Skip to main content
Log in

A neurophysiologically-based mathematical model of flash visual evoked potentials

  • Published:
Biological Cybernetics Aims and scope Submit manuscript

Abstract

Evidence is presented that a neurophysiologically-inspired mathematical model, originally developed for the generation of spontaneous EEG (electroencephalogram) activity, can produce VEP (visual evoked potential)-like waveforms when pulse-like signals serve as input. It was found that the simulated VEP activity was mainly due to intracortical excitatory connections rather than direct thalamic input. Also, the model-generated VEPs exhibited similar relationships between prestimulus EEG characteristics and subsequent VEP morphology, as seen in human data. Specifically, the large correlation between the N1 amplitude and the prestimulus alpha phase angle, and the insensitivity of P2 to the latter feature, as observed in actual VEPs to low intensity flashes, was also found in the model-generated data. These findings provide support for the hypothesis that the spontaneous EEG and the VEP are generated by some of the same neural structures and that the VEP is due to distributed activity, rather than dipolar sources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Andersen P, Sears TA (1964) The role of inhibition in the phasing of spontaneous thalamo-cortical discharges. J Physiol 173:459–480

    Google Scholar 

  • Andersson SA, Holmgren E, Manson JR (1971) Localized thalamic rhythmicity induced by spinal and cortical lesions. Electroencephal Clin Neurophysiol 31:347–356

    Google Scholar 

  • Babloyantz A, Salazar JM, Nicolis C (1985) Evidence of chaotic dynamics of brain activity during the sleep cycle. Phys Lett 111A. 152–156

    Google Scholar 

  • Barrett G (1986) Analytic techniques in the estimation of evoked potentials. In: Lopes da Silva LH, Storm van Leeuwen W, Rémond A (eds) Clinical applications of computer analysis of EEG and other neurophysiological signals. Elsevier Scientific Publishers, Amsterdam, pp 311–333

    Google Scholar 

  • Brandt ME (1989) The relationship between prestimulus EEG and visual evoked potentials. Ph. D.-dissertation, Biomedical Engineering Program, University of Houston, Houston

    Google Scholar 

  • Brazier MAB (1958) Studies of evoked responses by flash in man and cat. In: Reticular formation of the brain. Little Brown & Co. Boston, pp 151–176

    Google Scholar 

  • Brazier MAB (1964) Evoked responses recorded from the depths of the human brain. Ann NY Acad Sci 112:33–59

    Google Scholar 

  • Cotterill RMJ (eds) (1988) Computer simulation in brain science. Cambridge University Press, Cambridge

    Google Scholar 

  • Curtis DR, Eccles JC (1957) The time course of excitatory and inhibitory synaptic action. J Physiol 145:522

    Google Scholar 

  • Douglas RJ, Martin KAC, Whitteridge D (1989) A canonical microcircuit for neocortex. Neural Computat 1:480–488

    Google Scholar 

  • Ducati A, Fava E, Motti EDF (1988) Neuronal generators of the visual evoked potentials: intracerebral recordings in awake humans. Electroencephal Clin Neurophysiol 71:89–99

    Google Scholar 

  • Fester D, Lindström S (1984) Neuronal circuitry of the cat visual cortex. In: Edelman GM, Gall WE, Cowan WM (eds) Dynamic aspects of neocortical function. John Wiley, New York, pp87–103

    Google Scholar 

  • Freeman WJ (1975) Mass action in the nervous system. Academic Press, New York

    Google Scholar 

  • Freeman WJ (1987a) Analytic techniques in the search for the physiological basis of the EEG. In: Gevins AS, Rémond A (eds) Methods of analysis of brain electrical and magnetic signals. EEG Handbook, vol 1. Elsevier, Amsterdam

    Google Scholar 

  • Freeman WJ (1987b) Simulation of chaotic EEG patterns with a dynamical model of the olfactory system. Biol Cybern 56:139–150

    Google Scholar 

  • Glass L, Mackey MC (1988) From clocks to chaos, the rhythms of life. Princeton University Press, Princeton

    Google Scholar 

  • Goff WR, Allison T, Vaughan Jr HG (1978) The functional neuroanatomy of the event-related potentials. In: Callaway E, Tueting P, Koslow SH (eds) Event-related brain potentials in man. Academic Press, New York, pp 1–79

    Google Scholar 

  • Jansen BH, Brandt ME (1991) The effect of the phase of prestimulus alpha activity on the averaged visual evoked response. Electroencephal Clin Neurophysiol 80:241–250

    Google Scholar 

  • Kandel ER, Schwartz JH (1985) Principles of neural science. Elsevier, Amsterdam

    Google Scholar 

  • Katznelson RD (1981) Normal modes of the brain: neuroanatomical basis and a physiological theoretical model. In: Nunez P (eds) Electric fields of the brain: the neurophysics of EEG. Oxford University Press, New York, pp 401–442

    Google Scholar 

  • Kelly DH (1961) Visual response to time-dependent stimuli. II. Single-channel model of the photopic visual system. J Opt Soc Am 51: 747–754

    Google Scholar 

  • Koch C, Segev I (eds) (1989) Methods in neuronal modeling: from synapses to networks. MIT Press, Cambridge

    Google Scholar 

  • Lopes da Silva FH, Hoeks A, Zetterberg LH (1974) Model of brain rhythmic activity. Kybernetik 15: 27–37

    Google Scholar 

  • Lopes da Silva FH Rotterdam A van, Barts P, Heusden E van, Burr W (1976) Model of neuronal populations. The basic mechanism of rhythmicity. In: Corner MA, Swaab DF (eds) Progress in brain research, vol 45. Elsevier, Amsterdam, pp 281–308

    Google Scholar 

  • Lopes da Silva FH, Storm van Leeuwen W (1977) The cortical sources of the alpha rhythm. Neurosci Lett 6:237–241

    Google Scholar 

  • MacGregor RJ (1987) Neural and brain modeling. Academic Press, New York

    Google Scholar 

  • Mast J, Victor JD (1991) Fluctuations of steady-state VEPs: Interaction of driven evoked potentials and the EEG. Electroencephal Clin Neurophysiol 78:389–401

    Google Scholar 

  • Mountcastle VB (1957) Modality and topographic properties of single neurons of cat's somatic sensory cortex. J Neurophysiol 20: 408–434

    Google Scholar 

  • Nunez PL (1981) Electric fields of the brain: the neurophysics of EEG. Oxford University Press, New York

    Google Scholar 

  • Pineda JA, Holmes TC, Foote SL (1991) Intensity-amplitude relationships in monkey event-related potentials: parallels to human augmenting-reducing responses. Electroencephal Clin Neurophysiol 78:456–465

    Google Scholar 

  • Rapp PE, Zimmerman ID, Albano AM, deGuzman GC, Greenbaum NN, Bashore TR (1985) Experimental studies of chaotic neural behavior: cellular activity and electroencephalographic signals. In: Othmer HG (eds) Nonlinear oscillations in biology and chemistry. Springer, Berlin Heidelberg New York, pp 175–205

    Google Scholar 

  • Rogers RL, Papanicolaou AC, Baumann SD, Sydjarï C, Eisenberg HM (1990) Neuromagnetic evidence of a dynamic excitation pattern generating the N100 auditory response. Electroencephal Clin Neurophysiol 77:237–240

    Google Scholar 

  • Rogers RL, Baumann SD, Papanicolaou AC, Bourbon TW, Alagarsamy S, Eisenberg HM (1991) Localization of the P3 sources using magnetoencephalography and magnetic resonance imaging. Electroencephal Clin Neurophysiol 79:308–321

    Google Scholar 

  • Rotterdam A van, Lopes da Silva FH, van den Ende J, Viergever A, Hermans AJ (1982) A model of the spatial-temporal characteristics of the alpha rhythm. Bull Math Biol 44:283–305

    Google Scholar 

  • Skarda A, Freeman WJ (1987) How brains make chaos in order to make sense of the world. Behav Brain Sci 10:161–195

    Google Scholar 

  • Steriade M, Llinás R (1988) The functional states of the thalamus and the associated neuronal underplay. Physiol Rev 68: 649–742

    Google Scholar 

  • Szentángothai J (1978) The local neuronal apparatus of the cerebral cortex. In: Cerebral correlates of conscious experience. Elsevier/North Holland Biomedical Press, Amsterdam, pp 131–138

    Google Scholar 

  • Traub RD, Miles R, Wong RKS (1988) Large scale simulations of the hippocampus. IEEE Eng Med Biol 7:31–38

    Google Scholar 

  • Toyama K, Matsunami K, Ohno T, Tokashiki S (1974) An intracellular study of neuronal organization in visual cortex. Exp Brain Res 21:45–66

    Google Scholar 

  • Watson AB, Nachmias J (1977) Patterns of temporal integration in the detection of grating. Vision Res 17:893–902

    Google Scholar 

  • Wilson HR, Cowan JD (1972) Excitatory and inhibitory interaction in localized populations of model neurons. Biophys J 12:1–24

    Google Scholar 

  • Wilson CL, Babb TL, Halgren E, Crandall PH (1983) Visual receptive fields and response properties of neurons in human temporal lobe and visual pathways. Brain 106:473–502

    Google Scholar 

  • Winfree AT (1987) When time breaks down. Princeton University Press, Princeton

    Google Scholar 

  • Zetterberg LH, Kristiansson L, Mossberg K (1978) Performance of a model for a local neuron population. Biol Cybern 31:15–26

    Google Scholar 

  • Zouridakis G (1990) Nonlinear modeling of EEG and VEP activity. M. Sc.-Thesis, Biomedical Engineering Program, University of Houston, Houston

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jansen, B.H., Zouridakis, G. & Brandt, M.E. A neurophysiologically-based mathematical model of flash visual evoked potentials. Biol. Cybern. 68, 275–283 (1993). https://doi.org/10.1007/BF00224863

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00224863

Keywords

Navigation