Critical branching captures activity in living neural networks and maximizes the number of metastable states

Physical Review Letters

Volumn 94, Issue 5, 2005, Pages

  Haldeman, Clayton ^a   Beggs, John M ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY PROCESSING UNITS; CRITICAL BRANCHING; GREEDY ALGORITHMS; METASTABLE STATES;

DATA ACQUISITION; DATA STORAGE EQUIPMENT; ELECTRODES; MATHEMATICAL MODELS; PHASE TRANSITIONS; PROBABILITY;

NEURAL NETWORKS;

ANIMAL; BIOLOGICAL MODEL; BIOLOGICAL RHYTHM; BRAIN; COMPARATIVE STUDY; COMPUTER SIMULATION; EVALUATION STUDY; HUMAN; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY; SYNAPTIC TRANSMISSION; VALIDATION STUDY;

ANIMALS; BIOLOGICAL CLOCKS; BRAIN; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONS; SYNAPTIC TRANSMISSION;

EID: 18144382578     PISSN: 00319007     EISSN: 10797114     Source Type: Journal    
DOI: 10.1103/PhysRevLett.94.058101     Document Type: Article

References (26)

1. C. W. Eurich, J. M. Herrmann, and U. A. Ernst, Phys. Rev. E 66, 066137 (2002).
2. A. V. Herz and J. J. Hopfield, Phys. Rev. Lett. 75, 1222 (1995).
3. P. Bak and D. R. Chialvo, Phys. Rev. E 63, 031912 (2001).
4. S. Bornholdt and T. Rohl, Phys. Rev. E 67, 066118 (2003).
5. J. J. Hopfield, Proc. Natl. Acad. Sci. U.S.A. 79, 2554 (1982).
6. D. J. Amit, Modeling Brain Function: The World of Attractor Neural Networks (Cambridge University Press, Cambridge, England, 1989).
7. J. M. Beggs and D. Plenz, J. Neurosci. 23, 11167 (2003).
8. H. E. Stanley, Introduction to Phase Transitions and Critical Phenomena (Clarendon Press, Oxford, 1971).
9. M. Paczuski, S. Maslov, and P. Bak, Phys. Rev. E 53, 414 (1996).
10. T. E. Harris, The Theory of Branching Processes (Dover Publications, New York, 1989).
11. J. M. Beggs and D. Plenz, J. Neurosci. 24, 5216 (2004).
12. R. Segev, I. Baruchi, E. Hulata et al., Phys. Rev. Lett. 92, 118102 (2004).
13. Y. Ikegaya, G. Aaron, R. Cessait et al., Science 304, 559 (2004).
14. M. Bove, S. Martinoia, G. Verreschi et al., Biosens. Bioelectron. 13, 601 (1998).
15. Y. Jimbo, A. Kawana, P. Parodi et al., Biol. Cybern. 83, 1 (2000).
16. M. W. Oram, M. C. Wiener, R. Lestienne et al., J. Neurophysiol. 81, 3021 (1999).
17. B. Derrida and Y. Pomeau, Europhys. Lett. 1, 45 (1986).
18. B. Derrida and G. Weisbuch, J. Phys. (France) 47, 1297 (1986).
19. A. Wolf, J. B. Swift, H. L. Swinney et al., Physica D (Amsterdam) 16, 285 (1985).
20. I. Tsuda, Neural Networks 5, 313 (1992).
21. M. N. Shadlen and W. T. Newsome, J. Neurosci. 18, 3870 (1998).
22. I. Timofeev, F. Grenier, M. Bazhenov et al., Cereb. Cortex 10, 1185 (2000).
23. I. R. Tsang and I. J. Tsang, Phys. Rev. E 60, 2684 (1999).
24. W. Maass, T. Natschlager, and H. Markram, Neural Comput. 14, 2531 (2002).
25. R. Shaw, Z. Naturfursch, a 36, 80 (1981).
26. N. Bertschinger and T. Natschlager, Neural Comput. 16, 1413 (2004).