Neural network dynamics

Annual Review of Neuroscience

Volumn 28, Issue , 2005, Pages 357-376

  Vogels, Tim P ^a   Rajan, Kanaka ^a   Abbott, L F ^a  

^a BRANDEIS UNIVERSITY   (United States)

Author keywords

Balance; Memory; Signal propagation; States; Sustained activity

Indexed keywords

COGNITION; NERVE CELL NETWORK; OSCILLATION; PRIORITY JOURNAL; REVIEW; SIGNAL PROCESSING; SPIKE; STIMULUS RESPONSE; WORKING MEMORY;

ACTION POTENTIALS; ANIMALS; HUMANS; NERVE NET; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 23344446786     PISSN: 0147006X     EISSN: None     Source Type: Book Series    
DOI: 10.1146/annurev.neuro.28.061604.135637     Document Type: Review

References (81)

1. Abbott LF, van Vreeswijk C. 1993. Asynchronous states in networks of pulse-coupled oscillators. Phys. Rev. E 48:1483-90
2. Abeles M. 1991. Corticonics: Neural Circuits of the Cerebral Cortex. Cambridge, UK: Cambridge Univ. Press. 280 pp.
3. Aertsen A, Diesmann M, Gewaltig MO. 1996. Propagation of synchronous spiking activity in feedforward neural networks. J. Physiol. Paris 90:243-47
4. Amit DJ, Brunel N. 1997. Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb. Cortex 7:237-52
5. Anderson JS, Lampl I, Gillespie DC, Ferster D. 2000. The contribution of noise to contrast invariance of orientation tuning in cat visual cortex. Science 290:1968-72
6. Arieli A, Sterkin A, Grinvald A, Aertsen A. 1996. Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 273:1868-71
7. Aviel Y, Mehring C, Abeles M, Horn D. 2003. On embedding synfire chains in a balanced network. Neural Comput. 15:1321-40
8. Beggs JM, Plenz D. 2003. Neuronal avalanches in neocortical circuits. J. Neurosci. 23:11167-77
9. Beggs JM, Plenz D. 2004. Neuronal avalanches are diverse and precise activity patterns that are stable for many hours in cortical slice cultures. J. Neurosci. 24:5216-29
10. Ben-Yishai R, Bar-Or RL, Sompolinsky H. 1995. Theory of orientation tuning in visual cortex. Proc. Natl. Acad. Sci. USA 92:3844-48
11. Ben-Yishai R, Hansel D, Sompolinsky H. 1997. Traveling waves and the processing of weakly tuned inputs in a cortical network module. J. Comput. Neurosci. 4:57-77
12. Brunel N. 2000. Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons. J. Physiol. Paris 94:445-63
13. Brunel N, Hakim D. 1999. Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural Comput. 11:1621-71
14. Brunel N, Sergi S. 1998. Firing frequency of leaky intergrate-and-fire neurons with synaptic current dynamics. J. Theor. Biol. 195:87-95
15. Burkitt AN, Clark GM. 1999. Analysis of integrate-and-fire neurons: synchronization of synaptic input and output spikes. Neural Comput. 11:871-901
16. Burns BD, Webb AC. 1976. The spontaneous activity of neurones in the cat's visual cortex. Proc. R. Soc. London B Biol. Sci. 194:211-23
17. Buzsaki G, Draguhn A. 2004. Neuronal oscillations in cortical networks. Science 304:1926-29
18. Camperi M, Wang X-J. 1998. A model of visuospatial short-term memory in prefrontal cortex: recurrent network and cellular bistability. J. Comput. Neurosci. 5:383-405
19. Cateau H, Fukai T. 2001. Fokker-Planck approach to the pulse packet propagation in synfire chain. Neural Netw. 14:675-85
20. Chance FS, Abbott LF, Reyes AD. 2002. Gain modulation through background synaptic input. Neuron 35:773-82
21. Compte A, Brunel N, Goldman-Rakic PS, Wang X-J. 2000. Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. Cereb. Cortex 10:910-23
22. Dayan P, Abbott LF. 2001. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press. 460 pp.
23. de Carvalho JX, Prado CP. 2000. Self-organized criticality in the olami-feder-christensen model. Phys. Rev. Lett. 84:4006-9
24. Dean AF. 1981. The variability of discharge of simple cells in the cat striat cortex. Exp. Brain Res. 44:437-40
25. Destexhe A. 1994. Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons. Phys. Rev. E 50:1594-606
26. Diesmann M, Gewaltig MO, Aertsen A. 1999. Stable propagation of synchronous spiking in cortical neural networks. Nature 402:529-33
27. Ermentrout GB, Cowan JD. 1979. Temporal oscillations in neuronal nets. J. Math. Biol. 7:265-80
28. Fusi S, Mattia M. 1999. Collective behavior of networks with linear (VLSI) integrate and fire neurons. Neural Comput. 11:633-52
29. Gerstner W. 2000. Population dynamics of spiking neurons: fast transients, asynchronous state, and locking. Neural Comput. 12:43-89
30. Golomb D. 1998. Models of neuronal transient synchrony during propagation of activity through neocortical circuitry. J. Neurophysiol. 79:1-12
31. Golomb D, Rinzel J. 1993. Dynamics of globally coupled inhibitory neurons with hereogeneity. Phys. Rev. E 48:4810-14
32. Gray CM. 1994. Synchronous oscillations in neuronal systems: mechanisms and functions. J. Comput. Neurosci. 1:11-38
33. Gutkin BS, Laing CR, Colby CL, Chow CC, Ermentrout GB. 2001. Turning on and off with excitation: the role of spike-timing asynchrony and synchrony in sustained neural activity. J. Comput. Neurosci. 11:121-34
34. Hahnloser RHR, Seung HS, Slotine JJ. 2003. Permitted and forbidden sets in symmetric threshold-linear networks. Neural Comput. 15:621-38
35. Hansel D, Mato G. 1993. Existence and stability of persistent states in large neuronal networks. Phys. Rev. Lett. 86:4175-78
36. Hansel D, Mato G. 2002. Asynchronous states and the emergence of synchrony in large networks of interacting excitatory and inhibitory neurons. Neural Comput. 15:1-56
37. Hansel D, Sompolinsky H. 2000. Modeling feature selectivity in local cortical circuits. In Methods in Neuronal Modeling: From Synapses to Networks, ed. C Koch, I Segev, pp. 499-567. Cambridge, MA: MIT Press
38. Harris TE. 1963. The Theory of Branching Processes. Berlin: Springer. 229 pp.
39. Herrmann M, Hertz J, Pruegel-Bennett A. 1995. Analysis of synfire chains. Netw.: Comput. Neural Syst. 6:403-14
40. Holt GR, Softky WR, Koch C, Douglas RJ. 1996. Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons. J. Neurophysiol. 75:1806-14
41. Laurent G. 1996. Dynamical representation of odors by oscillating and evolving neural assemblies. Trends Neurosci. 19:489-96
42. Leopold DA, Murayama Y, Logothetis NK. 2003. Very slow activity fluctuations in monkey visual cortex: Implications for functional brain imaging. Cereb. Cortex 13:422-433
43. Lerchner A, Ahmadi M, Hertz J. 2004. High-conductance states in a mean-field cortical network model. Neurocomputing 58-60:935-40
44. Litvak V, Sompolinsky H, Segev I, Abeles M. 2003. On the transmission of rate code in long feedforward networks with excitatory-inhibitory balance. J. Neurosci. 23:3006-15
45. Marder E, Calabrese RL. 1996. Principles of rhythmic motor pattern generation. Physiol. Rev. 76:687-17
46. Marsalek PR, Koch C, Maunsell J. 1997. On the relationship between synaptic input and spike output jitter in individual neurons. Proc. Natl. Acad. Sci. USA 94:735-40
47. Mehring C, Hehl U, Kubo M, Diesmann M, Aertsen A. 2003. Activity dynamics and propagation of synchronous spiking in locally connected random networks Biol. Cybern. 88:395-408
48. Ott E. 2002. Chaos in Dynamical Systems. Cambridge, UK: Cambridge Univ. Press. 478 pp.
49. Penttonen M, Buzsaki G. 2003. Natural logarithmic relationship between brain oscillators. Thalamus Relat. Syst. 2:145-52
50. Prinz AA, Bucher D, Marder E. 2004. Similar network activity from widely disparate combinations of intrinsic properties and synaptic strengths. Nat. Neurosci. 12:1345-52
51. Renart A, Song P, Wang X-J. 2003. Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks. Neuron 38:473-85
52. Reyes AD. 2003. Synchrony-dependent propagation of firing rate in iteratively constructed networks in vitro. Nat. Neurosci. 6:593-99
53. Ricciardi LM. 1977. Diffusion Processes and Related Topics in Biology. Berlin: Springer-Verlag. 200 pp.
54. Rinzel J, Ermentrout GB. 1998. Analysis of neural excitability and oscillations. In Methods in Neuronal Modeling, ed. C Koch, I Segev, pp. 251-91. Cambridge, MA: MIT Press
55. Salinas E, Sejnowski T. 2002. Integrate-and-fire neurons driven by correlated stochastic input. Neural Comput. 14:2111-55
56. Seung HS, Lee DD, Reis BY, Tank DW. 2000. Stability of the memory of eye position in a recurrent network of conductance-based model neurons. Neuron 26:259-71
57. Shadlen MN, Newsome WT. 1994. Noise, neural codes and cortical organization. Curr. Opin. Neurobiol. 4:569-79
58. Shriki O, Hansel D, Sompolinsky H. 2003. Rate models for conductance-based cortical neuronal networks Neural Comput. 15:1809-41
59. Silberberg G, Bethge M, Markram H, Pawelzik K, Tsodyks M. 2004. Dynamics of population rate codes in ensembles of neocortical neurons. J. Neurophysiol. 91:704-9
60. Softky WR, Koch C. 1993. The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J. Neurosci. 13:334-50
61. Song S, Sjöström PJ, Reigl M, Nelson SB, Chklovskii DB. 2005. Highly non-random features of synaptic connectivity in local cortical circuits. In press
62. Strogatz SH. 1994. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Reading, MA: Perseus Books. 498 pp.
63. Tegner J, Compte A, Wang X-J. 2002. The dynamical stability of reverberatory neural circuits. Biol. Cybern. 87:471-81
64. Traub R, Jefferys JGR, Whittington MA. 1997. Simulation of gamma rhythms in networks of interneurons and pyramidal cells. J. Comput. Neurosci. 4:141-50
65. Traub R, Jefferys JGR, Whittington MA. 1999. Fast Oscillations in Cortical Circuits. Cambridge, MA: MIT Press. 308 pp.
66. Traub RD, Miles R, Wong RKS. 1989. Model of the origin of rhythmic population oscillations in the hippocampal slice. Science 243:1319-25
67. Troyer TW, Miller KD. 1997. Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell. Neural Comput. 9:971-83
68. Tsodyks M, Sejnowski TJ. 1995. Rapid switching in balanced cortical network models. Network 6:1-14
69. Tuckwell HC. 1988. Introduction to Theoretical Neurobiology, Vol. 2. Cambridge, UK: Cambridge Univ. Press. 265 pp.
70. Usher M, Stemmler M, Koch C. 1994. Network amplification of local fluctuations causes high spike rate variability, fractal patterns and oscillatory local field potentials. Neural Comput. 6:795-836
71. van Rossum MC, Turrigiano GG, Nelson SB. 2002. Fast propagation of firing rates through layered networks of noisy neurons. J. Neurosci. 22:1956-66
72. van Vreeswijk C. 2000. Analysis of the asynchronous state in networks of strongly coupled oscillators. Phys. Rev. Lett. 84:5110-13
73. van Vreeswijk C, Sompolinsky H. 1996. Chaos in neuronal networks with balanced excitatory and inhibitory activity Science 274:1724-26
74. van Vreeswijk C, Sompolinsky H. 1998. Chaotic balanced state in a model of cortical circuits. Neural Comput. 10:1321-71
75. Vogels TP, Abbott LF. 2004. Signal propagation in large networks of integrate-and-fire neurons. Soc. Neurosci. 970.7 (Abstr.)
76. Wang X-J, Buzsaki G. 1996. Gamma oscillations by synaptic inhibition in a hippocampal interneuronal network model. J. Neurosci. 19:9587-603
77. Wang X-J, Goldman-Rakic P, eds. 2004. Special issue: Persistent neural activity: experiments and theory. Cereb. Cortex 13:1123-269
78. White JA, Chow CC, Ritt J, Soto-Trovino C, Kopell N. 1998. Synchronization and oscillatory dynamics in heterogeneous, mutually inhibibitory neurons. J. Comput. Neurosci. 5:5-16
79. Whittington MA, Traub RD, Kopell N, Ermentrout GB, Buhl EH. 2000. Inhibition-based rhythms: experiments and mathematical observations on network dynamics. Int. J. Psychophysiol. 38:315-36
80. Wilson HR, Cowan JD. 1972. Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 12:1-24
81. Zapperi S, Baekgaard Lauritsen K, Stanley HE. 1995. Self-organized branching processes: mean-field theory for avalanches. Phys. Rev. Lett. 75:4071-74