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Volumn 9, Issue 1, 2014, Pages

Nonlinear dynamics analysis of a self-organizing recurrent neural network: Chaos waning

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONNECTOME; DEFERRED CHAOS; MACHINE LEARNING; NERVE CELL PLASTICITY; NERVE CELL STIMULATION; NONLINEAR SYSTEM; SELF ORGANIZING RECURRENT NEURAL NETWORK; SIMULATION; SYNAPTIC TRANSMISSION;

EID: 84899849785     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0086962     Document Type: Article
Times cited : (10)

References (26)
  • 2
    • 84873511304 scopus 로고    scopus 로고
    • Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
    • Zheng P, Dimitrakakis C, Triesch J (2013) Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex. PLoS Computational Biology 9: e1002848.
    • (2013) PLoS Computational Biology , vol.9
    • Zheng, P.1    Dimitrakakis, C.2    Triesch, J.3
  • 7
    • 36649020961 scopus 로고    scopus 로고
    • Effects of Hebbian learning on the dynamics and structure of random networks with inhibitory and excitatory neurons
    • DOI 10.1016/j.jphysparis.2007.10.003, PII S0928425707000356, Neuro-Computation: From Sensorimotor Integration to Computational Frameworks
    • Siri B, Quoy M, Delord B, Cessac B, Berry H (2007) Effects of Hebbian learning on the dynamics and structure of random networks with inhibitory and excitatory neurons. Journal of Physiology - Paris 101: 136-148. (Pubitemid 350198849)
    • (2007) Journal of Physiology Paris , vol.101 , Issue.1-3 , pp. 136-148
    • Siri, B.1    Quoy, M.2    Delord, B.3    Cessac, B.4    Berry, H.5
  • 8
    • 0043192817 scopus 로고    scopus 로고
    • Complex dynamics and the structure of small neural networks
    • Pasemann F (2002) Complex dynamics and the structure of small neural networks. Network: Computational Neural Systems 13: 195-216.
    • (2002) Network: Computational Neural Systems , vol.13 , pp. 195-216
    • Pasemann, F.1
  • 10
    • 0032053304 scopus 로고    scopus 로고
    • Self-organization and dynamics reduction in recurrent networks: Stimulus presentation and learning
    • DOI 10.1016/S0893-6080(97)00131-7, PII S0893608097001317
    • Dauce E, Quoy M, Cessac B, Doyon B, Samuelides M (1998) Self-organization and dynamics reduction in recurrent networks: stimulus presentation and learning. Neural Networks 11: 521-533. (Pubitemid 28351087)
    • (1998) Neural Networks , vol.11 , Issue.3 , pp. 521-533
    • Dauce, E.1    Quoy, M.2    Cessac, B.3    Doyon, B.4    Samuelides, M.5
  • 11
    • 0031166854 scopus 로고    scopus 로고
    • Chaos and asymptotical stability in discrete-time neural networks
    • PII S0167278996003028
    • Chen L, Aihara K (1997) Chaos and asymptotical stability in discrete-time neural networks. Physica D 104: 286-325. (Pubitemid 127701453)
    • (1997) Physica D: Nonlinear Phenomena , vol.104 , Issue.3-4 , pp. 286-325
    • Chen, L.1    Aihara, K.2
  • 12
    • 0001961264 scopus 로고
    • Mean-field equations, bifurcation map and route to chaos in discrete time neural networks
    • Cessac B, Doyon B, Quoy M, Samuelides M (1994) Mean-field equations, bifurcation map and route to chaos in discrete time neural networks. Physica D 74: 24-44.
    • (1994) Physica D , vol.74 , pp. 24-44
    • Cessac, B.1    Doyon, B.2    Quoy, M.3    Samuelides, M.4
  • 14
    • 46449083010 scopus 로고    scopus 로고
    • Chaotic dynamics on large networks
    • Sprott JC (2008) Chaotic dynamics on large networks. Chaos 18: 023135.
    • (2008) Chaos , vol.18 , pp. 023135
    • Sprott, J.C.1
  • 16
    • 77954485043 scopus 로고    scopus 로고
    • Stimulus-dependent suppression of chaos in recurrent neural networks
    • Rajan K, Abbott LF, Sompolinsky H (2010) Stimulus-dependent suppression of chaos in recurrent neural networks. Physical Review E 82: 011903.
    • (2010) Physical Review e , vol.82 , pp. 011903
    • Rajan, K.1    Abbott, L.F.2    Sompolinsky, H.3
  • 17
    • 41849095656 scopus 로고    scopus 로고
    • Simple models of complex chaotic systems
    • Sprott JC (2008) Simple models of complex chaotic systems. American Journal of Physics 76: 474-480.
    • (2008) American Journal of Physics , vol.76 , pp. 474-480
    • Sprott, J.C.1
  • 18
    • 84871566364 scopus 로고    scopus 로고
    • The Functional Benefits of Criticality in the Cortex
    • Shew WL, Plenz D (2013) The Functional Benefits of Criticality in the Cortex. The Neuroscientist 19: 88-100.
    • (2013) The Neuroscientist , vol.19 , pp. 88-100
    • Shew, W.L.1    Plenz, D.2
  • 19
    • 2942552269 scopus 로고    scopus 로고
    • Real-time computation at the edge of chaos in recurrent neural networks
    • DOI 10.1162/089976604323057443
    • Bertschinger N, Natschläger T (2004) Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks. Neural Computation 16: 1413-1436. (Pubitemid 38740016)
    • (2004) Neural Computation , vol.16 , Issue.7 , pp. 1413-1436
    • Bertschinger, N.1    Natschlager, T.2
  • 20
    • 33846543881 scopus 로고    scopus 로고
    • Edge of chaos and prediction of computational performance for neural circuit models
    • DOI 10.1016/j.neunet.2007.04.017, PII S0893608007000433, Echo State Networks and Liquid State Machines
    • Legenstein R, Maass W (2007) Edge of chaos and prediction of computational performance for neural circuit models. Neural Networks 20: 323-334. (Pubitemid 46856111)
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 323-334
    • Legenstein, R.1    Maass, W.2
  • 21
    • 78649366197 scopus 로고    scopus 로고
    • Theory of hybrid dynamical systems and its applications to biological and medical systems
    • Aihara K, Suzuki H (2010) Theory of hybrid dynamical systems and its applications to biological and medical systems. Philosophical Transactions of the Royal Society A 368: 4893-4914.
    • (2010) Philosophical Transactions of the Royal Society A , vol.368 , pp. 4893-4914
    • Aihara, K.1    Suzuki, H.2
  • 22
    • 63649085510 scopus 로고    scopus 로고
    • Gating multiple signals through detailed balance of excitation and inhibition in spiking networks
    • Vogels TP, Abbott LF (2009) Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. Nature Neuroscience 12: 483-491.
    • (2009) Nature Neuroscience , vol.12 , pp. 483-491
    • Vogels, T.P.1    Abbott, L.F.2
  • 25
    • 84876007722 scopus 로고    scopus 로고
    • Neuronal Avalanches Differ from Wakefulness to Deep Sleep-Evidence from Intracranial Depth Recordings in Humans
    • Priesemann V, Valderrama M, Wibral M, Le Van Quyen M (2013) Neuronal Avalanches Differ from Wakefulness to Deep Sleep-Evidence from Intracranial Depth Recordings in Humans. PLoS Computational Biology 9: e1002985.
    • (2013) PLoS Computational Biology , vol.9
    • Priesemann, V.1    Valderrama, M.2    Wibral, M.3    Le Van Quyen, M.4
  • 26
    • 34249775479 scopus 로고    scopus 로고
    • Fading memory and time series prediction in recurrent networks with different forms of plasticity
    • DOI 10.1016/j.neunet.2007.04.020, PII S0893608007000469, Echo State Networks and Liquid State Machines
    • Lazar A, Pipa G, Triesch J (2007) Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks 20: 312-322. (Pubitemid 46856112)
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 312-322
    • Lazar, A.1    Pipa, G.2    Triesch, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.