732982.e5.CrossRefGoogle ScholarPubMed
Trappenberg, T. P. (2002), Fundamentals of Computational Neuroscience, Oxford University Press, Oxford.Google Scholar
Traub, R. D., Contreras, D., Cunningham, M. O., Murray, H., LeBeau, F. E. N., Roopun, A., Bibbig, A., Wilent, W. B., Higley, M. J. & Whittington, M. A. (2005), ‘Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts’, Journal of Neurophysiology 93(4), 21942232.CrossRefGoogle ScholarPubMed
Traub, R., Dudek, F., Taylor, C. P. & Knowles, W. D. (1985), ‘Simulation of hippocampal afterdischarges synchronized by electrical interactions’, Neuroscience 14(4), 10331038.CrossRefGoogle ScholarPubMed
Tripp, J. (1983), ‘Physical concepts and mathematical models’, in Williamson, S. J., Romani, G.-L., Kaufman, L. & Modena, I., eds., Biomagnetism, Springer, New York, pp. 101139.CrossRefGoogle Scholar
Tuttle, A., Diaz, J. R. & Mori, Y. (2019), ‘A computational study on the role of glutamate and NMDA receptors on cortical spreading depression using a multidomain electrodiffusion model’, PLoS Computational Biology 15(12), e1007455.CrossRefGoogle Scholar
Tveito, A., Jæger, K. H., Lines, G. T., Paszkowski, Ł., Sundnes, J., Edwards, A. G., Māki-Marttunen, T., Halnes, G. & Einevoll, G. T. (2017), ‘An evaluation of the accuracy of classical models for computing the membrane potential and extracellular potential for neurons’, Frontiers in Computational Neuroscience 11, 27.CrossRefGoogle ScholarPubMed
Tveito, A., Mardal, K.-A. & Rognes, M. E. (2021), Modeling Excitable Tissue: The EMI Framework, Springer Nature, Cham, Switzerland.CrossRefGoogle Scholar
Uhlirova, H., Kılıc, K., Tian, P., Sakadz, S., Saisan, P. A., Gagnon, L., Thunemann, M., Nizar, K., Yasseen, M. A. Jr, D. J. H., Vandenberghe, M., Djurovic, S., Andreassen, O. A., Silva, G. A., Masliah, E., Kleinfeld, D., Vinogradov, S., Buxton, R. B., Einevoll, G. T., Boas, D. A., Dale, A. M. & Devor, A. (2016), ‘The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements’, Proceedings of the Royal Society of London. Series B Biological Sciences 371(1705), 20150356.Google ScholarPubMed
Ulbert, I., Halgren, E., Heit, G. & Karmos, G. (2001), ‘Multiple microelectrode-recording system for human intracortical applications’, Journal of Neuroscience Methods 106(1), 6979.CrossRefGoogle ScholarPubMed
Ullah, G., Cressman, J. R., Barreto, E. & Schiff, S. J. (2009), ‘The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states. II. Network and glial dynamics’, Journal of Computational Neuroscience 26(2), 171183.CrossRefGoogle ScholarPubMed
Van Geit, W., Gevaert, M., Chindemi, G., Rössert, C., Courcol, J.-D., Muller, E., Schürmann, F., Segev, I. & Markram, H. (2016), ‘BluePyOpt: leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience’, Frontiers in Neuroinformatics 10, 118.CrossRefGoogle ScholarPubMed
Van Uitert, R., Weinstein, D. & Johnson, C. (2003), ‘Volume currents in forward and inverse magnetoencephalographic simulations using realistic head models’, Annals of Biomedical Engineering 31(1), 2131.CrossRefGoogle ScholarPubMed
van Vreeswijk, C. & Sompolinsky, H. (1997), ‘Irregular firing in cortical circuits with inhibition/excitation balance’, in Bower, J. M., ed., Computational Neuroscience, Springer, US, New York, pp. 209213.CrossRefGoogle Scholar
Vermaas, M., Piastra, M. C., Oostendorp, T. F., Ramsey, N. F. & Tiesinga, P. H. E. (2020 a), ‘FEMfuns: a volume conduction modeling pipeline that includes resistive, capacitive or dispersive tissue and electrodes’, Neuroinformatics 18(4), 569580.CrossRefGoogle ScholarPubMed
Vermaas, M., Piastra, M. C., Oostendorp, T., Ramsey, N. & Tiesinga, P. H. (2020 b), ‘When to include ecog electrode properties in volume conduction models’, Journal of Neural Engineering 17(5), 056031.CrossRefGoogle ScholarPubMed
Vissani, M., Palmisano, C., Volkmann, J., Pezzoli, G., Micera, S., Isaias, I. U. & Mazzoni, A. (2021), ‘Impaired reach-to-grasp kinematics in Parkinsonian patients relates to dopamine-dependent, subthalamic beta bursts’, npj Parkinson’s Disease 7(1), 53.CrossRefGoogle ScholarPubMed
Viswam, V., Obien, M. E. J., Franke, F., Frey, U. & Hierlemann, A. (2019), ‘Optimal electrode size for multi-scale extracellular-potential recording from neuronal assemblies’, Frontiers in Neuroscience 13, 123.CrossRefGoogle ScholarPubMed
Vorwerk, J., Cho, J.-H., Rampp, S., Hamer, H., Knosche, T. R. & Wolters, C. H. (2014), ‘A guideline for head volume conductor modeling in EEG and MEG’, NeuroImage 100, 590607.CrossRefGoogle ScholarPubMed
Wagner, T., Eden, U., Rushmore, J., Russo, C. J., Dipietro, L., Fregni, F., Simon, S., Rotman, S., Pitskel, N. B., Ramos-Estebanez, C., Pascual-Leone, A., Grodzinsky, A. J., Zahn, M. & Valero-Cabré, A. (2014), ‘Impact of brain tissue filtering on neurostimulation fields: a modeling study’, NeuroImage 85(3), 10481057.CrossRefGoogle Scholar
Waters, J., Schaefer, A. & Sakmann, B. (2005), ‘Backpropagating action potentials in neurones: measurement, mechanisms and potential functions’, Progress in Biophysics and Molecular Biology 87(1), 145170.CrossRefGoogle ScholarPubMed
Wei, Y., Ullah, G. & Schiff, S. J. (2014), ‘Unification of neuronal spikes, seizures, and spreading depression’, Journal of Neuroscience 34(35), 1173311743.CrossRefGoogle ScholarPubMed
Whittingstall, K. & Logothetis, N. K. (2013), ‘Physiological foundations of neural signals’, Principles of Neural Coding 15, 146.Google Scholar
Wilson, C. J. (1984), ‘Passive cable properties of dendritic spines and spiny neurons’, Journal of Neuroscience 4(1), 281297.CrossRefGoogle ScholarPubMed
Wilting, J. & Priesemann, V. (2019), ‘25 years of criticality in neuroscience - established results, open controversies, novel concepts’, Current Opinion in Neurobiology 58, 105111.CrossRefGoogle ScholarPubMed
Wolters, C. H., Anwander, A., Tricoche, X., Weinstein, D., Koch, M. A. & MacLeod, R. S. (2006), ‘Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: a simulation and visualization study using high-resolution finite element modeling’, NeuroImage 30(3), 813826.CrossRefGoogle Scholar
Wybo, W. A., Jordan, J., Ellenberger, B., Mengual, U. M., Nevian, T. & Senn, W. (2021), ‘Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses’, eLife 10, 126.CrossRefGoogle ScholarPubMed
Wybo, W. A. M., Stiefel, K. M. & Torben-Nielsen, B. (2013), ‘The green’s function formalism as a bridge between single- and multi-compartmental modeling’, Biological Cybernetics 107(6), 685694.CrossRefGoogle ScholarPubMed
Xing, D., Yeh, C.-I. & Shapley, R. M. (2009), ‘Spatial spread of the local field potential and its laminar variation in visual cortex’, Journal of Neuroscience 29(37), 1154011549.CrossRefGoogle ScholarPubMed
Xu, N. L., Harnett, M. T., Williams, S. R., Huber, D., O’Connor, D. H., Svoboda, K. & Magee, J. C. (2012), ‘Nonlinear dendritic integration of sensory and motor input during an active sensing task’, Nature 492, 247251.CrossRefGoogle ScholarPubMed
Yaron-Jakoubovitch, A., Jacobson, G. A., Koch, C., Segev, I. & Yarom, Y. (2008), ‘A paradoxical isopotentiality: a spatially uniform noise spectrum in neocortical pyramidal cells’, Frontiers in Cellular Neuroscience 2, 3.CrossRefGoogle ScholarPubMed
Yger, P., Spampinato, G. L., Esposito, E., Lefebvre, B., Deny, S., Gardella, C., Stimberg, M., Jetter, F., Zeck, G., Picaud, S., Duebel, J. & Marre, O. (2018), ‘A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo’, eLife 7, e34518.CrossRefGoogle ScholarPubMed
Zandt, B.-J., ten Haken, B., van Dijk, J. G. & van Putten, M. J. (2011), ‘Neural dynamics during anoxia and the “wave of death”’, PLoS ONE 6(7), e22127.CrossRefGoogle Scholar
Zempel, J. M., Politte, D. G., Kelsey, M., Verner, R., Nolan, T. S., Babajani-Feremi, A., Prior, F. & Larson-Prior, L. J. (2012), ‘Characterization of scale-free properties of human electrocorticography in awake and slow wave sleep states’, Frontiers in Neurology 3, 76.CrossRefGoogle ScholarPubMed
Zeng, F.-G., Rebscher, S., Harrison, W., Sun, X. & Feng, H. (2008), ‘Cochlear implants: system design, integration, and evaluation’, IEEE Reviews in Biomedical Engineering 1, 115142.CrossRefGoogle ScholarPubMed
Zeng, H. & Sanes, J. R. (2017), ‘Neuronal cell-type classification: challenges, opportunities and the path forward’, Nature Reviews Neuroscience 18(9), 530546.CrossRefGoogle ScholarPubMed
Zhuchkova, E., Remme, M. W. H. & Schreiber, S. (2013), ‘Somatic versus dendritic resonance: differential filtering of inputs through non-uniform distributions of active conductances’, PLoS ONE 8(11), e78908.CrossRefGoogle ScholarPubMed
Ziegler, E., Chellappa, S. L., Gaggioni, G., Ly, J. Q., Vandewalle, G., André, E., Geuzaine, C. & Phillips, C. (2014), ‘A finite-element reciprocity solution for EEG forward modeling with realistic individual head models’, NeuroImage 103, 542551.CrossRefGoogle ScholarPubMed
Zimmermann, J. & van Rienen, U. (2021), ‘Ambiguity in the interpretation of the low-frequency dielectric properties of biological tissues’, Bioelectrochemistry 140, 107773.CrossRefGoogle ScholarPubMed

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