A neural mass model based on single cell dynamics to model pathophysiology

详细信息    查看全文

• 作者：Bas-Jan Zandt (1)
  Sid Visser (2)
  Michel J. A. M. van Putten (1)
  Bennie ten Haken (1)
  
• 关键词：Mean field ; Neural mass ; Recurring network ; Firing rate curve ; Pathology ; Hodgkin ; Huxley ; Variance ; Channel blockers
• 刊名：Journal of Computational Neuroscience
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：37
• 期：3
• 页码：549-568
• 全文大小：2,285 KB
• 参考文献：1. Allen, C., & Stevens, C.F. (1994). An evaluation of causes for unreliability of synaptic transmission. / Proceedings National Academy Science USA, / 383 (10), 380鈥?0.
  2. Amit, D., & Brunel, N. (1997). Dynamics of a recurrent network of spiking neurons before and following learning Network Computation in Neural Systems.
  3. Baladron, J., Fasoli, D., Faugeras, O., Touboul, J. (2012). Mean-field description and propagation of chaos in networks of hodgkin-huxley and fitzhugh-nagumo neurons. / Journal Mathematics Neuroscience, / 2 (1), 10. doi:10.1186/2190-8567-2-10 . CrossRef
  4. Bazhenov, M., Timofeev, I., Frhlich, F., Sejnowski, T.J. (2008). Cellular and network mechanisms of electrographic seizures. / Drug Discovery Today Dis Models, / 5 (1), 45鈥?7. doi:10.1016/j.ddmod.2008.07.005 . CrossRef
  5. Bhattacharya, B.S., Coyle, D., Maguire, L.P. (2011). A thalamo-cortico-thalamic neural mass model to study alpha rhythms in Alzheimer鈥檚 disease. / Neural networks : the official journal of the International Neural Network Society, / 24 (6), 631鈥?5. doi:10.1016/j.neunet.2011.02.009 . CrossRef
  6. Chizhov, A., & Graham, L. (2007). Population model of hippocampal pyramidal neurons, linking a refractory density approach to conductance-based neurons. / Physical Review E, / 75(1) (011), 924. doi:10.1103/PhysRevE.75.011924 .
  7. De Schutter, E. (2010). Computational Modeling Methods for Neuroscientists. / Mit Press, chap, 6. URL http://books.google.nl/books/about/Computational_Modeling_Methods_for_Neuro.html?id=20RvPgAACAAJ&pgis=1.
  8. Deco, G., Jirsa, V.K., Pa, Robinson, Breakspear, M., Friston, K. (2008). The dynamic brain: from spiking neurons to neural masses and cortical fields. / PLoS computational biology, / 4(8) (e1000), 092. doi:10.1371/journal.pcbi.1000092 .
  9. Dreier, J.P. (2011). The role of spreading depression, spreading depolarization and spreading ischemia in neurological disease. / Nature medicine, / 17 (4), 439鈥?7. doi:10.1038/nm.2333 . CrossRef
  10. Faugeras, O., Touboul, J., Cessac, B. (2009). A constructive mean-field analysis of multi-population neural networks with random synaptic weights and stochastic inputs. / Frontiers in computational neuroscience, / 3 (February), 1. doi:10.3389/neuro.10.001.2009 .
  11. Fr枚hlich, F., Bazhenov, M., Iragui-Madoz, V., Sejnowski, T.J. (2008). Potassium dynamics in the epileptic cortex: new insights on an old topic. / Neuroscientist, / 14 (5), 422鈥?33. doi:10.1177/1073858408317955 . CrossRef
  12. Galtier, M.N., & Touboul, J. (2013). Macroscopic equations governing noisy spiking neuronal populations with linear synapses. / PLoS One, / 8(11) (e78), 917. doi:10.1371/journal.pone.0078917 .
  13. Grefkes, C., & Fink, G.R. (2011). Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches. / Brain : a journal of neurology, / 134 (Pt 5), 1264鈥?6. doi:10.1093/brain/awr033 . CrossRef
  14. Hindriks, R., & Putten, van MJaM (2012). Meanfield modeling of propofol-induced changes in spontaneous EEG rhythms. / NeuroImage, / 60 (4), 2323鈥?4. doi:10.1016/j.neuroimage.2012.02.042 . CrossRef
  15. Hines, M.L., Morse, T., Migliore, M., Carnevale, N.T., Shepherd, G.M. (2004). Modeldb: A database to support computational neuroscience. / Journal Computational Neuroscience, / 17 (1), 7鈥?1. doi:10.1023/B:JCNS.0000023869.22017.2e . CrossRef
  16. Hocepied, G., Legros, B., Van Bogaert, P., Grenez, F., Nonclercq, A. (2013). Early detection of epileptic seizures based on parameter identification of neural mass model. / Computer Biology Medicine, / 43 (11), 1773鈥?782. doi:10.1016/j.compbiomed.2013.08.022 . CrossRef
  17. Holt, G. (1997). / A critical reexamination of some assumptions and implications of cable theory in neurobiology. PhD thesis: California Institute of Technology. URL http://lnc.usc.edu/holt/papers/thesis/.
  18. Hutt, A. (2012). The population firing rate in the presence of GABAergic tonic inhibition in single neurons and application to general anaesthesia. / Cognitive neurodynamics, / 6 (3), 227鈥?7. doi:10.1007/s11571-011-9182-9 . CrossRef
  19. Hutt, A. (2013). The anesthetic propofol shifts the frequency of maximum spectral power in eeg during general anesthesia: analytical insights from a linear model. / Front Computational Neuroscience, / 7, 2. doi:10.3389/fncom.2013.00002 . CrossRef
  20. Izhikevich, E.M. (2007). / Dynamical Systems in Neuroscience The Geometry of Excitability and Bursting: Computational neuroscience, vol First. MIT Press. URL http://www.amazon.com/dp/0262514206.
  21. Jansen, B.H., & Rit, V.G. (1995). Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. / Biology Cybernetics, / 73 (4), 357鈥?66. CrossRef
  22. Liley, D.T.J., Cadusch, P.J., Dafilis, M.P. (2002). A spatially continuous mean field theory of electrocortical activity. / Network (Bristol England), / 13 (1), 67鈥?13. CrossRef
  23. Manwani, A., & Koch, C. (1999). Detecting and estimating signals in noisy cable structure, i: neuronal noise sources. / Neural Computation, / 11 (8), 1797鈥?829. CrossRef
  24. Marreiros, A.C., Daunizeau, J., Kiebel, S.J., Friston, K.J. (2008). Population dynamics: variance and the sigmoid activation function. / NeuroImage, / 42 (1), 147鈥?7. doi:10.1016/j.neuroimage.2008.04.239 . CrossRef
  25. Meisler, M.H., & Kearney, J.A. (2005). Sodium channel mutations in epilepsy and other neurological disorders. / Journal Clinical Investigation, / 115 (8), 2010鈥?017. doi:10.1172/JCI25466 . CrossRef
  26. Moran, R., Pinotsis, D.A., Friston, K. (2013). Neural masses and fields in dynamic causal modeling. / Front Computational Neuroscience, / 7, 57. doi:10.3389/fncom.2013.00057 . CrossRef
  27. Ostojic, S., & Brunel, N. (2011). From spiking neuron models to linear-nonlinear models. / PLoS computational biology, / 7(1) (e1001), 056. doi:10.1371/journal.pcbi.1001056 .
  28. van Putten M.J., & Zandt B.J. (2013). Neural Mass modeling for predicting seizures. / Clinical Neurophysiology. doi:10.1016/j.clinph.2013.11.013 .
  29. Robinson, P.A., Rennie, C.J., Wright, J.J., Bahramali, H., Gordon, E., Rowe, D.L. (2001). Prediction of electroencephalographic spectra from neurophysiology. / Physics Review E Statistics Nonlinear Soft Matter Physics, / 63(2 Pt 1) (021), 903.
  30. Pa, Robinson, Wu, H., Kim, J.W. (2008). Neural rate equations for bursting dynamics derived from conductance-based equations. / Journal of theoretical biology, / 250 (4), 663鈥?2. doi:10.1016/j.jtbi.2007.10.020 . CrossRef
  31. Schevon, C.A., Ng, S.K., Cappell, J., Goodman, R.R., McKhann, G Jr, Waziri, A., Branner, A., Sosunov, A., Schroeder, C.E., Emerson, R.G. (2008). Microphysiology of epileptiform activity in human neocortex. / Journal Clinical Neurophysiol, / 25 (6), 321鈥?30. doi:10.1097/WNP.0b013e31818e8010 . CrossRef
  32. Shriki, O., Hansel, D., Sompolinsky, H. (2003). Rate models for conductance-based cortical neuronal networks. / Neural computation, / 15 (8), 1809鈥?1. doi:10.1162/08997660360675053 . CrossRef
  33. Somjen, G. (2004). / Ions in the Brain: Normal Function, Seizures and Stroke. USA: Oxford University Press. http://books.google.nl/books?id=yaNrAAAAMAAJ.
  34. Somjen, G.G. (2001). Mechanisms of spreading depression and hypoxic spreading depression-like depolarization. / Physiology Reviews, / 81 (3), 1065鈥?096.
  35. Stead, M., Bower, M., Brinkmann, B.H., Lee, K., Marsh, W.R., Meyer, F.B., Litt, B., Van Gompel, J., Worrell, G.A. (2010). Microseizures and the spatiotemporal scales of human partial epilepsy. / Brain, / 133 (9), 2789鈥?797. doi:10.1093/brain/awq190 . CrossRef
  36. Tjepkema-Cloostermans, M.C., Hindriks, R., Hofmeijer, J., van Putten MJAM (2013). Generalized periodic discharges after acute cerebral ischemia: Reflection of selective synaptic failure?. / Clinical Neurophysiol. doi:10.1016/j.clinph.2013.08.005 .
  37. Touboul, J., Hermann, G., Faugeras, O. (2012). Noise-induced behaviors in neural mean field dynamics. / SIAM Journal on Applied Dynamical Systems, / 11 (1), 49鈥?1. doi:10.1137/110832392 . http://epubs.siam.org/doi/pdf/10.1137/110832392. CrossRef
  38. Victor, J.D., Drover, J.D., Conte, M.M., Schiff, N.D. (2011). Mean-field modeling of thalamocortical dynamics and a model-driven approach to EEG analysis. / Proceedings of the National Academy of Sciences of the United States of America 108 Suppl, / 15, 631鈥?. doi:10.1073/pnas.1012168108 .
  39. Visser, S., & Van Gils, S. (2014). Lumping Izhikevich neurons. / EPJ Nonlinear Biomedical Physics, / 2 (1), 6. doi:10.1140/epjnbp19 . URL http://www.epjnonlinearbiomedphys.com/content/2/1/6.
  40. Wilson, H.R., & Cowan, J.D. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. / Biophysical journal, / 12 (1), 1鈥?4. doi:10.1016/S0006-3495(72)86068-5 . CrossRef
  41. Zandt, B.J., ten Haken, B., van Dijk, J.G., van Putten, M J.A.M. (2011). Neural dynamics during anoxia and the 鈥漺ave of death鈥? / PLoS One, / 6(7) (e22), 127. doi:10.1371/journal.pone.0022127 .
  42. Ziburkus, J., Cressman, J.R., Barreto, E., Schiff, S.J. (2006). Interneuron and pyramidal cell interplay during / in vitro seizure-like events. / Journal Neurophysiology, / 95 (6), 3948鈥?954. doi:10.1152/jn.01378.2005 . CrossRef
  
• 作者单位：Bas-Jan Zandt (1)
  Sid Visser (2)
  Michel J. A. M. van Putten (1)
  Bennie ten Haken (1)
  
  1. MIRA - Institute for Biomedical Technology and Technical Medicine, University of Twente, P.O. Box 217, 7500, AE, Enschede, The Netherlands
  2. School of Mathematical Sciences, University of Nottingham, University Park, NG7 2RD,, Nottingham, UK
  
• ISSN：1573-6873

文摘

Neural mass models are successful in modeling brain rhythms as observed in macroscopic measurements such as the electroencephalogram (EEG). While the synaptic current is explicitly modeled in current models, the single cell electrophysiology is not taken into account. To allow for investigations of the effects of channel pathologies, channel blockers and ion concentrations on macroscopic activity, we formulate neural mass equations explicitly incorporating the single cell dynamics by using a bottom-up approach. The mean and variance of the firing rate and synaptic input distributions are modeled. The firing rate curve (F(I)-curve) is used as link between the single cell and macroscopic dynamics. We show that this model accurately reproduces the behavior of two populations of synaptically connected Hodgkin-Huxley neurons, also in non-steady state.