Optimal spike-based communication in excitable networks with strong-sparse and weak-dense links

Scientific Reports

Volumn 2, Issue , 2012, Pages

  Teramae, Jun Nosuke ^a,c   Tsubo, Yasuhiro ^a   Fukai, Tomoki ^a,b,c  

^a RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

^b RIKEN   (Japan)

^c JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; HUMAN; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY; SYNAPTIC TRANSMISSION;

ALGORITHMS; ANIMALS; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONS; SYNAPTIC TRANSMISSION;

EID: 84863810976     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep00485     Document Type: Article

References (60)

1. Watts, D. J. & Strogatz, S. H. Collective dynamics of "small-world" networks. Nature 393, 440-442 (1998).
2. Argollo de Menezes, M. & Barabási, A. L. Fluctuations in Network Dynamics. Phys. Rev. Lett. 92, 028701 (2004).
3. Bullmore, E. & Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186-198 (2009).
4. Chialvo, D. R. Emergent complex neural dynamics. Nature Phys. 6, 744-750 (2010).
5. Pajevic, S. & Plenz, D. The organization of strong links in complex networks. Nature Phys. 8, 429-436 (2012).
6. Softky, W. & Koch, C. The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J. Neurosci. 13, 334-350 (1993). (Pubitemid 23028748)
7. Hromádka, T., DeWeese, M. R. & Zador, A. M. Sparse representation of sounds in the unanesthetized auditory cortex. PLoS Biol. 6, e16 (2008).
8. Sakata, S. & Sakata, S. & Harris, K. D. Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron 64, 404-418 (2009).
9. Mizuseki, K., Diba, K., Pastalkova, E. & Buzsáki, G. Hippocampal CA1 pyramidal cells form functionally distinct sublayers. Nat. Neurosci. 14, 1174-1181 (2011).
10. Katz, L. C. & Shatz, C. J. Synaptic Activity and the Construction of Cortical Circuits. Science 274, 1133-1138 (1996). (Pubitemid 26389269)
11. Kenet, T., Bibitchkov, D., Tsodyks, M. V., Grinvald, A. & Arieli, A. Spontaneously emerging cortical representations of visual attributes. Nature 425, 954-956 (2003). (Pubitemid 37376925)
12. Petersen, C. C., Hahn, T. T.G., Metha, M., Grinvald, A. &Sakmann, B. Interaction of sensory responses with spontaneous depolarization in layer 2/3 barrel cortex. Proc. Natl. Acad. Sci. USA 100, 13638-13643 (2003). (Pubitemid 37444792)
13. MacLean, J., Watson, B., Aaron, G. & Yuste, R. Internal dynamics determine the cortical response to thalamic stimulation. Neuron 48, 811-823 (2005). (Pubitemid 41759431)
14. Luczak, A., Bartho, P. & Harris, K. D. Spontaneous events outline the realm of possible sensory responses in neocortical populations. Neuron 63, 413-425 (2009).
15. Berkes, P., Orbán, G., Lengyel, M. & Fiser, J. Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science 331, 83-87 (2011).
16. Beggs, J. M. & Plenz, D. Neuronal avalanches in neocortical circuits. J. Neurosci. 23, 11167-11177 (2003). (Pubitemid 37548953)
17. Petermann, T., Thiagarajan, T. C., Lebedev, M. A., Nicolelis, M. A. L., Chialvo, D. R. & Plenz, D. Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc. Natl. Acad. Sci. USA 106, 15921-15926 (2009).
18. van Vreeswijk, C. & Sompolinsky, H. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274, 1724-1726 (1996). (Pubitemid 26414907)
19. Brunel, N. Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8, 183-208 (2000). (Pubitemid 30219050)
20. Destexhe, A., Rudolph, M. & Paré, D. The high-conductance state of neocortical neurons in vivo. Nat. Rev. Neurosci. 4, 739-751 (2003). (Pubitemid 37280153)
21. Vogels, T. P. & Abbott, L. F. Signal propagation and logic gating in networks of integrate-and-fire neurons. J. Neurosci. 25, 10786-10795 (2005). (Pubitemid 41683145)
22. Kumar, A., Schrader, S., Aertsen, A. & Rotter, S. The high-conductance state of cortical networks. Neural Comput. 20, 1-43 (2008).
23. Izhikevich, E. M., Edelman, G. M. Large-scale model of mammalian thalamocortical systems. Proc. Natl. Acad. Sci. USA 105, 3593-3598 (2008). (Pubitemid 351723597)
24. Renart, A. et al. The asynchronous state in cortical circuits. Science 327, 587-590 (2010).
25. Yoshimura, Y. & Callaway, E. M. Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity. Nat. Neurosci. 8, 1552-1559 (2005). (Pubitemid 41573670)
26. Volman, V. & Perc, M. Fast random rewiring and strong connectivity impair subthreshold signal detection in excitable networks. New J. Phys. 12, 043013 (2010).
27. Sun, X., Lei, J., Perc, M., Kurths, J. & Chen, G. Burst synchronization transitions in a neuronal network of subnetworks. Chaos 21, 016110 (2011).
28. Perin, R., Berger, T. K. &Markram,H. A synaptic organizing principle for cortical neuronal groups. Proc. Natl. Acad. Sci. USA 108, 5419-5424 (2011).
29. Barrat, A., Barthélemy, M., Pastor-Satorras, R. & Vespignani, A. The architecture of complex weighted networks. Proc. Natl. Acad. Sci. USA 101, 3747-3752 (2004). (Pubitemid 38381049)
30. Bianconi, G. Emergence of weight-topology correlations in complex scale-free networks. Europhys. Lett. 71, 1029-1035 (2005). (Pubitemid 41352692)
31. Serrano, M. A., Boguñá, M. & Pastor-Satorras, R. Correlations in weighted networks. Phys. Rev. E, 74, 55101 (2006).
32. Restrepo, J. G., Ott, E. & Hunt, B. R. Weighted percolation on directed networks. Phys. Rev. Lett. 100, 58701 (2008).
33. Song, S., Sjöström, P. J., Reigl, M., Nelson, S. B. & Chklovskii, D. B. Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol. 3, e68 (2005).
34. Lefort, S., Tomm, C., Floyd Sarria, J. C. & Petersen, C. C. H. The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex. Neuron 61, 301-316 (2009).
35. Wiesenfeld, K. &Moss, F. Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs. Nature 373, 33-36 (1995).
36. Collins, J. J., Chow, C. C. & Imhoff, T. T. Stochastic resonance without tuning. Nature 376, 236-238 (1995).
37. Collins, J., Chow, C. C., Capela, A. C. & Imhoff, T. T. Aperiodic stochastic resonance. Phys. Rev. E 54, 5575-5584 (1996). (Pubitemid 126589824)
38. Collins, J. J., Imhoff, T. T. & Grigg, P. Noise-enhanced tactile sensation. Nature 383, 770 (1996).
39. Russell, D. F., Wilkens, L. A.&Moss, F. Use of behavioural stochastic resonance by paddle fish for feeding. Nature 402, 291-294 (1999). (Pubitemid 129516264)
40. Rudolph, M. & Destexhe, A. Do neocortical pyramidal neurons display stochastic resonance? J. Comput. Neurosci. 11, 19-42 (2001). (Pubitemid 32926842)
41. Kitajo, K., Nozaki, D., Ward, L. M. & Yamamoto, Y. Behavioral stochastic resonance within the human brain. Phys. Rev. Lett. 90, 218103 (2003).
42. Wolfart, J., Debay, D., LeMasson, G., Destexhe, A. & Bal, T. Synaptic background activity controls spike transfer from thalamus to cortex. Nat. Neurosci. 8, 1760-1767 (2005). (Pubitemid 41683205)
43. Volman, V. & Levine, H. Activity-dependent stochastic resonance in recurrent neuronal networks. Phys. Rev. E 77, 060903 (2008).
44. Volman, V. & Levine, H. Signal processing in local neuronal circuits based on activity-dependent noise and competition. Chaos 19, 033107 (2009).
45. McDonnell, M. D. &Ward, L. M. The benefits of noise in neural systems: bridging theory and experiment. Nat. Rev. Neurosci. 12, 415-426 (2011).
46. Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64, 267-280 (2009).
47. Roxin, A., Brunel, N., Hansel, D., Mongillo, G. & van Vreeswijk, C. On the distribution of firing rates in networks of cortical neurons. J. Neurosci. 31, 16217-16226 (2011).
48. Shu, Y., Hasenstaub, A. &McCormick, D. Turning on and off recurrent balanced cortical activity. Nature 423, 288-293 (2003). (Pubitemid 40852698)
49. Steriade, M., Timofeev, I. & Grenier, F. Natural waking and sleep states: a view from inside neocortical neurons. J. Neurophysiol. 85, 1969-1985 (2001). (Pubitemid 32440676)
50. Abeles, M., Bergman, H.,Margalit, E. & Vaadia, E. Spatiotemporal firing patterns in the frontal-cortex of behavingmonkeys. J. Neurophysiol. 70, 1629-1638 (1993). (Pubitemid 23326398)
51. Long, M. A., Jin, D. Z. & Fee, M. S. Support for a synaptic chain model of neuronal sequence generation. Nature 468, 394-399 (2010).
52. Hahnloser, R. H., Kozhevnikov, A. A. & Fee, M. S. An ultra-sparse code underlies the generation of neural sequences in a songbird. Nature 419, 65-70 (2002). (Pubitemid 34987870)
53. Koulakov, A., Hromádka, T. & Zador, A. M. Correlated connectivity and the distribution of firing rates in the neocortex. J. Neurosci. 29, 3685-3694 (2009).
54. van Rossum,M. C.W., Bi, G. Q. &Turrigiano, G.G. Stable Hebbian learning from spike timingdependent plasticity. J. Neurosci. 20, 8812-8821 (2000).
55. Gilson,M. & Fukai, T. Stability versus neuronal specialization for STDP: long-tail weight distributions solve the dilemma. PLoS ONE 6, e25339 (2011).
56. de Rugy, A., Loeb, G. E.&Carroll, T. J. Muscle coordination is habitual rather than optimal. J. Neurosci. 32, 7384-7391 (2012).
57. Tuckwell, H. C. Introduction to Theoretical Neurobiology (Cambridge Univ. Press, Cambridge, 1998).
58. Burkitt, A. N. A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biol. Cybern. 95, 1-19 (2006). (Pubitemid 43999784)
59. Fourcaud-Trocme, N. & Brunel, N. Dynamics of the firing probability of noisy integrate-and-fire neurons. Neural Comput. 14, 2057-2110 (2002).
60. Roxin, A., Brunel, N. & Hansel, D. Role of delays in shaping spatiotemporal dynamics of neuronal activity in large networks. Phys. Rev. Lett. 94, 238103 (2005).