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Volumn 8, Issue , 2014, Pages

Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise

Author keywords

Adaptive exponential integrate and fire neuron; Firing rate; Fokker Planck equation; Mean field; Spike triggered adaptation; Synaptic kinetics

Indexed keywords

DIFFERENTIAL EQUATIONS; ELECTROPHYSIOLOGY; FOKKER PLANCK EQUATION; NEURONS; PHYSIOLOGY; PROBABILITY DISTRIBUTIONS; TIMING JITTER;

EID: 84907294669     PISSN: None     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2014.00116     Document Type: Article
Times cited : (39)

References (117)
  • 1
    • 22244458151 scopus 로고
    • Asynchronousstatesinnetworksofpulse–coupledoscillators
    • Abbott, L.F., and van Vreeswijk, C.(1993).Asynchronousstatesinnetworksofpulse–coupledoscillators. Phys.Rev.E 48, 1483–1490.doi: 10.1103/PhysRevE.48.1483
    • (1993) Phys.Rev.E , vol.48 , pp. 1483-1490
    • Abbott, L.F.1    Van Vreeswijk, C.2
  • 2
    • 79961108119 scopus 로고    scopus 로고
    • Rateresponseofneuronssubjecttofast or frozennoise:Fromstochasticandhomogeneoustodeterministicandheterogeneous populations
    • Alijani, A.K., and Richardson, M.J.(2011).Rateresponseofneuronssubjecttofast or frozennoise:fromstochasticandhomogeneoustodeterministicandheterogeneous populations. Phys.Rev.E 84:011919. doi:10.1103/PhysRevE.84.011919
    • (2011) Phys.Rev.E , vol.84 , pp. 011919
    • Alijani, A.K.1    Richardson, M.J.2
  • 3
    • 0000438415 scopus 로고    scopus 로고
    • Dynamicsofarecurrentnetworkofspiking neuronsbeforeandfollowinglearning
    • Amit, D.J., and Brunel, N.(1997a).Dynamicsofarecurrentnetworkofspiking neuronsbeforeandfollowinglearning. Network 8, 373–404.doi:10.1088/0954-898X/8/4/003
    • (1997) Network , vol.8 , pp. 373-404
    • Amit, D.J.1    Brunel, N.2
  • 4
    • 0030947941 scopus 로고    scopus 로고
    • Modelofglobalspontaneousactivityandlocal structuredactivityduringdelayperiodsinthecerebralcortex
    • Amit, D.J., and Brunel, N.(1997b).Modelofglobalspontaneousactivityandlocal structuredactivityduringdelayperiodsinthecerebralcortex. Cereb.Cortex 7, 237–252. doi:10.1093/cercor/7.3.237
    • (1997) Cereb.Cortex , vol.7 , pp. 237-252
    • Amit, D.J.1    Brunel, N.2
  • 5
    • 36149028967 scopus 로고
    • Quantitative study of attract or neural network retrieving at low spike rates : I. substrate–spikes, rates and neuronal gain
    • Amit, D.J., and Tsodyks, M.V. (1991a). Quantitative study of attract or neural network retrieving at low spike rates: I. substrate–spikes, rates and neuronal gain. Netw. Comput. Neural Syst. 2, 259–273. doi:10.1088/0954-898X/2/3/003
    • (1991) Netw. Comput. Neural Syst , vol.2 , pp. 259-273
    • Amit, D.J.1    Tsodyks, M.V.2
  • 6
    • 36149034352 scopus 로고
    • Quantitative study of attract or neural networks retrieving at low spike rates: II. low-rate retrieval in symmetric networks
    • Amit, D.J., and Tsodyks, M.V. (1991b). Quantitative study of attract or neural networks retrieving at low spike rates: II. low-rate retrieval in symmetric networks. Netw. Comput. Neural Syst. 2, 275–294. doi:10.1088/0954-898X/2/3/004
    • (1991) Netw. Comput. Neural Syst , vol.2 , pp. 275-294
    • Amit, D.J.1    Tsodyks, M.V.2
  • 7
    • 33645456325 scopus 로고    scopus 로고
    • Persistent sodium current in layer 5 neocortical neurons is primarily generated in the proximal axon
    • Astman, N., Gutnick, M. J., and Fleidervish, I. A. (2006). Persistent sodium current in layer 5 neocortical neurons is primarily generated in the proximal axon. J. Neurosci. 26, 3465-3473. doi: 10.1523/JNEUROSCI.4907-05.2006
    • (2006) J. Neurosci , vol.26 , pp. 3465-3473
    • Astman, N.1    Gutnick, M.J.2    Fleidervish, I.A.3
  • 8
    • 84873695338 scopus 로고    scopus 로고
    • How adaptation shapes spike rate oscillations in recurrent neuronal networks
    • Augustin, M., Ladenbauer, J., and Obermayer, K. (2013). How adaptation shapes spike rate oscillations in recurrent neuronal networks. Front. Comput. Neurosci. 7:9. doi: 10.3389/fncom.2013.00009
    • (2013) Front. Comput. Neurosci , vol.7 , pp. 9
    • Augustin, M.1    Ladenbauer, J.2    Obermayer, K.3
  • 9
    • 56449129046 scopus 로고    scopus 로고
    • Extracting non-linear integrate-and-fire models from experimental data using dynamic i-v curves
    • Badel, L., Lefort, S., Berger, T. K., Petersen, C. C. H., Gerstner, W., and Richardson, M. J. E. (2008a). Extracting non-linear integrate-and-fire models from experimental data using dynamic i-v curves. Biol. Cybern. 99, 361-370. doi: 10.1007/s00422-008-0259-4
    • (2008) Biol. Cybern , vol.99 , pp. 361-370
    • Badel, L.1    Lefort, S.2    Berger, T.K.3    Petersen, C.C.H.4    Gerstner, W.5    Richardson, M.J.E.6
  • 10
    • 39149096545 scopus 로고    scopus 로고
    • Dynamic IV curves are reliable predictors of naturalistic pyramidal-neuron voltage traces
    • Badel, L., Lefort, S., Brette, R., Petersen, C., Gerstner, W., and Richardson, M. (2008b). Dynamic IV curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. J. Neurophysiol. 99, 656-666. doi: 10.1152/jn.01107.2007
    • (2008) J. Neurophysiol , vol.99 , pp. 656-666
    • Badel, L.1    Lefort, S.2    Brette, R.3    Petersen, C.4    Gerstner, W.5    Richardson, M.6
  • 11
    • 79958164664 scopus 로고    scopus 로고
    • Attracting dynamics of frontal cortex ensembles during memoryguided decision-making
    • Balaguer-Ballester, E., Lapish, C. C., Seamans, J. K., and Durstewitz, D. (2011). Attracting dynamics of frontal cortex ensembles during memoryguided decision-making. PLoS Comput. Biol. 7:e1002057. doi: 10.1371/journal.pcbi.1002057
    • (2011) PLoS Comput. Biol , vol.7
    • Balaguer-Ballester, E.1    Lapish, C.C.2    Seamans, J.K.3    Durstewitz, D.4
  • 12
    • 0035970024 scopus 로고    scopus 로고
    • Construction and analysis of non-poisson stimulus-response models of neural spiking activity
    • Barbieri, R., Quirk, M. C., Frank, L. M., Wilson, M. A., and Brown, E. N. (2001). Construction and analysis of non-poisson stimulus-response models of neural spiking activity. J. Neurosci. Methods 105, 25-37. doi: 10.1016/S01650270(00)00344-7
    • (2001) J. Neurosci. Methods , vol.105 , pp. 25-37
    • Barbieri, R.1    Quirk, M.C.2    Frank, L.M.3    Wilson, M.A.4    Brown, E.N.5
  • 13
    • 0141749203 scopus 로고    scopus 로고
    • A universal model for Spike-Frequency adaptation
    • Benda, J., and Herz, A. V. M. (2003). A universal model for Spike-Frequency adaptation. Neural Comput. 15, 2523-2564. doi: 10.1162/089976603322385063
    • (2003) Neural Comput , vol.15 , pp. 2523-2564
    • Benda, J.1    Herz, A.V.M.2
  • 15
    • 27144498986 scopus 로고    scopus 로고
    • Adaptive exponential integrate-and-fire model as an effective description of neuronal activity
    • Brette, R., and Gerstner, W. (2005). Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. J. Neurophysiol. 94, 3637-3642. doi: 10.1152/jn.00686.2005
    • (2005) J. Neurophysiol , vol.94 , pp. 3637-3642
    • Brette, R.1    Gerstner, W.2
  • 16
    • 0018886033 scopus 로고
    • Muscarinic suppression of a novel voltage-sensitive k+ current in a vertebrate neurone
    • Brown, D. A., and Adams, P. R. (1980). Muscarinic suppression of a novel voltage-sensitive k+ current in a vertebrate neurone. Nature 283, 673-676. doi: 10.1038/283673a0
    • (1980) Nature , vol.283 , pp. 673-676
    • Brown, D.A.1    Adams, P.R.2
  • 17
    • 0034006515 scopus 로고    scopus 로고
    • Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons
    • Brunel, N. (2000a). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8, 183-208. doi: 10.1023/A:1008925309027
    • (2000) J. Comput. Neurosci , vol.8 , pp. 183-208
    • Brunel, N.1
  • 18
    • 0041730763 scopus 로고    scopus 로고
    • Persistent activity and the single-cell frequency-current curve in a cortical network model
    • Brunel, N. (2000b). Persistent activity and the single-cell frequency-current curve in a cortical network model. Network Comput. Neural Syst. 11, 261-280. doi: 10.1088/0954-898X/11/4/302
    • (2000) Network Comput. Neural Syst , vol.11 , pp. 261-280
    • Brunel, N.1
  • 19
    • 0033210816 scopus 로고    scopus 로고
    • Fast global oscillations in networks of integrateand-fire neurons with low firing rates
    • Brunel, N., and Hakim, V. (1999). Fast global oscillations in networks of integrateand-fire neurons with low firing rates. Neural Comput. 11, 1621-1671. doi: 10.1162/089976699300016179
    • (1999) Neural Comput , vol.11 , pp. 1621-1671
    • Brunel, N.1    Hakim, V.2
  • 20
    • 42749100584 scopus 로고    scopus 로고
    • Firing-rate resonance in a generalized integrate-and-fire neuron with subthreshold resonance
    • Brunel, N., Hakim, V., and Richardson, M. J. E. (2003). Firing-rate resonance in a generalized integrate-and-fire neuron with subthreshold resonance. Phys. Rev. E 67:051916. doi: 10.1103/PhysRevE.67.051916
    • (2003) Phys. Rev. E , vol.67 , pp. 051916
    • Brunel, N.1    Hakim, V.2    Richardson, M.J.E.3
  • 21
    • 33646397012 scopus 로고    scopus 로고
    • How noise affects the synchronization properties of recurrent networks of inhibitory neurons
    • Brunel, N., and Hansel, D. (2006). How noise affects the synchronization properties of recurrent networks of inhibitory neurons. Neural Comput. 18, 1066-1110. doi: 10.1162/neco.2006.18.5.1066
    • (2006) Neural Comput , vol.18 , pp. 1066-1110
    • Brunel, N.1    Hansel, D.2
  • 22
    • 0041360352 scopus 로고    scopus 로고
    • Firing rate of the noisy quadratic integrate-and-fire neuron
    • Brunel, N., and Latham, P. E. (2003). Firing rate of the noisy quadratic integrate-and-fire neuron. Neural Comput. 15, 2281-2306. doi: 10.1162/089976603322362365
    • (2003) Neural Comput , vol.15 , pp. 2281-2306
    • Brunel, N.1    Latham, P.E.2
  • 23
    • 0032494755 scopus 로고    scopus 로고
    • Firing frequency of leaky integrate-and-fire neurons with synaptic current dynamics
    • Brunel, N., and Sergi, S. (1998). Firing frequency of leaky integrate-and-fire neurons with synaptic current dynamics. J. Theor. Biol. 195, 87-95. doi: 10.1006/jtbi.1998.0782
    • (1998) J. Theor. Biol , vol.195 , pp. 87-95
    • Brunel, N.1    Sergi, S.2
  • 24
    • 0034814469 scopus 로고    scopus 로고
    • Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition
    • Brunel, N., and Wang, X.-J. (2001). Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. J. Comput. Neurosci. 11, 63-85. doi: 10.1023/A:1011204814320
    • (2001) J. Comput. Neurosci , vol.11 , pp. 63-85
    • Brunel, N.1    Wang, X.-J.2
  • 25
    • 0141957923 scopus 로고    scopus 로고
    • Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input
    • Burkitt, A. N., Meffin, H., and Grayden, D. B. (2003). Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input. Biol. cybern. 89, 119-125. doi: 10.1007/s00422-003-0408-8
    • (2003) Biol. cybern , vol.89 , pp. 119-125
    • Burkitt, A.N.1    Meffin, H.2    Grayden, D.B.3
  • 26
    • 33846649561 scopus 로고    scopus 로고
    • Population model of hippocampal pyramidal neurons, linking a refractory density approach to conductancebased neurons
    • Chizhov, A. V., and Graham, L. J. (2007). Population model of hippocampal pyramidal neurons, linking a refractory density approach to conductancebased neurons. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 75:011924. doi: 10.1103/PhysRevE.75.011924
    • (2007) Phys. Rev. E Stat. Nonlin. Soft Matter Phys , vol.75 , pp. 011924
    • Chizhov, A.V.1    Graham, L.J.2
  • 27
    • 34247491502 scopus 로고    scopus 로고
    • Predicting neuronal activity with simple models of the threshold type: Adaptive exponential Integrate-and-Fire model with two compartments
    • Clopath Jolivet, R., Rauch, A., Lüscher, H., and Gerstner, W. (2007). Predicting neuronal activity with simple models of the threshold type: adaptive exponential Integrate-and-Fire model with two compartments. Neurocomputing 70, 1668-1673. doi: 10.1016/j.neucom.2006.10.047
    • (2007) Neurocomputing , vol.70 , pp. 1668-1673
    • Clopath Jolivet, R.1    Rauch, A.2    Lüscher, H.3    Gerstner, W.4
  • 28
    • 0023738153 scopus 로고
    • Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and cat
    • Connors, B., Malenka, R., and Silva, L. (1988). Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and cat. J. Physiol. 406, 443-468.
    • (1988) J. Physiol , vol.406 , pp. 443-468
    • Connors, B.1    Malenka, R.2    Silva, L.3
  • 29
    • 74549209036 scopus 로고    scopus 로고
    • Effective reduced diffusion-models: A data driven approach to the analysis of neuronal dynamics
    • Deco, G., Mart, D., Ledberg, A., Reig, R., and Sanchez Vives, M. V. (2009). Effective reduced diffusion-models: a data driven approach to the analysis of neuronal dynamics. PLoS Comput. Biol. 5:e1000587. doi: 10.1371/journal.pcbi.1000587
    • (2009) PLoS Comput. Biol , vol.5
    • Deco, G.1    Mart, D.2    Ledberg, A.3    Reig, R.4    Sanchez Vives, M.V.5
  • 30
    • 0030614345 scopus 로고    scopus 로고
    • Presynaptic and postsynaptic GABAB receptors of neocortical neurons of the rat in vitro: Differences in pharmacology and ionic mechanisms
    • Deisz, R. A., Billard, J.-M., and Zieglgänsberger, W. (1997). Presynaptic and postsynaptic GABAB receptors of neocortical neurons of the rat in vitro: differences in pharmacology and ionic mechanisms. Synapse 25, 62-72. doi: 10.1002/(SICI)1098-2396(199701)25:1<62::AID-SYN8>3.0.CO;2-D
    • (1997) Synapse , vol.25 , pp. 62-72
    • Deisz, R.A.1    Billard, J.-M.2    Zieglgänsberger, W.3
  • 31
    • 0141947274 scopus 로고    scopus 로고
    • Modelling the formation of working memory with networks of integrate-and-fire neurons connected by plastic synapses
    • Del Giudice, P., Fusi, S., and Mattia, M. (2003). Modelling the formation of working memory with networks of integrate-and-fire neurons connected by plastic synapses. J. Physiol. Paris 97, 659-681. doi: 10.1016/j.jphysparis.2004.01.021
    • (2003) J. Physiol. Paris , vol.97 , pp. 659-681
    • Del Giudice, P.1    Fusi, S.2    Mattia, M.3
  • 32
    • 0141499222 scopus 로고    scopus 로고
    • The high-conductance state of neocortical neurons in vivo
    • Destexhe, A., Rudolph, M., and Paré, D. (2003). The high-conductance state of neocortical neurons in vivo. Nat. Rev. Neurosci. 4, 739-751. doi: 10.1038/nrn1198
    • (2003) Nat. Rev. Neurosci , vol.4 , pp. 739-751
    • Destexhe, A.1    Rudolph, M.2    Paré, D.3
  • 33
    • 0030919664 scopus 로고    scopus 로고
    • Heterogeneity of release probability, facilitation, and depletion at central synapses
    • Dobrunz, L. E., and Stevens, C. F. (1997). Heterogeneity of release probability, facilitation, and depletion at central synapses. Neuron 18, 995-1008. doi: 10.1016/S0896-6273(00)80338-4
    • (1997) Neuron , vol.18 , pp. 995-1008
    • Dobrunz, L.E.1    Stevens, C.F.2
  • 34
    • 70349403747 scopus 로고    scopus 로고
    • Implications of synaptic biophysics for recurrent network dynamics and active memory
    • Durstewitz, D. (2009). Implications of synaptic biophysics for recurrent network dynamics and active memory. Neural Netw. 22, 1189-1200. doi: 10.1016/j.neunet.2009.07.016
    • (2009) Neural Netw , vol.22 , pp. 1189-1200
    • Durstewitz, D.1
  • 35
    • 33947276377 scopus 로고    scopus 로고
    • Dynamical basis of irregular spiking in NMDA-Driven prefrontal cortex neurons
    • Durstewitz, D., and Gabriel, T. (2007). Dynamical basis of irregular spiking in NMDA-Driven prefrontal cortex neurons. Cereb. Cortex 17, 894-908. doi: 10.1093/cercor/bhk044
    • (2007) Cereb. Cortex , vol.17 , pp. 894-908
    • Durstewitz, D.1    Gabriel, T.2
  • 36
    • 84907284936 scopus 로고    scopus 로고
    • “How can computational models be better utilized for understanding and treating schizophrenia?,”
    • Chapter 12, eds S. M. Silverstein, B. Moghaddam, and T. Wykes (Cambridge, MA: MIT Press
    • Durstewitz, D., and Seamans, J. K. (2012). “How can computational models be better utilized for understanding and treating schizophrenia?,” in Schizophrenia: Evolution and Synthesis, Chapter 12, eds S. M. Silverstein, B. Moghaddam, and T. Wykes (Cambridge, MA: MIT Press), 195-207.
    • (2012) Schizophrenia: Evolution and Synthesis , pp. 195-207
    • Durstewitz, D.1    Seamans, J.K.2
  • 37
    • 79961057097 scopus 로고    scopus 로고
    • Adaptation reduces variability of the neuronal population code
    • Farkhooi, F., Muller, E., and Nawrot, M. P. (2011). Adaptation reduces variability of the neuronal population code. Phys. Rev. E 83:050905. doi: 10.1103/PhysRevE.83.050905
    • (2011) Phys. Rev. E , vol.83 , pp. 050905
    • Farkhooi, F.1    Muller, E.2    Nawrot, M.P.3
  • 38
    • 0029744961 scopus 로고    scopus 로고
    • Kinetics of slow inactivation of persistent sodium current in layer v neurons of mouse neocortical slices
    • Fleidervish, I., and Gutnick, M. (1996). Kinetics of slow inactivation of persistent sodium current in layer v neurons of mouse neocortical slices. J. Neurophysiol. 76, 2125-2130.
    • (1996) J. Neurophysiol , vol.76 , pp. 2125-2130
    • Fleidervish, I.1    Gutnick, M.2
  • 39
    • 0347694858 scopus 로고    scopus 로고
    • How spike generation mechanisms determine the neuronal response to fluctuating inputs
    • Fourcaud-Trocmé, N., Hansel, D., van Vreeswijk, C., and Brunel, N. (2003). How spike generation mechanisms determine the neuronal response to fluctuating inputs. J. Neurosci. 23, 11628-11640.
    • (2003) J. Neurosci , vol.23 , pp. 11628-11640
    • Fourcaud-Trocmé, N.1    Hansel, D.2    Van Vreeswijk, C.3    Brunel, N.4
  • 40
    • 0036340236 scopus 로고    scopus 로고
    • Spike frequency adaptation and neocortical rhythms
    • Fuhrmann, G., Markram, H., and Tsodyks, M. (2002). Spike frequency adaptation and neocortical rhythms. J. Neurophysiol. 88, 761-770. doi: 10.1152/jn.00848.2001
    • (2002) J. Neurophysiol , vol.88 , pp. 761-770
    • Fuhrmann, G.1    Markram, H.2    Tsodyks, M.3
  • 41
    • 0033110047 scopus 로고    scopus 로고
    • Collective behavior of networks with linear (VLSI) integrate-and-fire neurons
    • Fusi, S., and Mattia, M. (1999). Collective behavior of networks with linear (VLSI) integrate-and-fire neurons. Neural Comput. 11, 633-652. doi: 10.1162/089976699300016601
    • (1999) Neural Comput , vol.11 , pp. 633-652
    • Fusi, S.1    Mattia, M.2
  • 42
    • 70350130109 scopus 로고    scopus 로고
    • How good are neuron models?
    • Gerstner, W., and Naud, R. (2009). How good are neuron models? Science 326, 379-380. doi: 10.1126/science.1181936
    • (2009) Science , vol.326 , pp. 379-380
    • Gerstner, W.1    Naud, R.2
  • 43
    • 34147131228 scopus 로고    scopus 로고
    • Diverse populationbursting modes of adapting spiking neurons
    • Gigante, G., Mattia, M., and Del Giudice, P. (2007). Diverse populationbursting modes of adapting spiking neurons. Phys. Rev. Lett. 98:148101. doi: 10.1103/PhysRevLett.98.148101
    • (2007) Phys. Rev. Lett , vol.98 , pp. 148101
    • Gigante, G.1    Mattia, M.2    Del Giudice, P.3
  • 44
    • 0001153339 scopus 로고
    • Amplitude distribution of shot noise
    • Gilbert, E. N., and Pollak, H. O. (1960). Amplitude distribution of shot noise. Bell Syst. Tech. J. 39, 333-350. doi: 10.1002/j.1538-7305.1960.tb01603.x
    • (1960) Bell Syst. Tech. J , vol.39 , pp. 333-350
    • Gilbert, E.N.1    Pollak, H.O.2
  • 45
    • 33646833761 scopus 로고    scopus 로고
    • Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition
    • Haider, B., Duque, A., Hasenstaub, A. R., and McCormick, D. A. (2006). Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. J. Neurosci. 26, 4535-4545. doi: 10.1523/JNEUROSCI.5297-05.2006
    • (2006) J. Neurosci , vol.26 , pp. 4535-4545
    • Haider, B.1    Duque, A.2    Hasenstaub, A.R.3    McCormick, D.A.4
  • 46
    • 0030087942 scopus 로고    scopus 로고
    • 2+ signaling in dendrites of pyramidal neurons
    • 2+ signaling in dendrites of pyramidal neurons. Biophys. J. 70, 1069-1081. doi: 10.1016/S0006-3495(96)79653-4
    • (1996) Biophys. J , vol.70 , pp. 1069-1081
    • Helmchen, F.1    Imoto, K.2    Sakmann, B.3
  • 47
    • 84865959800 scopus 로고    scopus 로고
    • An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data
    • Hertäg, L., Hass, J., Golovko, T., and Durstewitz, D. (2012). An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data. Front. Comput. Neurosci. 6:62. doi: 10.3389/fncom.2012.00062
    • (2012) Front. Comput. Neurosci , vol.6 , pp. 62
    • Hertäg, L.1    Hass, J.2    Golovko, T.3    Durstewitz, D.4
  • 48
    • 0742268989 scopus 로고    scopus 로고
    • Simple model of spiking neurons
    • Izhikevich, E. (2003). Simple model of spiking neurons. IEEE Trans. Neural Netw. 14, 1569-1572. doi: 10.1109/TNN.2003.820440
    • (2003) IEEE Trans. Neural Netw , vol.14 , pp. 1569-1572
    • Izhikevich, E.1
  • 50
    • 42149192537 scopus 로고    scopus 로고
    • Large-scale model of mammalian thalamocortical systems
    • Izhikevich, E. M., and Edelman, G. M. (2008). Large-scale model of mammalian thalamocortical systems. Proc. Natl. Acad. Sci. U.S.A. 105, 3593-3598. doi: 10.1073/pnas.0712231105
    • (2008) Proc. Natl. Acad. Sci. U.S.A , vol.105 , pp. 3593-3598
    • Izhikevich, E.M.1    Edelman, G.M.2
  • 51
    • 0025483631 scopus 로고
    • Voltage dependence of NMDA-Activated macroscopic conductances predicted by Single-Channel kinetics
    • Jahr, C. E., and Stevens, C. F. (1990). Voltage dependence of NMDA-Activated macroscopic conductances predicted by Single-Channel kinetics. J. Neurosci. 10, 3178-3182.
    • (1990) J. Neurosci , vol.10 , pp. 3178-3182
    • Jahr, C.E.1    Stevens, C.F.2
  • 52
    • 41049097311 scopus 로고    scopus 로고
    • A benchmark test for a quantitative assessment of simple neuron models
    • Jolivet, R., Kobayashi, R., Rauch, A., Naud, R., Shinomoto, S., and Gerstner, W. (2008). A benchmark test for a quantitative assessment of simple neuron models. J. Neurosci. Methods 169, 417-424. doi: 10.1016/j.jneumeth.2007.11.006
    • (2008) J. Neurosci. Methods , vol.169 , pp. 417-424
    • Jolivet, R.1    Kobayashi, R.2    Rauch, A.3    Naud, R.4    Shinomoto, S.5    Gerstner, W.6
  • 53
    • 33745833056 scopus 로고    scopus 로고
    • Predicting spike timing of neocortical pyramidal neurons by simple threshold models
    • Jolivet, R., Rauch, A., Lüscher, H., and Gerstner, W. (2006). Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J. Comput. Neurosci. 21, 35-49. doi: 10.1007/s10827-006-7074-5
    • (2006) J. Comput. Neurosci , vol.21 , pp. 35-49
    • Jolivet, R.1    Rauch, A.2    Lüscher, H.3    Gerstner, W.4
  • 56
    • 4344670177 scopus 로고    scopus 로고
    • Minimal models of adapted neuronal response to in vivo-Like input currents
    • La Camera, G., Rauch, A., Lüscher, H.-R., Senn, W., and Fusi, S. (2004). Minimal models of adapted neuronal response to in vivo-Like input currents. Neural Comput. 16, 2101-2124. doi: 10.1162/0899766041732468
    • (2004) Neural Comput , vol.16 , pp. 2101-2124
    • La Camera, G.1    Rauch, A.2    Lüscher, H.-R.3    Senn, W.4    Fusi, S.5
  • 57
    • 84900805510 scopus 로고    scopus 로고
    • How adaptation currents change threshold, gain, and variability of neuronal spiking
    • Ladenbauer, J. M., Augustin, M., and Obermayer, K. (2014). How adaptation currents change threshold, gain, and variability of neuronal spiking. J. Neurophysiol. 111, 939-953. doi: 10.1152/jn.00586.2013
    • (2014) J. Neurophysiol , vol.111 , pp. 939-953
    • Ladenbauer, J.M.1    Augustin, M.2    Obermayer, K.3
  • 58
    • 61649093252 scopus 로고    scopus 로고
    • Associative memory models: From the cell-assembly theory to biophysically detailed cortex simulations
    • Lansner, A. (2009). Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations. Trends Neurosci. 32, 178-186. doi: 10.1016/j.tins.2008.12.002
    • (2009) Trends Neurosci , vol.32 , pp. 178-186
    • Lansner, A.1
  • 59
    • 84959542925 scopus 로고    scopus 로고
    • Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs
    • Ledoux, E., and Brunel, N. (2011). Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs. Front. Comput. Neurosci. 5:25. doi: 10.3389/fncom.2011.00025
    • (2011) Front. Comput. Neurosci , vol.5 , pp. 25
    • Ledoux, E.1    Brunel, N.2
  • 60
    • 58549118757 scopus 로고    scopus 로고
    • The excitatory neuronal network of the c2 barrel column in mouse primary somatosensory cortex
    • Lefort, S., Tomm, C., Floyd Sarria, J.-C., and Petersen, C. C. (2009). The excitatory neuronal network of the c2 barrel column in mouse primary somatosensory cortex. Neuron 61, 301-316. doi: 10.1016/j.neuron.2008.12.020
    • (2009) Neuron , vol.61 , pp. 301-316
    • Lefort, S.1    Tomm, C.2    Floyd Sarria, J.-C.3    Petersen, C.C.4
  • 61
    • 77954231844 scopus 로고    scopus 로고
    • Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex
    • London, M., Roth, A., Beeren, L., Häusser, M., and Latham, P. E. (2010). Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466, 123-127. doi: 10.1038/nature09086
    • (2010) Nature , vol.466 , pp. 123-127
    • London, M.1    Roth, A.2    Beeren, L.3    Häusser, M.4    Latham, P.E.5
  • 62
    • 77955487287 scopus 로고    scopus 로고
    • Bistable, irregular firing and population oscillations in a modular attractor memory network
    • Lundqvist, M., Compte, A., and Lansner, A. (2010). Bistable, irregular firing and population oscillations in a modular attractor memory network. PLoS Comput. Biol. 6:e1000803. doi: 10.1371/journal.pcbi.1000803
    • (2010) PLoS Comput. Biol , vol.6
    • Lundqvist, M.1    Compte, A.2    Lansner, A.3
  • 63
    • 0021284570 scopus 로고
    • Control of the repetitive discharge of rat CA 1 pyramidal neurones in vitro
    • Madison, D. V., and Nicoll, R. A. (1984). Control of the repetitive discharge of rat CA 1 pyramidal neurones in vitro. J. Physiol. 354, 319-331.
    • (1984) J. Physiol , vol.354 , pp. 319-331
    • Madison, D.V.1    Nicoll, R.A.2
  • 64
    • 65549099674 scopus 로고    scopus 로고
    • Beyond poisson: Increased spiketime regularity across primate parietal cortex
    • Maimon, G., and Assad, J. A. (2009). Beyond poisson: increased spiketime regularity across primate parietal cortex. Neuron 62, 426-440. doi: 10.1016/j.neuron.2009.03.021
    • (2009) Neuron , vol.62 , pp. 426-440
    • Maimon, G.1    Assad, J.A.2
  • 65
    • 84887390404 scopus 로고    scopus 로고
    • Contextdependent computation by recurrent dynamics in prefrontal cortex
    • Mante, V., Sussillo, D., Shenoy, K. V., and Newsome, W. T. (2013). Contextdependent computation by recurrent dynamics in prefrontal cortex. Nature 503, 78-84. doi: 10.1038/nature12742
    • (2013) Nature , vol.503 , pp. 78-84
    • Mante, V.1    Sussillo, D.2    Shenoy, K.V.3    Newsome, W.T.4
  • 66
    • 31444442519 scopus 로고    scopus 로고
    • The blue brain project
    • Markram, H. (2006). The blue brain project. Nat. Rev. Neurosci. 7, 153-160. doi: 10.1038/nrn1848
    • (2006) Nat. Rev. Neurosci , vol.7 , pp. 153-160
    • Markram, H.1
  • 67
    • 84861414911 scopus 로고    scopus 로고
    • The human brain project
    • Markram, H. (2012). The human brain project. Sci. Am. 306, 50-55. doi: 10.1038/scientificamerican0612-50
    • (2012) Sci. Am , vol.306 , pp. 50-55
    • Markram, H.1
  • 68
    • 1842333229 scopus 로고    scopus 로고
    • Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex
    • Markram, H., Lübke, J., Frotscher, M., Roth, A., and Sakmann, B. (1997). Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. J. Physiol. 500, 409-440.
    • (1997) J. Physiol , vol.500 , pp. 409-440
    • Markram, H.1    Lübke, J.2    Frotscher, M.3    Roth, A.4    Sakmann, B.5
  • 69
    • 0026044988 scopus 로고
    • Synaptic transmission between individual pyramidal neurons of the rat visual cortex in vitro
    • Mason, A., Nicoll, A., and Stratford, K. (1991). Synaptic transmission between individual pyramidal neurons of the rat visual cortex in vitro. J. Neurosci. 11, 72-84.
    • (1991) J. Neurosci , vol.11 , pp. 72-84
    • Mason, A.1    Nicoll, A.2    Stratford, K.3
  • 70
    • 85036133906 scopus 로고    scopus 로고
    • Population dynamics of interacting spiking neurons
    • Mattia, M., and Del Giudice, P. (2002). Population dynamics of interacting spiking neurons. Phys. Rev. E 66:051917. doi: 10.1103/PhysRevE.66.051917
    • (2002) Phys. Rev. E , vol.66 , pp. 051917
    • Mattia, M.1    Del Giudice, P.2
  • 71
    • 0022249586 scopus 로고
    • Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex
    • McCormick, D. A., Connors, B. W., Lighthall, J. W., and Prince, D. A. (1985). Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 54, 782-806.
    • (1985) J. Neurophysiol , vol.54 , pp. 782-806
    • McCormick, D.A.1    Connors, B.W.2    Lighthall, J.W.3    Prince, D.A.4
  • 72
    • 84907290031 scopus 로고    scopus 로고
    • “How can models be better utilized to enhance outcome?,”
    • Chapter 13, eds S. M. Silverstein, B. Moghaddam, and T. Wykes (Cambridge, MA: MIT Press
    • Mitchell, K. J., O’Donnell, P., Durstewitz, D., Fenton, A. A., Gringrich, J. A., Gordon, J. A., et al. (2012). “How can models be better utilized to enhance outcome?,” in Schizophrenia: Evolution and Synthesis, Chapter 13, eds S. M. Silverstein, B. Moghaddam, and T. Wykes (Cambridge, MA: MIT Press), 209-223.
    • (2012) Schizophrenia: Evolution and Synthesis , pp. 209-223
    • Mitchell, K.J.1    O’donnell, P.2    Durstewitz, D.3    Fenton, A.A.4    Gringrich, J.A.5    Gordon, J.A.6
  • 73
    • 37249044144 scopus 로고    scopus 로고
    • Balanced excitatory and inhibitory inputs to cortical neurons decouple firing irregularity from rate modulations
    • Miura, K., Tsubo, Y., Okada, M., and Fukai, T. (2007). Balanced excitatory and inhibitory inputs to cortical neurons decouple firing irregularity from rate modulations. J. Neurosci. 27, 13802-13812. doi: 10.1523/JNEUROSCI.2452-07.2007
    • (2007) J. Neurosci , vol.27 , pp. 13802-13812
    • Miura, K.1    Tsubo, Y.2    Okada, M.3    Fukai, T.4
  • 74
    • 0022411669 scopus 로고
    • Distribution of n-methyl-daspartate-sensitive l-[3h] glutamate-binding sites in rat brain
    • Monaghan, D. T., and Cotman, C. W. (1985). Distribution of n-methyl-daspartate-sensitive l-[3h] glutamate-binding sites in rat brain. J. Neurosci. 5, 2909-2919.
    • (1985) J. Neurosci , vol.5 , pp. 2909-2919
    • Monaghan, D.T.1    Cotman, C.W.2
  • 76
    • 0037207351 scopus 로고    scopus 로고
    • Response of spiking neurons to correlated inputs
    • Moreno, R., de la Rocha, J., Renart, A., and Parga, N. (2002). Response of spiking neurons to correlated inputs. Phys. Rev. Lett. 89:288101. doi: 10.1103/PhysRevLett.89.288101
    • (2002) Phys. Rev. Lett , vol.89 , pp. 288101
    • Moreno, R.1    de la Rocha, J.2    Renart, A.3    Parga, N.4
  • 77
    • 36248947984 scopus 로고    scopus 로고
    • Spike-frequency adapting neural ensembles: Beyond mean adaptation and renewal theories
    • Muller, E., Buesing, L., Schemmel, J., and Meier, K. (2007). Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories. Neural Comput. 19, 2958-3010. doi: 10.1162/neco.2007.19.11.2958
    • (2007) Neural Comput , vol.19 , pp. 2958-3010
    • Muller, E.1    Buesing, L.2    Schemmel, J.3    Meier, K.4
  • 78
    • 84868154067 scopus 로고    scopus 로고
    • Coding and decoding with adapting neurons: A population approach to the peri-stimulus time histogram
    • Naud, R., and Gerstner, W. (2012). Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram. PLoS Comput. Biol. 8:e1002711. doi: 10.1371/journal.pcbi.1002711
    • (2012) PLoS Comput. Biol , vol.8
    • Naud, R.1    Gerstner, W.2
  • 79
    • 56449095252 scopus 로고    scopus 로고
    • Firing patterns in the adaptive exponential integrate-and-fire model
    • Naud, R., Marcille, N., Clopath, C., and Gerstner, W. (2008). Firing patterns in the adaptive exponential integrate-and-fire model. Biol. Cybern. 99, 335-347. doi: 10.1007/s00422-008-0264-7
    • (2008) Biol. Cybern , vol.99 , pp. 335-347
    • Naud, R.1    Marcille, N.2    Clopath, C.3    Gerstner, W.4
  • 80
    • 84880193048 scopus 로고    scopus 로고
    • Bifurcations of large networks of twodimensional integrate and fire neurons
    • Nicola, W., and Campbell, S. A. (2013a). Bifurcations of large networks of twodimensional integrate and fire neurons. J. Comput. Neurosci. 35, 87-108. doi: 10.1007/s10827-013-0442-z
    • (2013) J. Comput. Neurosci , vol.35 , pp. 87-108
    • Nicola, W.1    Campbell, S.A.2
  • 81
    • 84891504526 scopus 로고    scopus 로고
    • Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons
    • Nicola, W., and Campbell, S. A. (2013b). Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons. Front. Comput. Neurosci. 7:184. doi: 10.3389/fncom.2013.00184
    • (2013) Front. Comput. Neurosci , vol.7 , pp. 184
    • Nicola, W.1    Campbell, S.A.2
  • 82
    • 0036487070 scopus 로고    scopus 로고
    • Intrinsic physiological properties of cat retinal ganglion cells
    • O’Brien, B. J., Isayama, T., Richardson, R., and Berson, D. M. (2002). Intrinsic physiological properties of cat retinal ganglion cells. J. Physiol. 538, 787-802. doi: 10.1113/jphysiol.2001.013009
    • (2002) J. Physiol , vol.538 , pp. 787-802
    • O’brien, B.J.1    Isayama, T.2    Richardson, R.3    Berson, D.M.4
  • 83
    • 79959931689 scopus 로고    scopus 로고
    • Interspike interval distributions of spiking neurons driven by fluctuating inputs
    • Ostojic, S. (2011). Interspike interval distributions of spiking neurons driven by fluctuating inputs. J. Neurophysiol. 106, 361-373. doi: 10.1152/jn.00830.2010
    • (2011) J. Neurophysiol , vol.106 , pp. 361-373
    • Ostojic, S.1
  • 84
    • 0032975272 scopus 로고    scopus 로고
    • Multiple mechanisms of spike-frequency adaptation in motoneurones
    • Powers, R. K., Sawczuk, A., Musick, J. R., and Binder, M. D. (1999). Multiple mechanisms of spike-frequency adaptation in motoneurones. J. Physiol. Paris 93, 101-114. doi: 10.1016/S0928-4257(99)80141-7
    • (1999) J. Physiol. Paris , vol.93 , pp. 101-114
    • Powers, R.K.1    Sawczuk, A.2    Musick, J.R.3    Binder, M.D.4
  • 85
    • 3142740626 scopus 로고    scopus 로고
    • “Mean-field theory of irregularly spiking neuronal populations and working memory in recurrent cortical networks,”
    • ed J. Feng (London: CRC Press
    • Renart, A., Brunel, N., and Wang, X.-J. (2003). “Mean-field theory of irregularly spiking neuronal populations and working memory in recurrent cortical networks,” in Computational Neuroscience: A Comprehensive Approach, ed J. Feng (London: CRC Press), 431-490.
    • (2003) Computational Neuroscience: A Comprehensive Approach , pp. 431-490
    • Renart, A.1    Brunel, N.2    Wang, X.-J.3
  • 86
    • 33845992188 scopus 로고    scopus 로고
    • Mean-Driven and Fluctuation-Driven persistent activity in recurrent networks
    • Renart, A., Moreno-Bote, R., Wang, X., and Parga, N. (2006). Mean-Driven and Fluctuation-Driven persistent activity in recurrent networks. Neural Comput. 19, 1-46. doi: 10.1162/neco.2007.19.1.1
    • (2006) Neural Comput , vol.19 , pp. 1-46
    • Renart, A.1    Moreno-Bote, R.2    Wang, X.3    Parga, N.4
  • 88
    • 70349108710 scopus 로고    scopus 로고
    • Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents
    • Richardson, M. J. (2009). Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 80:021928. doi: 10.1103/PhysRevE.80.021928
    • (2009) Phys. Rev. E Stat. Nonlin. Soft Matter Phys , vol.80 , pp. 021928
    • Richardson, M.J.1
  • 89
    • 34548099438 scopus 로고    scopus 로고
    • Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductancebased synaptic drive
    • Richardson, M. J. E. (2007). Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductancebased synaptic drive. Phys. Rev. E 76:021919. doi: 10.1103/PhysRevE.76.021919
    • (2007) Phys. Rev. E , vol.76 , pp. 021919
    • Richardson, M.J.E.1
  • 91
    • 0029670122 scopus 로고    scopus 로고
    • + currents in neurones: Types, physiological roles and modulation
    • + currents in neurones: types, physiological roles and modulation. Trends Neurosci. 19, 150-154. doi: 10.1016/S01662236(96)80026-9
    • (1996) Trends Neurosci , vol.19 , pp. 150-154
    • Sah, P.1
  • 92
    • 0029122186 scopus 로고
    • Spatial profile of dendritic calcium transients evoked by action potentials in rat neocortical pyramidal neurones
    • Schiller, J., Helmchen, F., and Sakmann, B. (1995). Spatial profile of dendritic calcium transients evoked by action potentials in rat neocortical pyramidal neurones. J. Physiol. 487, 583-600.
    • (1995) J. Physiol , vol.487 , pp. 583-600
    • Schiller, J.1    Helmchen, F.2    Sakmann, B.3
  • 93
    • 0032525177 scopus 로고    scopus 로고
    • The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding
    • Shadlen, M. N., and Newsome, W. T. (1998). The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J. Neurosci. 18, 3870-3896.
    • (1998) J. Neurosci , vol.18 , pp. 3870-3896
    • Shadlen, M.N.1    Newsome, W.T.2
  • 94
    • 36149019489 scopus 로고
    • On the first passage time probability problem
    • Siegert, A. J. F. (1951). On the first passage time probability problem. Phys. Rev. 81, 617-623. doi: 10.1103/PhysRev.81.617
    • (1951) Phys. Rev , vol.81 , pp. 617-623
    • Siegert, A.J.F.1
  • 95
    • 0035924588 scopus 로고    scopus 로고
    • Rate, timing, and cooperativity jointly determine cortical synaptic plasticity
    • Sjöström, P. J., Turrigiano, G. G., and Nelson, S. B. (2001). Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149-1164. doi: 10.1016/S0896-6273(01)00542-6
    • (2001) Neuron , vol.32 , pp. 1149-1164
    • Sjöström, P.J.1    Turrigiano, G.G.2    Nelson, S.B.3
  • 96
    • 84889256063 scopus 로고    scopus 로고
    • A systems medicine research approach for studying alcohol addiction
    • Spanagel, R., Durstewitz, D., Hansson, A., Heinz, A., Kiefer, F., Köhr, G., et al. (2013). A systems medicine research approach for studying alcohol addiction. Addict. Biol. 18, 883-896. doi: 10.1111/adb.12109
    • (2013) Addict. Biol , vol.18 , pp. 883-896
    • Spanagel, R.1    Durstewitz, D.2    Hansson, A.3    Heinz, A.4    Kiefer, F.5    Köhr, G.6
  • 97
    • 0028903712 scopus 로고
    • Activity-dependent action potential invasion and calcium influx into hippocampal CA1 dendrites
    • Spruston, N., Schiller, Y., Stuart, G., and Sakmann, B. (1995). Activity-dependent action potential invasion and calcium influx into hippocampal CA1 dendrites. Science 268, 297-300. doi: 10.1126/science.7716524
    • (1995) Science , vol.268 , pp. 297-300
    • Spruston, N.1    Schiller, Y.2    Stuart, G.3    Sakmann, B.4
  • 98
    • 0035003185 scopus 로고    scopus 로고
    • Natural waking and sleep states: A view from inside neocortical neurons
    • Steriade, M., Timofeev, I., and Grenier, F. (2001). Natural waking and sleep states: a view from inside neocortical neurons. J. Neurophysiol. 85, 1969-1985.
    • (2001) J. Neurophysiol , vol.85 , pp. 1969-1985
    • Steriade, M.1    Timofeev, I.2    Grenier, F.3
  • 99
    • 5044238460 scopus 로고    scopus 로고
    • + channels: Molecular determinants and function of the SK family
    • + channels: molecular determinants and function of the SK family. Nat. Rev. Neurosci. 5, 758-770. doi: 10.1038/nrn1516
    • (2004) Nat. Rev. Neurosci , vol.5 , pp. 758-770
    • Stocker, M.1
  • 100
    • 0031574080 scopus 로고    scopus 로고
    • Action potential initiation and propagation in rat neocortical pyramidal neurons
    • Stuart, G., Schiller, J., and Sakmann, B. (1997). Action potential initiation and propagation in rat neocortical pyramidal neurons. J. Physiol. 505, 617-632. doi: 10.1111/j.1469-7793.1997.617ba.x
    • (1997) J. Physiol , vol.505 , pp. 617-632
    • Stuart, G.1    Schiller, J.2    Sakmann, B.3
  • 101
    • 0009839796 scopus 로고
    • On stochastic processes connected with certain physical recording apparatuses
    • Takács, L. (1955). On stochastic processes connected with certain physical recording apparatuses. ACTA Math. Acad. Sci. H. 6, 363-380. doi: 10.1007/BF02024395
    • (1955) ACTA Math. Acad. Sci. H , vol.6 , pp. 363-380
    • Takács, L.1
  • 102
    • 85088991346 scopus 로고    scopus 로고
    • Functional maps of neocortical local circuitry
    • Thomson, A. M., and Lamy, C. (2007). Functional maps of neocortical local circuitry. Front. Neurosci. 1:1. doi: 10.3389/neuro.01.1.1.002.2007
    • (2007) Front. Neurosci , vol.1 , pp. 1
    • Thomson, A.M.1    Lamy, C.2
  • 103
    • 0035852679 scopus 로고    scopus 로고
    • Disfacilitation and active inhibition in the neocortex during the natural Sleep-Wake cycle: An intracellular study
    • Timofeev, I., Grenier, F., and Steriade, M. (2001). Disfacilitation and active inhibition in the neocortex during the natural Sleep-Wake cycle: An intracellular study. Proc. Natl. Acad. Sci. U.S.A. 98, 1924-1929. doi: 10.1073/pnas.98.4.1924
    • (2001) Proc. Natl. Acad. Sci. U.S.A , vol.98 , pp. 1924-1929
    • Timofeev, I.1    Grenier, F.2    Steriade, M.3
  • 104
    • 49449110607 scopus 로고    scopus 로고
    • Bifurcation analysis of a general class of non-linear integrate and fire neurons
    • Touboul, J. (2008). Bifurcation analysis of a general class of non-linear integrate and fire neurons. SIAM J. Appl. Math. 68, 1045-1079. doi: 10.1137/070687268
    • (2008) SIAM J. Appl. Math , vol.68 , pp. 1045-1079
    • Touboul, J.1
  • 105
    • 56449131028 scopus 로고    scopus 로고
    • Dynamics and bifurcations of the adaptive exponential integrate-and-fire model
    • Touboul, J., and Brette, R. (2008). Dynamics and bifurcations of the adaptive exponential integrate-and-fire model. Biol. Cybern. 99, 319-334. doi: 10.1007/s00422-008-0267-4
    • (2008) Biol. Cybern , vol.99 , pp. 319-334
    • Touboul, J.1    Brette, R.2
  • 106
    • 70349239144 scopus 로고    scopus 로고
    • Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness
    • Toyoizumi, T., Rad, K. R., and Paninski, L. (2009). Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness. Neural Comput. 21, 1203-1243. doi: 10.1162/neco.2008.0408-757
    • (2009) Neural Comput , vol.21 , pp. 1203-1243
    • Toyoizumi, T.1    Rad, K.R.2    Paninski, L.3
  • 107
    • 20144369542 scopus 로고    scopus 로고
    • Single-Column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts
    • Traub, R. D., Contreras, D., Cunningham, M. O., Murray, H., LeBeau, F. E. N., Roopun, A., et al. (2005). Single-Column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. J. Neurophysiol. 93, 2194-2232. doi: 10.1152/jn.00983.2004
    • (2005) J. Neurophysiol , vol.93 , pp. 2194-2232
    • Traub, R.D.1    Contreras, D.2    Cunningham, M.O.3    Murray, H.4    Lebeau, F.E.N.5    Roopun, A.6
  • 108
    • 0024244042 scopus 로고
    • Large scale simulations of the hippocampus
    • Traub, R. D., Miles, R., and Wong, R. K. (1988). Large scale simulations of the hippocampus. IEEE Eng. Med. Biol. 7, 31-38. doi: 10.1109/51.20378
    • (1988) IEEE Eng. Med. Biol , vol.7 , pp. 31-38
    • Traub, R.D.1    Miles, R.2    Wong, R.K.3
  • 109
    • 36149037160 scopus 로고
    • Mean-field analysis of neuronal spike dynamics
    • Treves, A. (1993). Mean-field analysis of neuronal spike dynamics. Netw. Comput. Neural Syst. 4, 259-284. doi: 10.1088/0954-898X/4/3/002
    • (1993) Netw. Comput. Neural Syst , vol.4 , pp. 259-284
    • Treves, A.1
  • 110
    • 0031018015 scopus 로고    scopus 로고
    • The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability
    • Tsodyks, M. V., and Markram, H. (1997). The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc. Natl. Acad. Sci. U.S.A. 94, 719-723. doi: 10.1073/pnas.94.2.719
    • (1997) Proc. Natl. Acad. Sci. U.S.A , vol.94 , pp. 719-723
    • Tsodyks, M.V.1    Markram, H.2
  • 112
    • 0035345072 scopus 로고    scopus 로고
    • Patterns of synchrony in neural networks with spike adaptation
    • van Vreeswijk, C., and Hansel, D. (2001). Patterns of synchrony in neural networks with spike adaptation. Neural Comput. 13, 959-992. doi: 10.1162/08997660151134280
    • (2001) Neural Comput , vol.13 , pp. 959-992
    • van Vreeswijk, C.1    Hansel, D.2
  • 113
    • 0029835892 scopus 로고    scopus 로고
    • Chaos in neuronal networks with balanced excitatory and inhibitory activity
    • van Vreeswijk, C., and Sompolinsky, H. (1996). Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274, 1724-1726. doi: 10.1126/science.274.5293.1724
    • (1996) Science , vol.274 , pp. 1724-1726
    • van Vreeswijk, C.1    Sompolinsky, H.2
  • 115
    • 0033705948 scopus 로고    scopus 로고
    • Inhibition-based rhythms: Experimental and mathematical observations on network dynamics
    • Whittington, M., Traub, R., Kopell, N., Ermentrout, B., and Buhl, E. (2000). Inhibition-based rhythms: experimental and mathematical observations on network dynamics. Int. J. Psychophysiol. 38, 315-336. doi: 10.1016/S01678760(00)00173-2
    • (2000) Int. J. Psychophysiol , vol.38 , pp. 315-336
    • Whittington, M.1    Traub, R.2    Kopell, N.3    Ermentrout, B.4    Buhl, E.5
  • 116
    • 0026491094 scopus 로고
    • Muscarinic inhibition of m-current and a potassium leak conductance in neurones of the rat basolateral amygdala
    • Womble, M. D., and Moises, H. C. (1992). Muscarinic inhibition of m-current and a potassium leak conductance in neurones of the rat basolateral amygdala. J. Physiol. 457, 93-114.
    • (1992) J. Physiol , vol.457 , pp. 93-114
    • Womble, M.D.1    Moises, H.C.2
  • 117
    • 0032516707 scopus 로고    scopus 로고
    • Cholinergic switching within neocortical inhibitory networks
    • Xiang, Z., Huguenard, J. R., and Prince, D. A. (1998). Cholinergic switching within neocortical inhibitory networks. Science 281, 985-988. doi: 10.1126/sci-ence.281.5379.985
    • (1998) Science , vol.281 , pp. 985-988
    • Xiang, Z.1    Huguenard, J.R.2    Prince, D.A.3


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