single-rb.php

JRM Vol.19 No.4 pp. 409-415
doi: 10.20965/jrm.2007.p0409
(2007)

Paper:

Synchrony-Induced Attractor Transition in Cortical Neural Networks Organized by Spike-Timing Dependent Plasticity

Takaaki Aoki* and Toshio Aoyagi*,**

*CREST, Japan Science and Technology Corporation, Kyoto 606-8501, Japan

**Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

Received:
January 11, 2007
Accepted:
March 5, 2007
Published:
August 20, 2007
Keywords:
spike-timing dependent plasticity, neural synchrony, neural network, cortical neuron model
Abstract

Recent studies have shown that synchronous neural activity in the cortex area occurs related to behavior or recognition of animals, which suggests that such neural activity involves in information processing. Functions enabled by synchronous firing, however, are still unknown. Results reporting that a transition between recall states of associative memory is induced by external synchronous spikes in a neural network formed by spike-timing dependent plasticity indicate the possibility of a function of synchronous neural activity as a transition signal, requiring further examination using detailed cortical neuron models (AokiAoyagi). We introduced a mathematical model of pyramidal and fast-spiking cortical neurons based on Hodgkin-Huxley, and confirmed the transition between recall states through synchronous spike inputs in detailed neuron models.

Cite this article as:
Takaaki Aoki and Toshio Aoyagi, “Synchrony-Induced Attractor Transition in Cortical Neural Networks Organized by Spike-Timing Dependent Plasticity,” J. Robot. Mechatron., Vol.19, No.4, pp. 409-415, 2007.
Data files:
References
  1. [1] T. Aoyagi, “Synchrony-induced switching behavior of spike-pattern attractors created by spike-timing dependent plasticity,” Neural Comput., 19(10), 2007 (in press).
  2. [2] T. Aoyagi, T. Takekawa, and T. Fukai, “Gamma rhythmic bursts: coherence control in networks of cortical pyramidal neurons,” Neural Comput., 15, pp. 1035-1061, 2003.
  3. [3] B. B. Averbeck and D. Lee, “Coding and transmission of information by neural ensembles,” Trends in Neurosci., 27, pp. 225-230, 2004.
  4. [4] G. Q. Bi and M. M. Poo, “Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type,” J. Neurosci., 18, pp. 10464-10472, 1998.
  5. [5] C. D. Brody and J. J. Hopfield, “Simple networks for spike-timing-based computation, with application to olfactory processing,” Neuron, 37, pp. 843-852, 2003.
  6. [6] D. Debanne, B. H. Gahwiler, and S. M. Thompson, “Long-term synaptic plasticity between pairs of individual ca3 pyramidal cells in rat hippocampal slice cultures,” J. Physiol., 507, pp. 237-247, 1998.
  7. [7] M. Diesmann, M. O. Gewaltig, and A. Aertsen, “Stable propagation of synchronous spiking in cortical neural networks,” Nature, 402, pp. 529-533, 1999.
  8. [8] A. K. Engel, P. Fries, and W. Singer, “Dynamic predictions: oscillations and synchrony in top-down processing,” Nat. Rev. Neurosci., 2, pp. 704-716, 2001.
  9. [9] G. B. Ermentrout and D. Kleinfeld, “Traveling electrical waves in cortex: insights from phase dynamics and speculation on a computational role,” Neuron, 29, pp. 33-44, 2001.
  10. [10] P. Fries, L. H. Reynolds, A. E. Rorie, and R. Desimone, “Modulation of oscillatory neuronal synchronization by selective visual attention,” Science, 291, pp. 1560-1563, 2001.
  11. [11] C. M. Gray, P. Konig, A. K. Engel, and W. Singer, “Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties,” Nature, 338, pp. 334-337, 1989.
  12. [12] D. O. Hebb, “The organization of behavior : A neuropsychological theory,” Wiley, New York, 1949.
  13. [13] J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Natl. Acad. Sci. USA, 79, pp. 2554-2558, 1982.
  14. [14] D. Lee, “Coherent oscillations in neuronal activity of the supplementary motor area during a visuomotor task,” J. Neurosci., 23, pp. 6798-6809, 2003.
  15. [15] H. Markram, J. Lubke, M. Frotscher, and B. Sakmann, “Regulation of synaptic efficacy by coincidence of postsynaptic aps and epsps,” Science, 275, pp. 213-215, 1997.
  16. [16] H. Mushiake, N. Saito, K. Sakamoto, Y. Itoyama, and J. Tanji, “Activity in the lateral prefrontal cortex reflects multiple steps of future events in action plans,” Neuron, 50(4), pp. 631-641, 2006.
  17. [17] M. Nomura, T. Fukai, and T. Aoyagi, “Synchrony of fast-spiking interneurons interconnected by gabaergic and electrical synapses,” Neural Comput., 15(9), pp. 2179-2198, 2003.
  18. [18] W. H. Press, W. T. Vetterling, S. A. Teukolsky, and B. P. Flannery, “Numerical recipes in c++: the art of scientific computing,” 2002.
  19. [19] A. Riehle, S. Grun, M. Diesmann, and A. Aertsen, “Spike synchronization and rate modulation differentially involved in motor cortical function,” Science, 278, pp. 1950-1953, 1997.
  20. [20] J. Rubin, D. D. Lee, and H. Sompolinsky, “Equilibrium properties of temporally asymmetric hebbian plasticity,” Phys. Rev. Lett., 86, pp. 364-367, 2001.
  21. [21] K. Sakamoto, H.Mushiake, N. Saito, and J. Tanji, “Functional rules of neuronal synchrony and firing rate in the prefrontal cortex,” Technical Report of IEICE, 8, p. 105, 2005.
  22. [22] E. Salinas and T. J. Sejnowski, “Correlated neuronal activity and the flow of neural information,” Nat. Rev. Neurosci., 2, pp. 539-550, 2001.
  23. [23] M. N. Shadlen and J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron, 24, pp. 67-77, 1999.
  24. [24] S. Song, K. D. Miller, and L. F. Abbott, “Competitive hebbian learning through spike-timing-dependent synaptic plasticity,” Nat. Neurosci., 3, pp. 919-926, 2000.
  25. [25] Y. Yoshimura and E. M. Callaway, “Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity,” Nat. Neurosci., 8(11), pp. 1552-1559, 2005.
  26. [26] Y. Yoshimura, J. L. M. Dantzker, and E. M. Callaway, “Excitatory cortical neurons form fine-scale functional networks,” Nature, 433(7028), pp. 868-873, 2005.
  27. [27] L. I. Zhang, H. W. Tao, C. E. Holt, W. A. Harris, and M. Poo, “A critical window for cooperation and competition among developing retinotectal synapses,” Nature, 395, pp. 37-44, 1998.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 05, 2021