Dynamics of spiking neurons: Between homogeneity and synchrony

Journal of Computational Neuroscience

Volumn 34, Issue 3, 2013, Pages 433-460

  Rangan, Aaditya V ^a   Young, Lai Sang ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

Emergent dynamics; Multiple firing events; Spiking neurons

Indexed keywords

NETWORK ARCHITECTURE; NEURAL NETWORKS; NEURONS;

DIFFUSION PROCESS; EMERGENT DYNAMIC; EMERGENT PROPERTY; INTERMEDIATE REGIMES; MODEL PAPERS; MULTIPLE FIRING EVENT; NETWORK OF NEURONS; RANDOMLY CONNECTED NETWORKS; SPIKING NEURONES; STRUCTURED NETWORKS;

DYNAMICS;

ARTICLE; EXCITATORY POSTSYNAPTIC POTENTIAL; INHIBITORY POSTSYNAPTIC POTENTIAL; MULTIPLE FIRING EVENTS; NERVE CELL; NERVE CELL NETWORK; NERVOUS SYSTEM FUNCTION; PRIORITY JOURNAL; SPIKING NEURON; STRIATE CORTEX;

EID: 84877763820     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-012-0429-1     Document Type: Article

References (61)

1. Amit, D.; & Tsodyks, M. (1991). Quantitative study of attractor neural networks retrieving at low spike rates. I: Substrate - spikes, rates, and neuronal gain. Network, 2, 259-274.
2. Anderson, J.S.; Carandini, M.; Ferster, D. (2000). Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. Journal of Neurophysiology, 84, 909-926.
3. Battaglia, D.; & Hansel, D. (2011). Synchronous chaos and broad band gamma rhythm in a minimal multi-layer model of primary visual cortex. PLoS Computational Biology, 7(10), e1002176.
4. Benayoun, M.; Cowan, J.D.; van Drongelen, W.; Wallace, E. (2010). Avalanches in a stochastic model of spiking neurons. PLoS Computationam Biology, 6, e1000846.
5. Brunel, N.; & Hakim, V. (1999). Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural Computation, 11, 1621-1671.
6. Cai, D.; Tao, L.; Rangan, A.V.; McLaughlin, D. (2006). Kinetic theory for neuronal network dynamics. Communications in Mathematical Sciences, 4, 97.
7. Cardanobile, S.; & Rotter, S. (2010). Multiplicatively interacting point processes and applications to neural modeling. Journal of Computational Neuroscience, 28, 267-284.
8. Carlen, M.; Meletis, K.; Siegle, J.H.; Cardin, J.A.; Futai, K.; Vierling-Claassen, D.; Ruhlmann, C.; Jones, S.R.; Diesseroth, K.; Shen, M.; Moore, C.I.; Tsai, L.-H. (2011). A critical role for NMDA receptors in parvalbumin interneurons for gamma rhythm induction and behavior. Molecular Psychiatry, 11, 1-12.
9. Churchland, M.M.; et al. (2010). Stimulus onset quenches neural variability: a widespread cortical phenomenon. Nature Neuroscience, 13(3), 369-378.
10. Daw, N.W.; Stein, P.G.S.; Fox, K. (1993). The role of nmda receptors in information transmission. Annual Review Neuroscience, 16, 207-222.
11. Dayan, P.; & Abbott, L.F. (2001). Theoretical neuroscience. Cambridge: MIT Press.
12. DeWeese, M.R.; & Zador, A.M. (2006). Non-gaussian membrane potential dynamics imply sparse, synchronous activity in auditory cortex. Journal of Neuroscience, 22, 12206-12218.
13. Ermentrout, G.B.; & Cowan, J.D. (1979). A mathematical theory of visual hallucination patterns. Biological Cybernetics, 34, 137-150.
14. Feldmeyer, D.; Egger, V.; Lubke, J.; Sakmann, B. (1999). Reliable synaptic connections between pairs of excitatory layer 4 neurones within a single barrel of developing rat somatosensory cortex. Journal of Physiology, 521, 169-190.
15. Fox, K.; Sato, H.; Daw, N. (1998). The location and function of NMDA receptors in cat and kitten visual cortex. Journal of Neuroscience, 9, 2443-2454.
16. Gerstner, W. (2000). Population dynamics of spiking neurons: fast transients, asynchronous states, and locking. Neural Computation, 12, 43-80.
17. Goldberg, J.A.; Rokni, U.; Sompolinsky, H. (2004). Patterns of ongoing activity and the functional architecture of the primary visual cortex. Neuron, 13, 489-500.
18. Hansel, D.; & Sompolinsky, H. (1996). Chaos and synchrony in a model of a hypercolumn in visual cortex. Jornal of Computational Neuroscience, 3, 7-34.
19. Haskell, E.; Nykamp, D.Q.; Tranchina, D. (2001). Population density methods for large-scale modeling of neuronal networks with realistic synaptic kinetics: cutting the dimension down to size. Network: Computational Neural System 12, 141-174.
20. Homayoun, H.; & Moghaddam, B. (2007). Nmda receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons. Journal of Neuroscience, 24, 11496-11500.
21. Huntley, G.W.; Vickers, J.C.; Brose, N.; Heinemann, S.F.; Morrison, J.H. (1994). Distribution and synaptic localization of immunocytochemically identified nmda receptor subunit proteins in sensory motor and visual cortices of monkey and human. Journal of Neuroscience, 14, 3603-3619.
22. Jermakowicz, W.J.; Chen, X.; Khaytin, I.; Bonds, A.B.; Casagrande, V.A. (2009). Relationship between spontaneous and evoked spike-time correlations in primate visual cortex. Journal of Neurophysiology, 101, 2279-2289.
23. Knight, B. (1972). Dynamics of encoding in a populaton neurons. Journal of General Physiology, 59, 734-766.
24. Knight, B.; Manin, D.; Sirovich, L. (1996). Dynamical models of interacting neuron populations. In E. Gerf (Ed.), Symposium on robotics and cybernetics: computational engineering in systems applications. Lille: Cite Scientifique.
25. Kovacic, G.; Rangan, A.V.; Tao, L.; Cai, D. (2009). Fokker-Planck description of conductance-based integrate-and-fire neuronal networks. Physical Review E, 80, 021904.
26. Kremkow, J.; Perrinet, L.U.; Masson, G.S.; Aertsen, A. (2010). Functional consequences of correlated excitatory and inhibitory conductances in cortical networks. Journal on Computational Neuroscience, 28, 579-594.
27. Kriener, B.; T. Tetzlaff, Aertsen, A.; Diesmann, M.; Rotter, S. (2008). Correlations and population dynamics in cortical networks. Neural Computation, 20, 2185-2226.
28. Krukowski, A.E.; & Miller, K.D. (2001). Thalamocortical nmda conductances and intracortical inhibition can explain cortical temporal tuning. Nature Neuroscience, 4, 424-430.
29. Lampl, I.; Reichova, I.; Ferster, D. (1999). Synchronous membrane potential fluctuations in neurons of the cat visual cortex. Neuron, 22, 361-374.
30. Lei, H.; Riffell, J.A.; Gage, S.L.; Hildebrand, J.G. (2009). Contrast enhancement of stimulus intermittency in a primary olfactory network and its behavioral significance. Journal of Biology, 8, 21.
31. Loannides, A.A. (2007). Dynamic functional connectivity. Current Opinion in Neurobiology, 17, 161-170.
32. Lund, J.S.; Wu, Q.; Hadingham, P.T.; Levitt, J.B. (1995). Cells and circuits contributing to functional properties in area V1 of macaque monkey cerebral cortex: bases for neuroanatomically realistic models. Journal of Anatomy (London), 187, 563-581.
33. Mazzoni, A.; Broccard, F.D.; Garcia-Perez, E.; Bonifazi, P.; Ruaro, M.E.; Torre, V. (2007). On the dynamics of the spontaneous activity in neuronal networks. PLoS One, 5, e439.
34. Murphy, B.K.; & Miller, K.D. (2009). Balanced amplification: a new mechanism of selective amplification of neural activity patterns. Neuron, 61, 635-648.
35. Murthy, A.; & Humphrey, A.L. (1999). Inhibitory contributions to spatiotemporal receptive-field structure and direction selectivity in simple cells of cat area 17. Journal on Neurophysiology, 81, 1212-1224.
36. Myme, C.; Sugino, K.; Turrigiano, G.; Nelson, S.B. (2003). The nmda-to-ampa ratio at synapses onto layer 2/3 pyramidal neurons is conserved across prefrontal and visual cortices. Journal of Neurophysiology, 90, 771-779.
37. Ozeki, H.; Finn, I.M.; Schaffer, E.S.; Miller, K.D.; Ferster, D. (2009). Inhibitory stabilization of the cortical network. Neuron, 62, 578-592.
38. Petermann, T.; Thiagarajan, T.C.; Lebedev, M.A.; Nicolelis, M.A.L.; Chailvo, D.R.; Plenz, D. (2009). Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proceedings of the National Academy of Sciences of the United States of America, 106(37), 15921-15926.
39. Rangan, A.V. (2009). Diagrammatic expansion of pulse-coupled network dynamics. Physical Review Letters, 102, 158101.
40. Rangan, A.V.; & Cai, D. (2006). Maximum-entropy closures for kinetic theories of neuronal network dynamics. Physical Review Letters, 96, 178101.
41. Rangan, A.V.; Cai, D.; Kovacic, G. (2008). Kinetic theory for neuronal networks with fast and slow excitatory conductances driven by the same spike train. Physical Review E, 77, 041915.
42. Riffell, J.A.; Lei, H.; Christensen, T.A.; Hildebrand, J.G. (2009a). Characterization and coding of behaviorally significant odor mixtures. Current Biology, 19, 335-340.
43. Riffell, J.A.; Lei, H.; Hildebrand, J.G. (2009b). Neural correlates of behavior in the moth manduca sexta in response to complex odors. Proceedings of the Nationall Academy of Sciences, 106, 19219-19226.
44. Rivadulla, C.; Sharma, J.; Sur, M. (2001). Specific roles of nmda and ampa receptors in direction-selective and spatial phase-selective responses in visual cortex. Journal of Neuroscience, 21, 1710-1719.
45. Rosier, A.M.; Arckens, L.; Orban, G.A.; Vandesande, F. (1993). Laminar distribution of nmda receptors in cat and monkey visual cortex visualized by [3h]-mk-801 binding. Journal of Computational Neurology, 335, 369-380.
46. Samonds, J.M.; Zhou, Z.; Bernard, M.R.; Bonds, A.B. (2005). Synchronous activity in cat visual cortex encodes collinear and cocircular contours. Journal of Neurophysiology, 95(4), 2602-2616.
47. Schroeder, C.E.; Javitt, D.C.; Steinschneider, M.; Mehta, A.D.; Givre, S.J.; H.G. Vaughan, Arezzo, J.C. Jr. (1997). N-methyl-d-aspartate enhancement of phasic responses in primate neocortex. Experimental Brain Research, 114, 271-278.
48. Shiokawa, H.; Kaftan, E.J.; MacDermott, A.B.; Tong, C. (2010). Nr2 subunits and nmda receptors on lamina II inhibitory and excitatory interneurons of the mouse dorsal horn. Molecular Pain, 6, 1-15.
49. Sillito, A.M. (1975). The contribution of inhibitory mechanisms to the receptive field properties of neurones in the striate cortex of the cat. Journal of Physiology, London, 250, 305-329.
50. Sirovich, L.; Omurtag, A.; Knight, B. (2000). Dynamics of neuronal populations; the equilibrium solution. SIAM Journal in Applied Mathematics, 60, 2009-2028.
51. Sompolinsky, H.; & Shapley, R. (1997). New perspectives on the mechanisms for orientation selectivity. Current Opinion in Neurobiology, 7, 514-522.
52. Sun, Y.; Zhou, D.; Rangan, A.V.; Cai, D. (2010). Pseudo-Lyapunov exponents and predictability of Hodgkin-Huxley neuronal network dynamics. Journal of Computational Neuroscience, 28, 247-266.
53. Tsodyks, M.; Kenet, T.; Grinvald, A.; Arieli, A. (1999). Linking spontaneous activity of single cortical neurons and the underlying functional architecture. Science, 286, 1943-1946.
54. Wang, X.J. (1999). Synaptic basis of cortical persistent activity: the importance of nmda receptors to working memory. Journal of Neuroscience, 19, 9587-9603.
55. Wang, H.X.; & Gao, W.J. (2009). Cell type-specific development of NMDA receptors in the interneurons of rat prefrontal cortex. Neuropsychopharmacology, 34, 2028-2040.
56. Watt, A.J.; Rossum, M.C.W.; MacLeod, K.M.; Nelson, S.B.; Turrigiano, G.G. (2000). Activity coregulates quantal ampa and nmda currents at neocortical synapses. Neuron, 26, 659-670.
57. Wilson, H.; & Cowan, J. (1973). A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Kybernetik, 13, 55-80.
58. Worgotter, F.; & Koch, C. (1991). A detailed model of the primary visual pathway in the cat comparison of afferent excitatory and intracortical inhibitory connection schemes for orientation selectivity. Journal of Neuroscience, 11, 1959-1979.
59. Yu, Y.; & Ferster, D. (2010). Membrane potential synchrony in primary visual cortex during sensory stimulation. Neuron, 68, 1187-1201.
60. Yu, S.; Yang, H.; Nakahara, H.; Santos, G.S.; Nikolic, D.; Plenz, D. (2011). Higher-order interactions characterized in cortical activity. Journal of Neuroscience, 31, 17514-17526.
61. Zhou, D.; Sun, Y.; Rangan, A.V.; Cai, D. (2008). Network-induced chaos in integrate-and-fire neuronal ensembles. Physical Review E, 80, 031918.