Compound Potentials of the Brain, Ongoing and Evoked: Perspectives from Comparative Neurology

  • T. H. Bullock
Part of the Springer Series in Brain Dynamics book series (SSBD, volume 1)


From the point of view of general biology, it is not surprising that one can record a compound fluctuating field potential from the brain. Our expectations come from several directions:
  1. 1.

    Fluctuating membrane potentials and various kinds of episodic potentials of action or oscillation are of general occurrence among nerve cells as well as other kinds of cells, for example, the cells of the blastula (Burr and Bullock 1941), the skin, gland, gut, muscle, and blood vessels.

  2. 2.

    At least six different kinds of active potentials are known in neurons and parts of neurons, including synaptic potentials with various properties, hyperpolarizations with long duration and decreased conductance, plateau potentials, pacemaker potentials, spikes, and negative and positive afterpotentials. The power spectrum of all these processes extends from dc to several kHz.

  3. 3.

    Lamination or other geometric biases can be expected to influence the summing of these cellular sources in special situations.

  4. 4.

    The null hypothesis of the independence of generators predicts a certain level of coincidence, depending on the duration of the cellular event and the definition of simultaneity.

  5. 5.

    Therefore large numbers of generators, small and large, are operative, in all orientations, some rhythmically but many episodically and generating broad-band signals, mostly spreading decrementally. The composite will therefore have a lot of spatial microstructure and less and less structure at macro levels. What cannot be predicted is the amplitude, frequency, and spatial and temporal structure.



Power Spectrum Optic Tectum Compound Potential Humpback Whale Current Source Density 
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  1. Adrian ED, Matthews BHC (1934) The interpretation of potential waves in the cortex. J Physiol (Lond) 81: 440–471Google Scholar
  2. Allison T (1972) Comparative and evolutionary aspects of sleep. In: Chase MH (ed) The sleeping brain. Brain Information Service, Brain Research Institute, UCLA, Los Angeles, pp 1–57Google Scholar
  3. Basar E (1980) EEG-brain dynamics, relation between EEG and brain evoked potentials. Elsevier, AmsterdamGoogle Scholar
  4. Bullock TH (1945) Problems in the comparative study of brain waves. Yale J Biol Med 17: 657–679PubMedGoogle Scholar
  5. Bullock TH (1980) Reassessment of neural connectivity and its specification. In: Pinksker HM, Willis WD (eds) Information processing in the nervous system. Raven, New York, pp 199–220Google Scholar
  6. Bullock TH (1983) Electrical signs of activity in assemblies of neurons: compound field potentials as objects of study in their own right. Acta Morphol Hung 31: 39–62PubMedGoogle Scholar
  7. Bullock TH (1984) Ongoing compound field potentials from octopus brain are labile and vertebrate-like. Electroencephalogr Clin Neurophysiol 57: 473–483PubMedCrossRefGoogle Scholar
  8. Bullock TH, Lange GD, McClune MC (1983) Spatial structure of cortical EEG: synchrony of small populations can be measured by coherence as function of distance. Neurosci Abstr 9: 11–94Google Scholar
  9. Bullock TH, Lange GD, McClune MC (1984) A measure of synchrony in the cortical EEG: the slow wave drowsy state is slightly more synchronized horizontally than the low voltage fast state. Neurosci Abstr 10: 11–43Google Scholar
  10. Burr HS, Bullock TH (1941) Steady state potential differences in the early development of Amblystoma. Yale J Biol Med 14: 51–57PubMedGoogle Scholar
  11. Creutzfeldt O, Houchin J (1974) Neuronal basis of EEG waves. In: Remond A (ed) Handbook of electroencephalography and clinical neurophysiology, vol 2, part C. Elsevier, Amsterdam, pp 555Google Scholar
  12. Danilova NN (1975) Neuronal mechanisms of synchronization and desynchronization of electrical activity of the brain. In: Sokolov EN, Vinogradova OS (eds) Neuronal mechanisms of the orienting reflex. Erlbaum, Hillsdale; Wiley, New York, pp 178–199Google Scholar
  13. Enger PS (1957) The electroencephalogram of the codfish. Acta Physiol Scand 39: 55–72PubMedCrossRefGoogle Scholar
  14. Hobson JA (1967) Respiration and EEG synchronisation in the frog. Nature 213: 988–989CrossRefGoogle Scholar
  15. Klemm WR (1969) Animal electroencephalography. Academic, New YorkGoogle Scholar
  16. Kruger J, Bach M (1981) Simultaneous recording with 30 microelectrodes in monkey visual cortex. Exp Brain Res 41: 191–194PubMedCrossRefGoogle Scholar
  17. Kuperstein M, Eichenbaum H (1985) Unit activity, evoked potentials and slow waves in the rat hippocampus and olfactory bulb recorded with a 24-channel microelectrode. Neuroscience 15: 703–712PubMedCrossRefGoogle Scholar
  18. Laming PR (1980) Electroencephalographic studies on arousal in the goldfish (Carassius auratus). J Comp Physiol Psychol 94: 238–254PubMedCrossRefGoogle Scholar
  19. Laming PR (1981) The physiological basis of alert behaviour in fish. In: Laming PR (ed) Brain mechanisms of behaviour in lower vertebrates. Cambridge University Press, Cambridge, pp 203–224Google Scholar
  20. Laming PR (1982) Electroencephalographic correlates of behavior in the anurans, Bufo regularis and Rana temporaria. Behav Neural Biol 34: 296–306PubMedCrossRefGoogle Scholar
  21. Laming PR (1983) Relationships between the responses of visual units, EEGs and slow potential shifts in the optic tectum of the toad. In: Ewert J-P, Capranica RR, Ingle DJ (eds) Advances in vertebrate neuroethology. Plenum, New York, pp 595–602 (NATO ASI Series A: Life sciences, vol 56 )Google Scholar
  22. Laming PR, Savage GE (1981) Seasonal differences in brain activity and responsiveness shown by the goldfish (Carassius auratus). Behav Neural Biol 32: 386–389PubMedCrossRefGoogle Scholar
  23. Lopes da Silva F, van Rotterdam A (1982) Biophysical aspects of EEG and MEG generation. In: Niedermeyer E, Lopes da Silva F (eds) Electroencephalography: basic principles, clinical applications and related fields. Urban and Schwarzenberg, Baltimore, pp 15–26Google Scholar
  24. McDonald M (1964) A system for stabilizing evoked potentials obtained in the brain stem of the cat. Med Electron Biol Eng 2: 417–423PubMedCrossRefGoogle Scholar
  25. Mitzdorf U (1985) Visually and electrically evoked field potentials and current source densities in the cat visual cortex. In: Morocutti C, Rizzo PA (eds) Evoked potentials. Neurophysiological and clinical aspects. Elsevier, Amsterdam, pp 273–279Google Scholar
  26. Payne RS, McVay S (1971) Songs of humpback whales. Science 173: 587–597CrossRefGoogle Scholar
  27. Petsche H, Pockberger H, Rappelsberger P (1984) On the search for the sources of the electroencephalogram. Neuroscience 11: 1–27PubMedCrossRefGoogle Scholar
  28. Pickard RS (1979) Printed circuit microelectrodes. Trends Neurosci 2: 259–261CrossRefGoogle Scholar
  29. Praetorius HM, Bodenstein G, Creutzfeldt OD (1977) Adaptive segmentation of EEG records: a new approach to automatic EEG analysis. Electroencephalogr Clin Neurophysiol 42: 84–94PubMedCrossRefGoogle Scholar
  30. Prohaska O, Pacha F, Pfundner P, Petsche H (1979) A 16-fold semi-microelectrode for intracortical recordings of field potentials. Electroencephalogr Clin Neurophysiol 47: 629–631PubMedCrossRefGoogle Scholar
  31. Schadé JP, Weiler PJ (1959) EEG patterns in goldfish. J Exp Biol 36: 435–452Google Scholar
  32. Segura ET, de Juan A (1966) Electroencephalographic studies in toads. Electroencephalogr Clin Neurophysiol 21: 373–380CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 1988

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  • T. H. Bullock

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