Inhibitory Interneurons can Rapidly Phase-Lock Neural Populations

  • William W. Lytton
  • Terrence J. Sejnowski
Part of the Brain Dynamics book series (BD)


The discovery of correlated trains of action potentials in the visual system (Eckhorn et al., 1988; Gray and Singer, 1989; Gray et al., 1989) has been long awaited (Sejnowski, 1986). The well-established existence of rhythms in field potentials recorded from the surface of the brain, or even the skull, would be difficult to explain if the responses of single neurons were not, under some circumstances, entrained to a common firing pattern. More surprising is the observation that neurons that are unlikely to have direct excitatory connections appear to be phase-locked; that is, they fire action potentials within a few milliseconds of each other (Gray et al., 1989). Regardless of the functional significance of these correlations, their existence requires a physical explanation. In a complex, highly nonlinear system of neurons, phase-locking can occur through a variety of mechanisms (Eckhorn et al., 1990; Kammen et al., 1990; Konig and Schillen, 1991a; 1991b; Sporns et al., 1991). One particular mechanism, explored in this chapter, is entrainment and phase-locking through a common, inhibitory interneuron. Inhibition could be effective in entraining pyramidal neurons in local circuits, as we demonstrate here with computer simulations.


Pyramidal Neuron Model Neuron Synaptic Input Inhibitory Interneuron Apical Dendrite 
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  1. Andersen P, Andersson SA (1968) Physiological Basis of the Alpha Rhythm. New York: Appleton-Century-CroftsGoogle Scholar
  2. Andersen, P, Sears. TA (1964) The role of inhibition the the phasing of spontaneous thalamocortical discharge. J physiol (Lond) 173:459–480Google Scholar
  3. Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, Reitboeck HJ (1988): Coherent oscillations: a mechanism of feature linking in the visual cortex. Biol Cybern 60:121–130CrossRefGoogle Scholar
  4. Eckhorn R, Reitboeck HJ, Arndt M, Dicke P (1990): Feature linking via synchronization among distributed assemblies: simulations of results from cat visual cortex. Neur Comput 2:293–307CrossRefGoogle Scholar
  5. Gray CM, Konig P, Engel AK, Singer W (1989): Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338:334–337CrossRefGoogle Scholar
  6. Gray CM, Singer W (1989): Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. PNAS 86:1698–1702CrossRefGoogle Scholar
  7. Kammen D, Koch C, Holmes PJ (1990): Collective oscillations in the visual cortex. In: Neural Information Processing Systems 2, Touretzky DS, ed. San Mateo, CA: Morgan Kaufmann, pp 76–83Google Scholar
  8. Konig P, Schillen TB (1991a): Stlmulus-dependent assembly formation of oscillatory responses: II. Desynchronization. Neur Comput 3:167–177CrossRefGoogle Scholar
  9. Konig P, Schillen TB (1991b): Stimulus-dependent assembly formation of oscillatory responses: I. Synchronization. Neur Comput 3:155–166CrossRefGoogle Scholar
  10. Lytton WW, Sejnowski TJ (1991): Inhibitory interneurons may help synchronize oscillations in cortical pyramidal neurons. J Neurophysiol 66:1059–1079Google Scholar
  11. Perkel DH, Schulman JH, Bullock TH, Moore GP, Segundo JP (1964): Pacemaker neurons: effects of regularly spaced synaptic input. Science 145:61–63CrossRefGoogle Scholar
  12. Sejnowski TJ (1981): Skeleton filters in the brain. In: Parallel Models of Associative Memory, Hinton GE, Anderson JA, eds. Hillsdale, NJ. Lawrence Erlbaum, pp 189—212Google Scholar
  13. Sejnowski TJ (1986): Open questions about computation in cerebral cortex. In: Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 2: Psychological and Biological Models, Rumelhart DE, McClelland JL, eds. Cambridge: MIT Press, pp 372–389Google Scholar
  14. Sporns O, Tononi G, Edelman GM (1991): Modeling perceptual grouping and figureground segregation by means of active reentrant connections. PNAS 88:129–133CrossRefGoogle Scholar
  15. Steriade M, Llinás R (1988): The functional states of the thalamus and the associated neuronal interplay. Physiol Rev 68:649–742Google Scholar
  16. von der Malsburg C (1981): The Correlation Theory of Brain Function: Internal Report 81–2. Goettingen: Abteilung fuer Neurobiologie, MPI fuer Biophysikalische ChemieGoogle Scholar
  17. Wang D, Buhmann J, von der Malsburg C (1990): Pattern segmentation in associative memory. Neur Comput 2:94–106CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • William W. Lytton
  • Terrence J. Sejnowski

There are no affiliations available

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