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Volumn 7, Issue 1, 2011, Pages

From spiking neuron models to linear-nonlinear models

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROPHYSIOLOGY; LINEAR TRANSFORMATIONS; NEURONS;

EID: 79551566720     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1001056     Document Type: Article
Times cited : (189)

References (70)
  • 3
    • 12544253489 scopus 로고    scopus 로고
    • A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects
    • Truccolo W, Eden UT, Fellows MR, Donoghue JP, Brown EN (2005) A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. J Neurophysiol 93: 1074-89.
    • (2005) J Neurophysiol , vol.93 , pp. 1074-1089
    • Truccolo, W.1    Eden, U.T.2    Fellows, M.R.3    Donoghue, J.P.4    Brown, E.N.5
  • 4
    • 50049100348 scopus 로고    scopus 로고
    • Spatio-temporal correlations and visual signalling in a complete neuronal population
    • Pillow JW, Shlens J, Paninski L, Sher A, Litke AM, et al. (2008) Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature 454: 995-999.
    • (2008) Nature , vol.454 , pp. 995-999
    • Pillow, J.W.1    Shlens, J.2    Paninski, L.3    Sher, A.4    Litke, A.M.5
  • 5
    • 0032521364 scopus 로고    scopus 로고
    • Refractoriness and neural precision
    • Berry MJ, Meister M (1998) Refractoriness and neural precision. J Neurosci 18: 2200-11.
    • (1998) J Neurosci , vol.18 , pp. 2200-2211
    • Berry, M.J.1    Meister, M.2
  • 6
    • 28044458279 scopus 로고    scopus 로고
    • Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model
    • Pillow JW (2005) Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model. J Neurosci 25: 11003-11013.
    • (2005) J Neurosci , vol.25 , pp. 11003-11013
    • Pillow, J.W.1
  • 7
    • 79551558705 scopus 로고    scopus 로고
    • Spiking Neuron Models Cambridge University Press
    • Gerstner W, Kistler W (2002) Spiking Neuron Models Cambridge University Press.
    • (2002)
    • Gerstner, W.1    Kistler, W.2
  • 8
    • 0015260274 scopus 로고
    • Excitatory and inhibitory interactions in localized populations of model neurons
    • Wilson HR, Cowan JD (1972) Excitatory and inhibitory interactions in localized populations of model neurons. Biophys J 12: 1-24.
    • (1972) Biophys J , vol.12 , pp. 1-24
    • Wilson, H.R.1    Cowan, J.D.2
  • 9
    • 0000650934 scopus 로고
    • Reduction of conductance-based models with slow synapses to neural nets
    • Ermentrout B (1994) Reduction of conductance-based models with slow synapses to neural nets. Neural Comput 6: 679-695.
    • (1994) Neural Comput , vol.6 , pp. 679-695
    • Ermentrout, B.1
  • 10
    • 0000788367 scopus 로고
    • Time structure of the activity in neural network models
    • Gerstner W (1995) Time structure of the activity in neural network models. Phys Rev E Stat Nonlin Soft Matter Phys 51: 738-758.
    • (1995) Phys Rev E Stat Nonlin Soft Matter Phys , vol.51 , pp. 738-758
    • Gerstner, W.1
  • 11
    • 0033630628 scopus 로고    scopus 로고
    • Population dynamics of spiking neurons: Fast transients, asynchronous states, and locking
    • Gerstner W (2000) Population dynamics of spiking neurons: fast transients, asynchronous states, and locking. Neural Comput 12: 43-89.
    • (2000) Neural Comput , vol.12 , pp. 43-89
    • Gerstner, W.1
  • 12
    • 6644226801 scopus 로고    scopus 로고
    • Effects of synaptic noise and filtering on the frequency response of spiking neurons
    • Brunel N, Chance F, Fourcaud N, Abbott L (2001) Effects of synaptic noise and filtering on the frequency response of spiking neurons. Phys Rev Lett 86: 2186-2189.
    • (2001) Phys Rev Lett , vol.86 , pp. 2186-2189
    • Brunel, N.1    Chance, F.2    Fourcaud, N.3    Abbott, L.4
  • 14
    • 0041324844 scopus 로고    scopus 로고
    • Rate models for conductance-based cortical neuronal networks
    • Shriki O, Hansel D, Sompolinsky H (2003) Rate models for conductance-based cortical neuronal networks. Neural Comput 15: 1809-41.
    • (2003) Neural Comput , vol.15 , pp. 1809-1841
    • Shriki, O.1    Hansel, D.2    Sompolinsky, H.3
  • 15
    • 4344670177 scopus 로고    scopus 로고
    • Minimal models of adapted neuronal response to in vivo-like input currents
    • La Camera G, Rauch A, Lüscher HR, Senn W, Fusi S (2004) Minimal models of adapted neuronal response to in vivo-like input currents. Neural Comput 16: 2101-24.
    • (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
  • 16
    • 33646730151 scopus 로고    scopus 로고
    • From spiking neurons to rate models: A cascade model as an approximation to spiking neuron models with refractoriness
    • Aviel Y, Gerstner W (2006) From spiking neurons to rate models: A cascade model as an approximation to spiking neuron models with refractoriness. Phys Rev E Stat Nonlin Soft Matter Phys 73: 1-10.
    • (2006) Phys Rev E Stat Nonlin Soft Matter Phys , vol.73 , pp. 1-10
    • Aviel, Y.1    Gerstner, W.2
  • 17
    • 79551565163 scopus 로고    scopus 로고
    • Firing rate dynamics in transitions between synchrony and asynchrony
    • Chicago, IL: Society for Neuroscience
    • Schaffer ES, Abbott LF (2009) Firing rate dynamics in transitions between synchrony and asynchrony. Program No. 321.22. 2009 Neuroscience Meeting Planner. Chicago, IL: Society for Neuroscience.
    • (2009) Program No. 321.22. 2009 Neuroscience Meeting Planner
    • Schaffer, E.S.1    Abbott, L.F.2
  • 20
    • 0026533782 scopus 로고
    • White-noise analysis in neurophysiology
    • Sakai HM (1992) White-noise analysis in neurophysiology. Physiol Rev 72: 491-505.
    • (1992) Physiol Rev , vol.72 , pp. 491-505
    • Sakai, H.M.1
  • 21
    • 0347694858 scopus 로고    scopus 로고
    • How spike generation mechanisms determine the neuronal response to fluctuating inputs
    • Fourcaud-Trocmé N, Hansel D, van Vreeswijk C, Brunel N (2003) How spike generation mechanisms determine the neuronal response to fluctuating inputs. J Neurosci 23: 11628-40.
    • (2003) J Neurosci , vol.23 , pp. 11628-11640
    • Fourcaud-Trocmé, N.1    Hansel, D.2    van Vreeswijk, C.3    Brunel, N.4
  • 22
    • 54149099557 scopus 로고    scopus 로고
    • The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro
    • Kondgen H, Geisler C, Fusi S, Wang XJ, Luscher HR, et al. (2007) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18: 2086-2097.
    • (2007) Cereb Cortex , vol.18 , pp. 2086-2097
    • Kondgen, H.1    Geisler, C.2    Fusi, S.3    Wang, X.J.4    Luscher, H.R.5
  • 23
    • 59649123647 scopus 로고    scopus 로고
    • Dynamical response properties of neocortical neuron ensembles: Multiplicative versus additive noise
    • Boucsein C, Tetzlaff T, Meier R, Aertsen A, Naundorf B (2009) Dynamical response properties of neocortical neuron ensembles: multiplicative versus additive noise. J Neurosci 29: 1006-10.
    • (2009) J Neurosci , vol.29 , pp. 1006-1010
    • Boucsein, C.1    Tetzlaff, T.2    Meier, R.3    Aertsen, A.4    Naundorf, B.5
  • 24
    • 0033210816 scopus 로고    scopus 로고
    • Fast global oscillations in networks of integrate-andfire neurons with low firing rates
    • Brunel N, Hakim V (1999) Fast global oscillations in networks of integrate-andfire neurons with low firing rates. Neural Comput 11: 1621-1671.
    • (1999) Neural Comput , vol.11 , pp. 1621-1671
    • Brunel, N.1    Hakim, V.2
  • 25
    • 0035794252 scopus 로고    scopus 로고
    • Transmission of noise coded versus additive signals through a neuronal ensemble
    • Lindner B, Schimansky-Geier L (2001) Transmission of noise coded versus additive signals through a neuronal ensemble. Phys Rev Lett 86: 2934-7.
    • (2001) Phys Rev Lett , vol.86 , pp. 2934-2937
    • Lindner, B.1    Schimansky-Geier, L.2
  • 26
    • 34548099438 scopus 로고    scopus 로고
    • Firing-rate response of linear and nonlinear integrateand-fire neurons to modulated current-based and conductance-based synaptic drive
    • Richardson MJE (2007) Firing-rate response of linear and nonlinear integrateand-fire neurons to modulated current-based and conductance-based synaptic drive. Phys Rev E Stat Nonlin Soft Matter Phys 76: 15.
    • (2007) Phys Rev E Stat Nonlin Soft Matter Phys , vol.76 , pp. 15
    • Richardson, M.J.E.1
  • 27
    • 36149019489 scopus 로고
    • On the 1st passage time probability problem
    • Siegert A (1951) On the 1st passage time probability problem. Phys Rev 81: 617-623.
    • (1951) Phys Rev , vol.81 , pp. 617-623
    • Siegert, A.1
  • 28
    • 0001127901 scopus 로고
    • Recherches quantitatives sur l'excitation electrique des nerfs traitee comme une polarisation
    • Lapicque L (1907) Recherches quantitatives sur l'excitation electrique des nerfs traitee comme une polarisation. J Physiol Pathol Gen 9: 620.
    • (1907) J Physiol Pathol Gen , vol.9 , pp. 620
    • Lapicque, L.1
  • 29
    • 0141565240 scopus 로고    scopus 로고
    • Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents
    • Rauch A, La Camera G, Luscher HR, Senn W, Fusi S (2003) Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents. J Neurophysiol 90: 1598-612.
    • (2003) J Neurophysiol , vol.90 , pp. 1598-1612
    • Rauch, A.1    la Camera, G.2    Luscher, H.R.3    Senn, W.4    Fusi, S.5
  • 31
    • 33745712258 scopus 로고    scopus 로고
    • A review of the integrate-and-fire neuron model: I. homogeneous synaptic input
    • Burkitt AN (2006) A review of the integrate-and-fire neuron model: I. homogeneous synaptic input. Biol Cybern 95: 1-19.
    • (2006) Biol Cybern , vol.95 , pp. 1-19
    • Burkitt, A.N.1
  • 32
    • 33745730999 scopus 로고    scopus 로고
    • A review of the integrate-and-fire neuron model: Ii. inhomogeneous synaptic input and network properties
    • Burkitt AN (2006) A review of the integrate-and-fire neuron model: Ii. inhomogeneous synaptic input and network properties. Biol Cybern 95: 97-112.
    • (2006) Biol Cybern , vol.95 , pp. 97-112
    • Burkitt, A.N.1
  • 33
    • 69049105412 scopus 로고    scopus 로고
    • How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains
    • Ostojic S, Brunel N, Hakim V (2009) How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains. J Neurosci 29: 10234-10253.
    • (2009) J Neurosci , vol.29 , pp. 10234-10253
    • Ostojic, S.1    Brunel, N.2    Hakim, V.3
  • 34
    • 33750583238 scopus 로고    scopus 로고
    • The spike-triggered average of the integrate-and-fire cell driven by Gaussian white noise
    • Paninski L (2006) The spike-triggered average of the integrate-and-fire cell driven by Gaussian white noise. Neural Comput 18: 2592-616.
    • (2006) Neural Comput , vol.18 , pp. 2592-2616
    • Paninski, L.1
  • 35
    • 48349147782 scopus 로고    scopus 로고
    • Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive. Physical review E
    • Badel L, Gerstner W, Richardson MJE (2008) Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive. Physical review E, Statistical, nonlinear, and soft matter physics 78: 011914.
    • (2008) Statistical, Nonlinear, and Soft Matter Physics , vol.78 , pp. 011914
    • Badel, L.1    Gerstner, W.2    Richardson, M.J.E.3
  • 36
    • 0037104631 scopus 로고    scopus 로고
    • Gain modulation from background synaptic input
    • Chance FS, Abbott LF, Reyes AD (2002) Gain modulation from background synaptic input. Neuron 35: 773-82.
    • (2002) Neuron , vol.35 , pp. 773-782
    • Chance, F.S.1    Abbott, L.F.2    Reyes, A.D.3
  • 37
    • 26844542935 scopus 로고    scopus 로고
    • Drivers and modulators from push-pull and balanced synaptic input
    • Abbott LF, Chance FS (2005) Drivers and modulators from push-pull and balanced synaptic input. Prog Brain Res 149: 147-55.
    • (2005) Prog Brain Res , vol.149 , pp. 147-155
    • Abbott, L.F.1    Chance, F.S.2
  • 38
    • 0035680305 scopus 로고    scopus 로고
    • Noise and the psth response to current transients: I. general theory and application to the integrate-and-fire neuron
    • Herrmann A, Gerstner W (2001) Noise and the psth response to current transients: I. general theory and application to the integrate-and-fire neuron. J Comput Neurosci 11: 135-51.
    • (2001) J Comput Neurosci , vol.11 , pp. 135-151
    • Herrmann, A.1    Gerstner, W.2
  • 39
    • 39149096545 scopus 로고    scopus 로고
    • Dynamic i-v curves are reliable predictors of naturalistic pyramidal-neuron voltage traces
    • Badel L, Lefort S, Brette R, Petersen CCH, Gerstner W, et al. (2008) Dynamic i-v curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. J Neurophysiol 99: 656-666.
    • (2008) J Neurophysiol , vol.99 , pp. 656-666
    • Badel, L.1    Lefort, S.2    Brette, R.3    Petersen, C.C.H.4    Gerstner, W.5
  • 40
    • 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 TK, Petersen CCH, Gerstner W, et al. (2008) Extracting non-linear integrate-and-fire models from experimental data using dynamic i-v curves. Biol Cybern 99: 361-370.
    • (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
  • 42
    • 0029836487 scopus 로고    scopus 로고
    • Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model
    • Wang XJ, Buzsáki G (1996) Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. J Neurosci 16: 6402-13.
    • (1996) J Neurosci , vol.16 , pp. 6402-6413
    • Wang, X.J.1    Buzsáki, G.2
  • 43
    • 19744369589 scopus 로고    scopus 로고
    • Robustness of the noise-induced phase synchronization in a general class of limit cycle oscillators
    • Teramae JN, Tanaka D (2004) Robustness of the noise-induced phase synchronization in a general class of limit cycle oscillators. Phys Rev Lett 93: 204103.
    • (2004) Phys Rev Lett , vol.93 , pp. 204103
    • Teramae, J.N.1    Tanaka, D.2
  • 44
    • 0036716145 scopus 로고    scopus 로고
    • Dynamics of the firing probability of noisy integrate-and-fire neurons
    • Fourcaud N, Brunel N (2002) Dynamics of the firing probability of noisy integrate-and-fire neurons. Neural Comput 14: 2057-110.
    • (2002) Neural Comput , vol.14 , pp. 2057-2110
    • Fourcaud, N.1    Brunel, N.2
  • 45
    • 36149028967 scopus 로고
    • Quantitative study of attractor neural network retrieving at low spike rates.1. substrate spikes, rates and neuronal gain
    • Amit D, Tsodyks M (1991) Quantitative study of attractor neural network retrieving at low spike rates.1. substrate spikes, rates and neuronal gain. Network 2: 259-273.
    • (1991) Network , vol.2 , pp. 259-273
    • Amit, D.1    Tsodyks, M.2
  • 46
    • 0001744909 scopus 로고
    • Activity patterns of a slow synapse network predicted by explicitly averaging spike dynamics
    • Rinzel J, Frankel P (1992) Activity patterns of a slow synapse network predicted by explicitly averaging spike dynamics. Neural Comput 4: 534-545.
    • (1992) Neural Comput , vol.4 , pp. 534-545
    • Rinzel, J.1    Frankel, P.2
  • 47
  • 48
    • 77953017373 scopus 로고    scopus 로고
    • Feature selection in simple neurons: How coding depends on spiking dynamics
    • Famulare M, Fairhall A (2010) Feature selection in simple neurons: how coding depends on spiking dynamics. Neural Comput 22: 581-98.
    • (2010) Neural Comput , vol.22 , pp. 581-598
    • Famulare, M.1    Fairhall, A.2
  • 49
    • 0043180466 scopus 로고    scopus 로고
    • Computation in a Single Neuron: Hodgkin and Huxley Revisited
    • Agüera y Arcas B, Fairhall AL, Bialek W (2003) Computation in a Single Neuron: Hodgkin and Huxley Revisited. Neural Comput 15: 1715-49.
    • (2003) Neural Comput , vol.15 , pp. 1715-1749
    • Agüera1    Arcas, B.2    Fairhall, A.L.3    Bialek, W.4
  • 50
    • 36849093520 scopus 로고    scopus 로고
    • Single neuron computation: From dynamical system to feature detector
    • Hong S, y Arcas BA, Fairhall AL (2007) Single neuron computation: from dynamical system to feature detector. Neural Comput 19: 3133-72.
    • (2007) Neural Comput , vol.19 , pp. 3133-3172
    • Hong, S.1    Arcas, B.A.2    Fairhall, A.L.3
  • 52
    • 0035212197 scopus 로고    scopus 로고
    • Variability and information in a neural code of the cat lateral geniculate nucleus
    • Liu RC, Tzonev S, Rebrik S, Miller KD (2001) Variability and information in a neural code of the cat lateral geniculate nucleus. J Neurophysiol 86: 2789-806.
    • (2001) J Neurophysiol , vol.86 , pp. 2789-2806
    • Liu, R.C.1    Tzonev, S.2    Rebrik, S.3    Miller, K.D.4
  • 53
    • 3142674925 scopus 로고    scopus 로고
    • Precision of spike trains in primate retinal ganglion cells
    • Uzzell VJ, Chichilnisky EJ (2004) Precision of spike trains in primate retinal ganglion cells. J Neurophysiol 92: 780-9.
    • (2004) J Neurophysiol , vol.92 , pp. 780-789
    • Uzzell, V.J.1    Chichilnisky, E.J.2
  • 54
    • 0034972776 scopus 로고    scopus 로고
    • Predicting every spike: A model for the responses of visual neurons
    • Keat J, Reinagel P, Reid RC, Meister M (2001) Predicting every spike: a model for the responses of visual neurons. Neuron 30: 803-17.
    • (2001) Neuron , vol.30 , pp. 803-817
    • Keat, J.1    Reinagel, P.2    Reid, R.C.3    Meister, M.4
  • 55
    • 13844255550 scopus 로고    scopus 로고
    • Contributions of the input signal and prior activation history to the discharge behaviour of rat motoneurones
    • Powers RK, Dai Y, Bell BM, Percival DB, Binder MD (2005) Contributions of the input signal and prior activation history to the discharge behaviour of rat motoneurones. J Physiol 562: 707-24.
    • (2005) J Physiol , vol.562 , pp. 707-724
    • Powers, R.K.1    Dai, Y.2    Bell, B.M.3    Percival, D.B.4    Binder, M.D.5
  • 57
    • 33745833056 scopus 로고    scopus 로고
    • Predicting spike timing of neocortical pyramidal neurons by simple threshold models
    • Jolivet R, Rauch A, Lüscher HR, Gerstner W (2006) Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J Comput Neurosci 21: 35-49.
    • (2006) J Comput Neurosci , vol.21 , pp. 35-49
    • Jolivet, R.1    Rauch, A.2    Lüscher, H.R.3    Gerstner, W.4
  • 58
    • 70349239144 scopus 로고    scopus 로고
    • Mean-field approximations for coupled populations of generalized linear model spiking neurons with markov refractoriness
    • Toyoizumi T, Rad KR, Paninski L (2009) Mean-field approximations for coupled populations of generalized linear model spiking neurons with markov refractoriness. Neural Comput 21: 1203-43.
    • (2009) Neural Comput , vol.21 , pp. 1203-1243
    • Toyoizumi, T.1    Rad, K.R.2    Paninski, L.3
  • 59
    • 0017082266 scopus 로고
    • Spike initiation by transmembrane current: A white-noise analysis
    • Bryant HL, Segundo JP (1976) Spike initiation by transmembrane current: a white-noise analysis. J Physiol 260: 279-314.
    • (1976) J Physiol , vol.260 , pp. 279-314
    • Bryant, H.L.1    Segundo, J.P.2
  • 60
    • 0029030249 scopus 로고
    • Reliability of spike timing in neocortical neurons
    • Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268: 1503-6.
    • (1995) Science , vol.268 , pp. 1503-1506
    • Mainen, Z.F.1    Sejnowski, T.J.2
  • 61
    • 0030721539 scopus 로고    scopus 로고
    • Functional identification of the input-output transforms of motoneurones in the rat and cat
    • Poliakov AV, Powers RK, Binder MD (1997) Functional identification of the input-output transforms of motoneurones in the rat and cat. J Physiol 504(Pt 2): 401-24.
    • (1997) J Physiol , vol.504 , Issue.PART 2 , pp. 401-424
    • Poliakov, A.V.1    Powers, R.K.2    Binder, M.D.3
  • 62
    • 0033050316 scopus 로고    scopus 로고
    • Functional identification of the input-output transforms of mammalian motoneurones
    • Binder MD, Poliakov AV, Powers RK (1999) Functional identification of the input-output transforms of mammalian motoneurones. J Physiol Paris 93: 29-42.
    • (1999) J Physiol Paris , vol.93 , pp. 29-42
    • Binder, M.D.1    Poliakov, A.V.2    Powers, R.K.3
  • 63
    • 27344433674 scopus 로고    scopus 로고
    • Two-dimensional time coding in the auditory brainstem
    • Slee SJ, Higgs MH, Fairhall AL, Spain WJ (2005) Two-dimensional time coding in the auditory brainstem. J Neurosci 25: 9978-88.
    • (2005) J Neurosci , vol.25 , pp. 9978-9988
    • Slee, S.J.1    Higgs, M.H.2    Fairhall, A.L.3    Spain, W.J.4
  • 64
    • 0034623811 scopus 로고    scopus 로고
    • The contribution of noise to contrast invariance of orientation tuning in cat visual cortex
    • 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.
    • (2000) Science , vol.290 , pp. 1968-1972
    • Anderson, J.S.1    Lampl, I.2    Gillespie, D.C.3    Ferster, D.4
  • 65
    • 0035834798 scopus 로고    scopus 로고
    • Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons
    • Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ (2001) Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107: 13-24.
    • (2001) Neuroscience , vol.107 , pp. 13-24
    • Destexhe, A.1    Rudolph, M.2    Fellous, J.M.3    Sejnowski, T.J.4
  • 66
    • 27144498986 scopus 로고    scopus 로고
    • Adaptive exponential integrate-and-fire model as an effective description of neuronal activity
    • Brette R, Gerstner W (2005) Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. J Neurophysiol 94: 3637-42.
    • (2005) J Neurophysiol , vol.94 , pp. 3637-3642
    • Brette, R.1    Gerstner, W.2
  • 67
    • 33751547740 scopus 로고    scopus 로고
    • Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons
    • La Camera G, Rauch A, Thurbon D, Luscher HR, Senn W, et al. (2006) Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons. J Neurophysiol 96: 3448-3464.
    • (2006) J Neurophysiol , vol.96 , pp. 3448-3464
    • la Camera, G.1    Rauch, A.2    Thurbon, D.3    Luscher, H.R.4    Senn, W.5
  • 68
    • 42749098503 scopus 로고    scopus 로고
    • Effects of synaptic conductance on the voltage distribution and firing rate of spiking neurons
    • Richardson MJE (2004) Effects of synaptic conductance on the voltage distribution and firing rate of spiking neurons. Phys Rev E 69: 8.
    • (2004) Phys Rev E , vol.69 , pp. 8
    • Richardson, M.J.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.