Threshold disorder as a source of diverse and complex behavior in random nets

McGuire PC, Bohr H, Clark JW, Haschke R, Pershing CL, Rafelski J (2002)
NEURAL NETWORKS 15(10): 1243-1258.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
McGuire, Patrick C.; Bohr, Henrik; Clark, John W.; Haschke, RobertUniBi ; Pershing, Chris L.; Rafelski, Johann
Abstract / Bemerkung
We study the diversity of complex spatio-temporal patterns in the behavior of random synchronous asymmetric neural networks (RSANNs). Special attention is given to the impact of disordered threshold values on limit-cycle diversity and limit-cycle complexity in RSANNs which have ‘normal’ thresholds by default. Surprisingly, RSANNs exhibit only a small repertoire of rather complex limit-cycle patterns when all parameters are fixed. This repertoire of complex patterns is also rather stable with respect to small parameter changes. These two unexpected results may generalize to the study of other complex systems. In order to reach beyond this seemingly disabling ‘stable and small’ aspect of the limit-cycle repertoire of RSANNs, we have found that if an RSANN has threshold disorder above a critical level, then there is a rapid increase of the size of the repertoire of patterns. The repertoire size initially follows a power-law function of the magnitude of the threshold disorder. As the disorder increases further, the limit-cycle patterns themselves become simpler until at a second critical level most of the limit cycles become simple fixed points. Nonetheless, for moderate changes in the threshold parameters, RSANNs are found to display specific features of behavior desired for rapidly responding processing systems: accessibility to a large set of complex patterns.
Stichworte
limit-cycle attractors; diversity; neurodynamics; random recurrent neural networks; noise or disorder; synchronous updating; complexity; threshold; creativity
Erscheinungsjahr
2002
Zeitschriftentitel
NEURAL NETWORKS
Band
15
Ausgabe
10
Seite(n)
1243-1258
ISSN
0893-6080
Page URI
https://pub.uni-bielefeld.de/record/1613269

Zitieren

McGuire PC, Bohr H, Clark JW, Haschke R, Pershing CL, Rafelski J. Threshold disorder as a source of diverse and complex behavior in random nets. NEURAL NETWORKS. 2002;15(10):1243-1258.
McGuire, P. C., Bohr, H., Clark, J. W., Haschke, R., Pershing, C. L., & Rafelski, J. (2002). Threshold disorder as a source of diverse and complex behavior in random nets. NEURAL NETWORKS, 15(10), 1243-1258. https://doi.org/10.1016/S0893-6080(02)00087-4
McGuire, Patrick C., Bohr, Henrik, Clark, John W., Haschke, Robert, Pershing, Chris L., and Rafelski, Johann. 2002. “Threshold disorder as a source of diverse and complex behavior in random nets”. NEURAL NETWORKS 15 (10): 1243-1258.
McGuire, P. C., Bohr, H., Clark, J. W., Haschke, R., Pershing, C. L., and Rafelski, J. (2002). Threshold disorder as a source of diverse and complex behavior in random nets. NEURAL NETWORKS 15, 1243-1258.
McGuire, P.C., et al., 2002. Threshold disorder as a source of diverse and complex behavior in random nets. NEURAL NETWORKS, 15(10), p 1243-1258.
P.C. McGuire, et al., “Threshold disorder as a source of diverse and complex behavior in random nets”, NEURAL NETWORKS, vol. 15, 2002, pp. 1243-1258.
McGuire, P.C., Bohr, H., Clark, J.W., Haschke, R., Pershing, C.L., Rafelski, J.: Threshold disorder as a source of diverse and complex behavior in random nets. NEURAL NETWORKS. 15, 1243-1258 (2002).
McGuire, Patrick C., Bohr, Henrik, Clark, John W., Haschke, Robert, Pershing, Chris L., and Rafelski, Johann. “Threshold disorder as a source of diverse and complex behavior in random nets”. NEURAL NETWORKS 15.10 (2002): 1243-1258.

2 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Reverberating activity in a neural network with distributed signal transmission delays.
Omi T, Shinomoto S., Phys Rev E Stat Nonlin Soft Matter Phys 76(5 pt 1), 2007
PMID: 18233688
Self-organized critical neural networks.
Bornholdt S, Röhl T., Phys Rev E Stat Nonlin Soft Matter Phys 67(6 pt 2), 2003
PMID: 16241315

41 References

Daten bereitgestellt von Europe PubMed Central.

A method of statistical neurodynamics.
Amari S., Kybernetik 14(4), 1974
PMID: 4850221

AUTHOR UNKNOWN, 0
Attractors in fully asymmetric neural networks
Bastolla, Journal of Physics A: Mathematical and General 30(), 1997
Attraction basins in discretized maps
Bastolla, Journal of Physics A: Mathematical and General 30(), 1997
Random iterative networks.
Bressloff PC, Taylor JG., Phys. Rev., A 41(2), 1990
PMID: 9903194
Influence of noise on the function of a "physiological" neural network.
Buhmann J, Schulten K., Biol Cybern 56(5-6), 1987
PMID: 3620531
Spontaneous action potentials due to channel fluctuations.
Chow CC, White JA., Biophys. J. 71(6), 1996
PMID: 8968572
Statistical mechanics of neural networks
Clark, Physics Reports 158(), 1988
Long-term behavior of neural networks
Clark, 1990
Neural network modelling.
Clark JW., Phys Med Biol 36(10), 1991
PMID: 1745659
Access and stability of cyclic modes in quasirandom networks of threshold neurons obeying a determinisitic synchronous dynamics
Clark, 1988
Brain without mind: Computer simulation of neural networks with modifiable neuronal interactions
Clark, Physics Reports 123(), 1985

AUTHOR UNKNOWN, 0
Taming chaos: Stabilization of aperiodic attractors by noise
Freeman, IEEE Transactions on Circuits and Systems 44(), 1997
Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex.
Gray CM, Singer W., Proc. Natl. Acad. Sci. U.S.A. 86(5), 1989
PMID: 2922407
Biomechanical complexity and the control of movement
Hasan, 1989
Neural networks and physical systems with emergent collective computational abilities.
Hopfield JJ., Proc. Natl. Acad. Sci. U.S.A. 79(8), 1982
PMID: 6953413

Kauffman, 1993
Critical phenomena in model neural networks
Kürten, Physics Letters A 129(), 1988
The existence of persistent states in the brain
Little, Mathematical Biosciences 19(), 1974
Transition to cycling in neural networks
Littlewort, 1988
Reliability of spike timing in neocortical neurons.
Mainen ZF, Sejnowski TJ., Science 268(5216), 1995
PMID: 7770778
Neurotransmitter modulation of the stomatogastric ganglion of decapod crustaceans
Marder, 1985
Brainwashing random asymmetric neural networks
McGuire, Physics Letters A 160(), 1991
Training random asymmetric neural networks towards chaos—a progress report
McGuire, 1992

Murray, 1989
Synchronization of the electrosensitive noisy cells in the paddlefish
Neiman, Physical Review Letters 82(), 1999
Controlling chaos.
Ott E, Grebogi C, Yorke JA., Phys. Rev. Lett. 64(11), 1990
PMID: 10041332
Controlling complexity.
Poon L, Grebogi C., Phys. Rev. Lett. 75(22), 1995
PMID: 10059795
Systems of coupled oscillators as models of central pattern generators
Rand, 1988
Attractors in the fully asymmetric SK-model
Schreckenberg, Zeitschrift für Physik B—Condensed Matter 86(), 1992
Persistent states of neural networks and the random nature of synaptic transmission
Shaw, Mathematical Biosciences 21(), 1974
How brains make chaos in order to make sense of the world
Skarda, Behavioral and Brain Sciences 10(), 1987
An interpretation of the self from the dynamical systems perspective: A constructivist approach
Tani, Journal of Consciousness Studies 5(), 1998
Spontaneous behaviour in neural networks.
Taylor JG., J. Theor. Biol. 36(3), 1972
PMID: 4404143
Model of biological pattern recognition with spatially chaotic dynamics
Yao, Neural Networks 3(), 1990
Impact of synaptic unreliability on the information transmitted by spiking neurons
Zador, Journal of Neurophysiology 79(), 1997
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