Advertisement

Biological Cybernetics

, Volume 112, Issue 5, pp 465–482 | Cite as

Physiology-based ERPs in normal and abnormal states

  • M S Zobaer
  • P A Robinson
  • C C Kerr
Original Article
  • 47 Downloads

Abstract

Evoked response potentials (ERPs) and other transients are modeled as impulse responses using physiology-based neural field theory (NFT) of the corticothalamic system of neural activity in the human brain that incorporates synaptic and dendritic dynamics, firing response, axonal propagation, and corticocortical and corticothalamic pathways. The properties of model-predicted ERPs are explored throughout the stability zone of the corticothalamic system, and predicted time series and wavelet spectra are also analyzed. This provides a unified treatment of predicted ERPs for both normal and abnormal states within the brain’s stability zone, including likely parameters to represent abnormal states of reduced arousal.

Keywords

Evoked response potentials Neural field theory Corticothalamic system Modeling Neurophysiology 

Notes

Acknowledgements

We thank R. Townsend for assistance with MATLAB and S. Assadzadeh for helpful discussions. This work was supported by the Australian Research Council Center of Excellence for Integrative Brain Function (ARC Center of Excellence Grant CE140100007), Australian Research Council Laureate Fellowship Grant FL140100025, and Discovery Early Career Research Award DE140101375.

References

  1. Abeysuriya RG, Rennie CJ, Robinson PA (2014) Prediction and verification of nonlinear sleep spindle harmonic oscillations. J Theor Biol 344:70–77CrossRefPubMedCentralPubMedGoogle Scholar
  2. Abeysuriya RG, Rennie CJ, Robinson PA (2015) Physiologically based arousal state estimation and dynamics. J Neurosci Methods 253:55–69CrossRefPubMedCentralPubMedGoogle Scholar
  3. Barlow JS (1957) An electronic method for detecting evoked responses of the brain and for reporting their average wave forms. Electroencephalogr Clin Neurophysiol 9:340–343CrossRefPubMedCentralPubMedGoogle Scholar
  4. Bartnik EA, Blinowska KJ, Durka PJ (1992) Single evoked potential reconstruction by means of wavelet transform. Biol Cybern 67:175–181CrossRefPubMedCentralPubMedGoogle Scholar
  5. Basar E (1980) EEG-brain dynamics: relation between EEG and brain evoked potentials. Elsevier/North-Holland Biomedical Press, New YorkGoogle Scholar
  6. Breakspear M, Roberts JA, Terry JR, Rodrigues S, Mahant N, Robinson PA (2006) A unifying explanation of primary generalized seizures through nonlinear brain modeling and bifurcation analysis. Cereb Cortex 16:1296–313CrossRefPubMedCentralPubMedGoogle Scholar
  7. Clearwater JM, Kerr CC, Rennie CJ, Robinson PA (2008) Neural mechanisms of ERP change: combining insights from electrophysiology and mathematical modeling. J Integr Neurosci 7:529–550CrossRefPubMedCentralPubMedGoogle Scholar
  8. Contreras D, Destexhe A, Sejnowski TJ, Steriade M (1997) Spatiotemporal patterns of spindle oscillations in cortex and thalamus. J Neurosci 17:1179–1196CrossRefPubMedCentralPubMedGoogle Scholar
  9. da Lopes Silva F (1991) Neural mechanisms underlying brain waves. Electroencephalogr Clin Neurophysiol 79:81–93CrossRefGoogle Scholar
  10. da Lopes Silva FH, Hoeks A, Smits H, Zetterberg LH (1974) Model of brain rhythmic activity. Kybernetik 15:27–37CrossRefGoogle Scholar
  11. Dijk DJ, Hayes B, Czeisler CA (1993) Dynamics of electroencephalographic sleep spindles and slow wave activity in men: effect of sleep deprivation. Brain Res 626:190–199CrossRefPubMedCentralPubMedGoogle Scholar
  12. Freeman WJ (1975) Mass action in the nervous system, 1st edn. Academic Press/Elsevier, New YorkGoogle Scholar
  13. Gennaro LD, Ferrara M (2003) Sleep spindles: an overview. Sleep Med Rev 7:423–440CrossRefPubMedCentralPubMedGoogle Scholar
  14. Gordon E, Cooper N, Rennie C, Hermens D, Williams LM (2005) Integrative neuroscience: the role of a standardized database. Clin EEG Neurosci 36:64–75CrossRefPubMedCentralPubMedGoogle Scholar
  15. Halasz P (2005) K-complex, a reactive EEG graphoelement of NREM sleep: an old chap in a new garment. Sleep Med Rev 9:391–412CrossRefPubMedCentralPubMedGoogle Scholar
  16. Hall JW (1992) Handbook of auditory evoked responses. Allyn and Bacon, BostonGoogle Scholar
  17. Kerr CC, Rennie CJ, Robinson PA (2008) Physiology-based modelling of cortical auditory evoked potentials. Biol Cybern 98:171–184CrossRefPubMedCentralPubMedGoogle Scholar
  18. Kerr CC, Rennie CJ, Robinson PA (2011) Model-based analysis and quantification of age trends in auditory evoked potentials. Clin Neurophysiol 122:134–147CrossRefPubMedCentralPubMedGoogle Scholar
  19. Kerr CC, van Albada S, Neymotin S, Chadderdon G, Robinson PA, Lytton W (2013) Cortical information flow in Parkinson’s disease: a composite network/field model. Front Comput Neurosci 7:1–14CrossRefGoogle Scholar
  20. Kim JW, Robinson PA (2007) Compact dynamical model of brain activity. Phys Rev E 75:e031907Google Scholar
  21. Loomis AL, Harvey EN, Hobart GA (1938) Distribution of disturbance patterns in the human electroencephalogram, with special reference to sleep. J Neurophysiol 13:231–256Google Scholar
  22. Luck SJ (2014) An introduction to the event related potential technique, 2nd edn. MIT Press, MassachusettsGoogle Scholar
  23. McCormick D, Bal T (1997) Sleep and arousal: thalamocortical mechanisms. Annu Rev Neurosci 20:185–215CrossRefPubMedCentralPubMedGoogle Scholar
  24. Merry RJE (2005) Wavelet theory and applications: a literature study. Eindhoven University of Technology, EindhovenGoogle Scholar
  25. Muller EJ, van Albada SJ, Kim JW, Robinson PA (2017) Unified neural field theory of brain dynamics underlying oscillations in Parkinson’s disease and generalized epilepsies. J Theor Biol 428:132–146CrossRefPubMedCentralPubMedGoogle Scholar
  26. Nordby H, Hugdahl K, Stickgold R, Bronnick KS, Hobson JA (1996) Event-related potentials (ERPs) to deviant auditory stimuli during sleep and waking. Neurosci Rep 7:1082–1086Google Scholar
  27. Nunez PL, Srinivasan R (1981) Electric fields of the brain: the neurophysics of EEG. In: Nunez PL (ed) Oxford University Press, OxfordGoogle Scholar
  28. Nunez PL, Srinivasan R (1993) Implications of recording strategy for estimates of neocortical dynamics with electroencephalography. Clin Neurophysiol 3:257–266Google Scholar
  29. Nunez PL, Srinivasan R (2006) A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness. Clin Neurophysiol 117:2424–2435CrossRefPubMedCentralPubMedGoogle Scholar
  30. O’Connor SC, Robinson PA (2004) Spatially uniform and nonuniform analyses of electroencephalographic dynamics, with application to the topography of the alpha rhythm. Phys Rev E 70:011911CrossRefGoogle Scholar
  31. Olver FW, Lozier DW, Boisvert RF, Clark CW (2000) NIST handbook of mathematical functions. Cambridge University Press, New YorkGoogle Scholar
  32. Penny WD, Kiebel SJ, Kilner JM, Rugg MD (2002) Event-related brain dynamics. Trends Neurosci 25:387–389CrossRefPubMedCentralPubMedGoogle Scholar
  33. Polikar R (1996) The wavelet tutorial, 2nd edn. College of Engineering, Rowan University, New JerseyGoogle Scholar
  34. Purves SJ, Low MD, Galloway J (1981) A comparison of visual, brainstem auditory, and somatosensory evoked potentials in multiple sclerosis. Can J Neurol Sci 8:15–19CrossRefPubMedCentralPubMedGoogle Scholar
  35. Regan DM (1979) Electrical responses evoked from the human brain. Sci Am 6:134–146CrossRefGoogle Scholar
  36. Rennie CJ, Robinson PA, Wright JJ (1999) Effects of local feedback on dispersion of electrical waves in the cerebral cortex. Phys Rev E 59:3320–3329CrossRefGoogle Scholar
  37. Rennie CJ, Robinson PA, Wright JJ (2002) Unified neurophysical model of EEG spectra and evoked potentials. Biol Cybern 86:457–471CrossRefPubMedCentralPubMedGoogle Scholar
  38. Roberts JA, Robinson PA (2012) Corticothalamic dynamics: structure of parameter space, spectra, instabilities, and reduced model. Phys Rev E 85:011910CrossRefGoogle Scholar
  39. Robinson PA (2017) The balanced and introspective brain. J R Soc Interface 14:1–8CrossRefGoogle Scholar
  40. Robinson PA, Rennie CJ, Wright JJ (1997) Propagation and stability of waves of electrical activity in the cerebral cortex. Phys Rev E 56:826–840CrossRefGoogle Scholar
  41. Robinson PA, Rennie CJ, Wright JJ, Bourke PD (1998) Steady states and global dynamics of electrical activity in the cerebral cortex. Phys Rev E 58:3557–3571CrossRefGoogle Scholar
  42. Robinson PA, Loxley PN, O’Connor SC, Rennie CJ (2001) Model analysis of corticothalamic dynamics, electroencephalographic spectra, and evoked potentials. Phys Rev E 63:041909CrossRefGoogle Scholar
  43. Robinson PA, Rennie CJ, Rowe DL (2002) Dynamics of large-scale brain activity in normal arousal states and epileptic seizures. Phys Rev E 65:041924CrossRefGoogle Scholar
  44. Robinson PA, Rennie CJ, Rowe DL, O’Connor SC (2004) Estimation of multiscale neurophysiologic parameters by electroencephalographic denotes. Hum Brain Mapp 23:53–72CrossRefPubMedCentralPubMedGoogle Scholar
  45. Robinson PA, Rennie CJ, Rowe DL, O’Connor SC, Gordon E (2005) Multiscale brain modelling. Philoso Trans R Soc B Bio Sci 360:1043–1050CrossRefGoogle Scholar
  46. Robinson PA, Chen PC, Yang L (2008) Physiologically based calculation of steady-state evoked potentials and cortical wave velocities. Biol Cybern 98:1–10CrossRefPubMedCentralPubMedGoogle Scholar
  47. Robinson PA, Rennie CJ, Phillips AJK, Kim JW, Roberts JA (2010) Phase transitions in physiologically based multiscale mean-field brain models. In: Steyn-Ross DA, Steyn-Ross M (eds) Modeling phase transitions in the brain. Springer Series in Computational Neuroscience. Springer, New YorkGoogle Scholar
  48. Robinson PA, Phillips AJK, Fulcher BD, Puckeridge M, Roberts JA, Rennie CJ (2011) Quantitative Modeling of Sleep Dynamics. In: Destexhe A, Brette R (eds) Sleep and anesthesia: neural correlates in theory and experiment. Springer Series in Computational Neuroscience. Springer, New YorkGoogle Scholar
  49. Robinson PA, Postnova S, Abeysuriya RG, Kim JW, Roberts JA, McKenzie-Sell L, Karanjai A, Kerr CC, Fung F, Anderson R, Breakspear MJ, Drysdale PM, Fulcher BD, Phillips AJK, Rennie CJ, Yin G (2015) A multiscale ‘working brain’ model. In: Bhattacharya B, Chowdhury F (eds) Validating computational models in neurological and psychiatric disorders. Springer Series in Computational Neuroscience. Springer, New YorkGoogle Scholar
  50. Sanz-Leona P, Robinson PA (2017) Multistability in the corticothalamic system. J Theor Biol 432:141–156CrossRefGoogle Scholar
  51. Schneiders MGE (2001) Wavelets in control engineering (Master’s thesis). Eindhoven University of Technology, EindhovenGoogle Scholar
  52. Sherman SM, Guillery RW (2001) Exploring the thalamus. Academic Press, San DiegoGoogle Scholar
  53. Spehlmann R (1981) EEG primer. Elsevier/North-Holland Biomedical Press, New YorkGoogle Scholar
  54. Steriade M (2000) Corticothalamic resonance, states of vigilance and mentation. J Neurosci 101:243–276CrossRefGoogle Scholar
  55. Steriade M (2000) Brain electrical activity and sensory processing during waking and sleep states. In: Kryger MH, Roth T, Dement DC (eds) Principles and practices of sleep medicine. W. B. Saunders, USAGoogle Scholar
  56. Steriade M, McCarley RW (2005) Brainstem control of wakefulness and sleep. Biomedical and life sciences. Springer, New YorkGoogle Scholar
  57. Steriade M, Nunez A, Amzica F (1993) Intracellular analysis of relations between the slow (\(<\)1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. J Neurosci 13:3266–3283CrossRefPubMedGoogle Scholar
  58. Steriade M, McCormick DA, Sejnowski TJ (1993) Thalamocortical oscillations in the sleeping and aroused brain. Science 262:679–685CrossRefPubMedCentralPubMedGoogle Scholar
  59. Synek VM (1988) Prognostically important EEG coma patterns in diffuse anoxic and traumatic encephalopathies in adults. J Clin Neurophysiol 5:161–174CrossRefPubMedCentralPubMedGoogle Scholar
  60. Ujszaszi J, Halasz P (1988) Long latency evoked potential components in human slow wave sleep. Electroencephalogr Clin Neurophysiol 69:516–522CrossRefPubMedCentralPubMedGoogle Scholar
  61. van Albada SJ, Robinson PA (2009) Mean-field modeling of the basal ganglia-thalamocortical system. I Firing rates in healthy and parkinsonian states. J Theor Biol 25:642–663CrossRefGoogle Scholar
  62. Walsh P, Kane N, Butler S (2005) The clinical role of evoked potentials. J Neurol Neurosurg Psychiatry 76:ii16–ii22CrossRefPubMedCentralPubMedGoogle Scholar
  63. Webster KE, Colrain IM (1998) Multichannel EEG analysis of respiratory evoked-potential components during wakefulness and NREM sleep. J Appl Physiol 85:1727–1735CrossRefPubMedCentralPubMedGoogle Scholar
  64. Weitzman ED, Kremen H (1965) Auditory evoked responses during different stages of sleep in man. Electroencephalogr Clin Neurophysiol 18:65–70CrossRefPubMedCentralPubMedGoogle Scholar
  65. Wilson HR, Cowan JD (1973) A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Kybernetik 13:55–80CrossRefPubMedGoogle Scholar
  66. Wright JJ, Liley DTJ (1994) A millimetric scale simulation of electrocortical wave dynamics based on anatomical estimates of cortical synaptic density. Netw Comput Neural Syst 5:191–202CrossRefGoogle Scholar
  67. Wright JJ, Sergejew AA, Stampfer HG (1990) Inverse filter computation of the neural impulse giving rise to the auditory evoked potential. Brain Topogr 2:293–302CrossRefPubMedCentralPubMedGoogle Scholar
  68. Young GB, McLachlan RS, Kreeft JH, Demelo JD (1997) An electroencephalographic classification for coma. Can J Neurol Sci 24:320–325CrossRefPubMedCentralPubMedGoogle Scholar
  69. Zisapel N (2007) Sleep and sleep disturbances: biological basis and clinical implications. Cell Mol Life Sci 64:1174–1186CrossRefPubMedCentralPubMedGoogle Scholar
  70. Zobaer MS, Anderson RM, Kerr CC, Robinson PA, Wong KKH, D’Rozario AL (2017) K-complexes, spindles, and ERPs as impulse responses: unification via neural field theory. Biol Cybern 111:149–164CrossRefPubMedCentralPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of PhysicsThe University of SydneySydneyAustralia
  2. 2.Center for Integrative Brain FunctionThe University of SydneySydneyAustralia
  3. 3.Center for Research ExcellenceGlebeAustralia
  4. 4.Department of PhysicsBangladesh University of TextilesDhakaBangladesh
  5. 5.Department of Physiology and PharmacologyState University of New York Downstate Medical CenterBrooklynUSA

Personalised recommendations