Journal of Computational Neuroscience

, Volume 11, Issue 2, pp 121–134 | Cite as

Turning On and Off with Excitation: The Role of Spike-Timing Asynchrony and Synchrony in Sustained Neural Activity

  • Boris S. Gutkin
  • Carlo R. Laing
  • Carol. L. Colby
  • Carson C. Chow
  • G. Bard Ermentrout

Abstract

Delay-related sustained activity in the prefrontal cortex of primates, a neurological analogue of working memory, has been proposed to arise from synaptic interactions in local cortical circuits. The implication is that memories are coded by spatially localized foci of sustained activity. We investigate the mechanisms by which sustained foci are initiated, maintained, and extinguished by excitation in networks of Hodgkin-Huxley neurons coupled with biophysical spatially structured synaptic connections. For networks with a balance between excitation and inhibition, a localized transient stimulus robustly initiates a localized focus of activity. The activity is then maintained by recurrent excitatory AMPA-like synapses. We find that to maintain the focus, the firing must be asynchronous. Consequently, inducing transient synchrony through an excitatory stimulus extinguishes the sustained activity. Such a monosynaptic excitatory turn-off mechanism is compatible with the working memory being wiped clean by an efferent copy of the motor command. The activity that codes working memories may be structured so that the motor command is both the read-out and a direct clearing signal. We show examples of data that is compatible with our theory.

working memory asynchrony synchrony sustained activity prefrontal cortex 

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References

  1. Amit DJ, Brunel N (1997) Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb. Cortex 7:237.Google Scholar
  2. Azouz R, Gray CM (1999) Cellular mechanisms contributing to response variability of cortical neurons in vivo. J. Neurosci. 19(6):209.Google Scholar
  3. Bringuier V, Chavane F, Glaeser L, Fregnac Y (1999) Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science 283(5402):695.Google Scholar
  4. Brody CD (1998) Slow covariations in neuronal resting potentials can lead to artefactually fast cross-correlations in their spike trains. J. Neurophysiol. 80(6):3345.Google Scholar
  5. Brody CD (1999) Correlations without synchrony neural computation. Soc. Neurosci. Abstract. 11(7):15371.Google Scholar
  6. Bush P, Sejnowski T (1996) Inhibition synchronizes sparsely connected cortical neurons within and between columns in realistic network models. J. Comput. Neurosci. 3(2):91.Google Scholar
  7. Camperi M, Wang XJ (1999) A model of visuospatial working memory in prefrontal cortex: Recurrent network and cellular bistability. J. Comput. Neurosci. 5:383.Google Scholar
  8. Colby CL, Duhamel JR (1991) Heterogeneity of extrastriate visual areas and multiple parietal areas in the macaque monkey. Neuropsychologia 29:517.Google Scholar
  9. Colby CL, Duhamel JR (1996) Spatial representations for action in parietal cortex. Cog. Brain Res. 5:105.Google Scholar
  10. Compte A, Brunel N, Goldman-Rakic PS, Wang XJ (2000) Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. Cereb Cortex 10(9): 910.Google Scholar
  11. Debanne D, Shulz DE, Fregnac Y (1998) Activity-dependent regulation of “on” and “off ” responses in cat visual cortical receptive fields. J. Physiol: (London) 508:523.Google Scholar
  12. Diesmann M, Gewaltig MO, Aertsen A (1999) Stable propagation of synchronous spiking in cortical neural networks. Nature 402:529.Google Scholar
  13. Dilmore J, Gutkin BS, Ermentrout GB (1999) Dopaminergic modulation of persistent sodium current affects excitability of prefrontal cortical neurons: A computational study. Neurocomputing 26/27:107.Google Scholar
  14. Engel AK, Koenig P, Kreiter AK, Singer (1991) Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252:1177.Google Scholar
  15. Ermentrout GB (1996) Type I membranes, phase resetting curves, and synchrony. Neural Comp. 8:979.Google Scholar
  16. Ermentrout GB, Kopell N (1998) Fine structure of neural spiking and synchronization in the presence of conduction delays. Proc. Natl. Acad. Sci. USA 95(3):1259.Google Scholar
  17. Floresco SB, Seamans JK, Phillips AG (1997) Selective roles for hippocampal, prefrontal cortical, and ventral striatal circuits in radial-arm maze tasks with or without a delay. J. Neurosci. 17:1880.Google Scholar
  18. Friedman H, Goldman-Rakic PS (1988) Activation of the hippocampus and dentate gyrus by working-memory: A 2-dg study in behaving rhesus monkeys. J. Neurosci. 8:4693.Google Scholar
  19. Funahashi S (1998) Soc. Neurosci. Abstract.Google Scholar
  20. Funahashi S, Bruce CJ, Goldman-Rakic PS, (1989) Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. J. Neurophys. 61:331.Google Scholar
  21. Funahashi S, Bruce CJ, Goldman-Rakic PS (1990) Visuospatial coding in primate prefrontal neurons revealed by oculomotor paradigms. J. Neurophys. 63:814.Google Scholar
  22. Funahashi S, Chafee MV, Goldman-Rakic PS (1993) Prefrontal neuron activity in rhesus monkeys performing a delayed anti-saccade task. Nature 365:753.Google Scholar
  23. Funahashi S, Inoue M (2000) Neuronal interactions related to working memory processes in the primate prefrontal cortex revealed by cross-correlation analysis. Cerebral Cortex 10:535.Google Scholar
  24. Fuster JM (1989) The prefornal cortex: Anatomy, physiology, and neuropsychology of the frontal lobe. Raven Press, New York.Google Scholar
  25. Fuster, J (1995) Temporal processing. In: Grafman J, ed. Structure and function of the human prefrontal cortex. New York Academy of Science, New York.Google Scholar
  26. Gnadt JW, Andersen RA (1988) Memory-related motor planning activity in posterior parietal cortex of macaque. Expt. Brain Res. 70:216.Google Scholar
  27. Goldman-Rakic PS (1995) Cellular basis of working memory. Neuron 14:477.Google Scholar
  28. Gray CM, Koenig P, Engel AK, Singer W (1989) Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338334.Google Scholar
  29. Guigon E, Dorrizzi B, Burnod Y, Schultz W (1995) Neural correlates of learning in the prefrontal cortex: A predictive model. Cereb. Cortex 5:135.Google Scholar
  30. Gutkin BS, Ermentrout GB (1998) Dynamics of membrane excitability determine interspike interval variability: A link between spike generation mechanisms and cortical spike train statistics. Neural Comp. 10(5):1285.Google Scholar
  31. Hansel D, Mato G, Meunier C (1995) Synchrony in excitatory neural networks. Neural Comp. 7:307.Google Scholar
  32. Hebb DO (1949) The organization of behavior. Wiley, New York.Google Scholar
  33. Hirsch JA, Alonso JM, Reid RC, Martinez LM (1998) Synaptic integration in striate cortical simple cells. J. Neurosci. 18(22):9517.Google Scholar
  34. Laing CR, Chow CC (2001) Stationary bumps in networks of spiking neurons. Neural Comp. 13(7):1473.Google Scholar
  35. Levitt JB, Lewis DA, Yoshioka T, Lund JS (1993) Topography of pyramidal neuron intrinsic connections in macaque prefrontal cortex (area 9 and 46). J. Comp. Neurol. 338:360.Google Scholar
  36. Lisman JE, Fellous JM, Wang XJ (1998) A role of NMDA-receptor channels in working memory. Nature Neurosci. 1:273.Google Scholar
  37. Lund JS, Lewis DA (1993) Local circuit neurons of developing and mature macaque prefrontal cortex: Golgi and immunocytochemical characteristics. J. Comp. Neurol. 328(2):282.Google Scholar
  38. Markram H, Tsodyks M (1996) Redistribution of synaptic efficacy between neocortical pyramidal neurons. Nature 382:759.Google Scholar
  39. Melchitzky DS, Sesack SR, Lewis DA (1998) Parvalbum-inimmunoreactive axon terminals in macaque monkey and human prefrontal cortex: Laminar, regional, and target specificity of type I and type II synapses. J. Comp. Neurol. 211:390.Google Scholar
  40. Miller EK, Desimone R (1994) Parallel neuronal mechanisms for short-term memory task. Science 263:520.Google Scholar
  41. Pucak ML, Levitt JB, Lund JS, Lewis DA (1996) Patterns of intrinsic and associational circuitry in monkey prefrontal cortex. J. Comp. Neurol. 376(4):614.Google Scholar
  42. Rao SG, Williams G, Goldman-Rakic PS (1999) Isodirectional tuning of adjacent interneurons and pyramidal cells during working memory: Evidence for microcolumnar organization in PFC J. Neurophysiol. 81:1903.Google Scholar
  43. Riehle A, Grun S, Diesmann M, Aertsen A (1998) Spike synchronisation and rate modification are differentially involved in motor cortical function. Science 278:1950.Google Scholar
  44. Romo R, Brody CD, Hernandez A, Lemus L (1999) Neuronal correlates of parametric working memory in the prefrontal cortex. Nature 399:470.Google Scholar
  45. Rosenkilde CE, Bauer RH, Fuster JM (1981) Single cell activity in ventral prefrontal cortex of behaving monkeys. Brain. Res. 209:375.Google Scholar
  46. Singer W (1999) Neuronal synchrony: A versatile code for the definition of relations? Neuron 24:48.Google Scholar
  47. Zipser D, Kehoe B, Littlewort G, Fuster J (1993) A spiking model of short-term active memory J. Neurosci. 13:3406.Google Scholar
  48. Wang XJ (1999) Synaptic basis of cortical persistent activity: The importance ofNMDA receptors to working memory J. Neuroscience 19(21):9587.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Boris S. Gutkin
    • 1
  • Carlo R. Laing
    • 2
  • Carol. L. Colby
    • 3
    • 4
  • Carson C. Chow
    • 5
    • 4
  • G. Bard Ermentrout
    • 5
    • 4
  1. 1.Unite de Neurosciences Intergratives et Computationelles, CNRSGif-sur-YvetteFrance
  2. 2.Department of PhysicsUniversity of OttawaOttawa
  3. 3.Department of NeuroscienceUniversity of PittsburghPittsburgh
  4. 4.Center for Neural Basis of CognitionUniversity of Pittsburgh and Carnegie Mellon UniversityPittsburgh
  5. 5.Department of MathematicsUniversity of PittsburghPittsburgh

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