메뉴 건너뛰기




Volumn 8, Issue 8, 2012, Pages

Decorrelation of Neural-Network Activity by Inhibitory Feedback

Author keywords

[No Author keywords available]

Indexed keywords

FEEDBACK; LINEAR NETWORKS; POPULATION STATISTICS; RECURRENT NEURAL NETWORKS;

EID: 84866137856     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002596     Document Type: Article
Times cited : (161)

References (87)
  • 1
    • 34547653865 scopus 로고    scopus 로고
    • Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing
    • Tripp B, Eliasmith C, (2007) Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing. Cereb Cortex 17: 1830-1840.
    • (2007) Cereb Cortex , vol.17 , pp. 1830-1840
    • Tripp, B.1    Eliasmith, C.2
  • 2
    • 0028290996 scopus 로고
    • Correlated neuronal discharge rate and its implications for psychophysical performance
    • Zohary E, Shadlen MN, Newsome WT, (1994) Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370: 140-143.
    • (1994) Nature , vol.370 , pp. 140-143
    • Zohary, E.1    Shadlen, M.N.2    Newsome, W.T.3
  • 3
    • 0032525177 scopus 로고    scopus 로고
    • The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding
    • Shadlen MN, Newsome WT, (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
  • 4
    • 0035432365 scopus 로고    scopus 로고
    • Correlated neuronal activity and the ow of neural information
    • Salinas E, Sejnowski TJ, (2001) Correlated neuronal activity and the ow of neural information. Nat Rev Neurosci 2: 539-550.
    • (2001) Nat Rev Neurosci , vol.2 , pp. 539-550
    • Salinas, E.1    Sejnowski, T.J.2
  • 5
    • 0003708920 scopus 로고
    • Internal report 81-2, Department of Neurobiology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
    • von der Malsburg C (1981) The correlation theory of brain function. Internal report 81-2, Department of Neurobiology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany.
    • (1981) The correlation theory of brain function
    • von der Malsburg, C.1
  • 8
    • 0033518170 scopus 로고    scopus 로고
    • Stable propagation of synchronous spiking in cortical neural networks
    • Diesmann M, Gewaltig MO, Aertsen A, (1999) Stable propagation of synchronous spiking in cortical neural networks. Nature 402: 529-533.
    • (1999) Nature , vol.402 , pp. 529-533
    • Diesmann, M.1    Gewaltig, M.O.2    Aertsen, A.3
  • 9
    • 2542488587 scopus 로고    scopus 로고
    • Consequences of realistic network size on the stability of embedded synfire chains
    • Tetzlaff T, Morrison A, Geisel T, Diesmann M, (2004) Consequences of realistic network size on the stability of embedded synfire chains. Neurocomputing 58-60: 117-121.
    • (2004) Neurocomputing , vol.58-60 , pp. 117-121
    • Tetzlaff, T.1    Morrison, A.2    Geisel, T.3    Diesmann, M.4
  • 11
    • 0029835892 scopus 로고    scopus 로고
    • Chaos in neuronal networks with balanced excitatory and inhibitory activity
    • van Vreeswijk C, Sompolinsky H, (1996) Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274: 1724-1726.
    • (1996) Science , vol.274 , pp. 1724-1726
    • van Vreeswijk, C.1    Sompolinsky, H.2
  • 12
    • 0034006515 scopus 로고    scopus 로고
    • Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons
    • Brunel N, (2000) Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J Comput Neurosci 8: 183-208.
    • (2000) J Comput Neurosci , vol.8 , pp. 183-208
    • Brunel, N.1
  • 13
    • 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
  • 14
    • 51349139658 scopus 로고    scopus 로고
    • Dependence of neuronal correlations on filter characteristics and marginal spike-train statistics
    • Tetzlaff T, Rotter S, Stark E, Abeles M, Aertsen A, et al. (2008) Dependence of neuronal correlations on filter characteristics and marginal spike-train statistics. Neural Comput 20: 2133-2184.
    • (2008) Neural Comput , vol.20 , pp. 2133-2184
    • Tetzlaff, T.1    Rotter, S.2    Stark, E.3    Abeles, M.4    Aertsen, A.5
  • 16
    • 77649294393 scopus 로고    scopus 로고
    • Cross-correlations in high-conductance states of a model cortical network
    • Hertz J, (2010) Cross-correlations in high-conductance states of a model cortical network. Neural Comput 22: 427-447.
    • (2010) Neural Comput , vol.22 , pp. 427-447
    • Hertz, J.1
  • 18
    • 0035458347 scopus 로고    scopus 로고
    • Correlation between uncoupled conductance-based integrate-and-fire neurons due to common and synchronous presynaptic firing
    • Stroeve S, Gielen S, (2001) Correlation between uncoupled conductance-based integrate-and-fire neurons due to common and synchronous presynaptic firing. Neural Comput 13: 2005-2029.
    • (2001) Neural Comput , vol.13 , pp. 2005-2029
    • Stroeve, S.1    Gielen, S.2
  • 19
    • 0037706879 scopus 로고    scopus 로고
    • The spread of rate and correlation in stationary cortical networks
    • Tetzlaff T, Buschermöhle M, Geisel T, Diesmann M, (2003) The spread of rate and correlation in stationary cortical networks. Neurocomputing 52-54: 949-954.
    • (2003) Neurocomputing , vol.52-54 , pp. 949-954
    • Tetzlaff, T.1    Buschermöhle, M.2    Geisel, T.3    Diesmann, M.4
  • 20
    • 32644485094 scopus 로고    scopus 로고
    • Auto- and crosscorrelograms for the spike response of leaky integrate-and-fire neurons with slow synapses
    • Moreno-Bote R, Parga N, (2006) Auto- and crosscorrelograms for the spike response of leaky integrate-and-fire neurons with slow synapses. Phys Rev Lett 96: 028101.
    • (2006) Phys Rev Lett , vol.96 , pp. 028101
    • Moreno-Bote, R.1    Parga, N.2
  • 21
    • 34547928124 scopus 로고    scopus 로고
    • Correlation between neural spike trains increases with firing rate
    • De la Rocha J, Doiron B, Shea-Brown E, Kresimir J, Reyes A, (2007) Correlation between neural spike trains increases with firing rate. Nature 448: 802-807.
    • (2007) Nature , vol.448 , pp. 802-807
    • de la Rocha, J.1    Doiron, B.2    Shea-Brown, E.3    Kresimir, J.4    Reyes, A.5
  • 22
    • 79958262262 scopus 로고    scopus 로고
    • Mechanisms that modulate the transfer of spiking correlations
    • Rosenbaum R, Josic K, (2011) Mechanisms that modulate the transfer of spiking correlations. Neural Comput 23: 1261-1305.
    • (2011) Neural Comput , vol.23 , pp. 1261-1305
    • Rosenbaum, R.1    Josic, K.2
  • 23
    • 36849043589 scopus 로고    scopus 로고
    • Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation
    • Battaglia D, Brunel N, Hansel D, (2007) Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation. Phys Rev Lett 99: 238106.
    • (2007) Phys Rev Lett , vol.99 , pp. 238106
    • Battaglia, D.1    Brunel, N.2    Hansel, D.3
  • 24
    • 78650812064 scopus 로고    scopus 로고
    • Dynamical entropy production in spiking neuron networks in the balanced state
    • Monteforte M, Wolf F, (2010) Dynamical entropy production in spiking neuron networks in the balanced state. Phys Rev Lett 105doi: 268104.
    • (2010) Phys Rev Lett , vol.105
    • Monteforte, M.1    Wolf, F.2
  • 26
    • 33846543881 scopus 로고    scopus 로고
    • Edge of chaos and prediction of computational performance for neural circuit models
    • Legenstein R, Maass W, (2007) Edge of chaos and prediction of computational performance for neural circuit models. Neural Netw 20: 323-334.
    • (2007) Neural Netw , vol.20 , pp. 323-334
    • Legenstein, R.1    Maass, W.2
  • 27
    • 38849132055 scopus 로고    scopus 로고
    • Stable irregular dynamics in complex neural networks
    • Jahnke S, Memmesheimer R, Timme M, (2008) Stable irregular dynamics in complex neural networks. Phys Rev Lett 100: 048102.
    • (2008) Phys Rev Lett , vol.100 , pp. 048102
    • Jahnke, S.1    Memmesheimer, R.2    Timme, M.3
  • 28
    • 85080358779 scopus 로고    scopus 로고
    • Beyond the edge: Amplification and temporal integration by recurrent networks in the chaotic regime
    • Toyoizumi T, Abbott LF, (2010) Beyond the edge: Amplification and temporal integration by recurrent networks in the chaotic regime. Front Neurosci doi: 10.3389/conf.fnins.2010.03.00155.
    • (2010) Front Neurosci
    • Toyoizumi, T.1    Abbott, L.F.2
  • 29
    • 33748426952 scopus 로고    scopus 로고
    • Desynchronization in diluted neural networks
    • Zillmer R, Livi R, Politi A, Torcini A, (2006) Desynchronization in diluted neural networks. Phys Rev E 74: 036203.
    • (2006) Phys Rev E , vol.74 , pp. 036203
    • Zillmer, R.1    Livi, R.2    Politi, A.3    Torcini, A.4
  • 30
    • 0037877795 scopus 로고
    • Theory of correlations in stochastic neural networks
    • Ginzburg I, Sompolinsky H, (1994) Theory of correlations in stochastic neural networks. Phys Rev E 50: 3171-3191.
    • (1994) Phys Rev E , vol.50 , pp. 3171-3191
    • Ginzburg, I.1    Sompolinsky, H.2
  • 31
    • 0033210816 scopus 로고    scopus 로고
    • Fast global oscillations in networks of integrate-and-_re neurons with low firing rates
    • Brunel N, Hakim V, (1999) Fast global oscillations in networks of integrate-and-_re neurons with low firing rates. Neural Comput 11: 1621-1671.
    • (1999) Neural Comput , vol.11 , pp. 1621-1671
    • Brunel, N.1    Hakim, V.2
  • 32
    • 80052025971 scopus 로고    scopus 로고
    • Cortical state and attention
    • Harris KD, Thiele A, (2011) Cortical state and attention. Nat Rev Neurosci 12: 509-523.
    • (2011) Nat Rev Neurosci , vol.12 , pp. 509-523
    • Harris, K.D.1    Thiele, A.2
  • 33
    • 78049437495 scopus 로고    scopus 로고
    • Instantaneous non-linear processing by pulsecoupled threshold units
    • Helias M, Deger M, Rotter S, Diesmann M, (2010) Instantaneous non-linear processing by pulsecoupled threshold units. PLoS Comput Biol 6: e1000929.
    • (2010) PLoS Comput Biol , vol.6
    • Helias, M.1    Deger, M.2    Rotter, S.3    Diesmann, M.4
  • 34
    • 77958128002 scopus 로고    scopus 로고
    • Firing-rate response of a neuron receiving excitatory and inhibitory synaptic shot noise
    • Richardson MJE, Swarbrick R, (2010) Firing-rate response of a neuron receiving excitatory and inhibitory synaptic shot noise. Phys Rev Lett 105: 178102.
    • (2010) Phys Rev Lett , vol.105 , pp. 178102
    • Richardson, M.J.E.1    Swarbrick, R.2
  • 35
    • 0347694858 scopus 로고    scopus 로고
    • How spike generation mechanisms determine the neuronal response to uctuating inputs
    • Brunel
    • Fourcaud-Trocmé N, Hansel D, van Vreeswijk C, (2003) Brunel (2003) How spike generation mechanisms determine the neuronal response to uctuating 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
  • 36
    • 18144427154 scopus 로고    scopus 로고
    • Action potential onset dynamics and the response speed of neuronal populations
    • Naundorf B, Geisel T, Wolf F, (2005) Action potential onset dynamics and the response speed of neuronal populations. J Comput Neurosci 18: 297-309.
    • (2005) J Comput Neurosci , vol.18 , pp. 297-309
    • Naundorf, B.1    Geisel, T.2    Wolf, F.3
  • 37
    • 6644226801 scopus 로고    scopus 로고
    • Effects of synaptic noise and filtering on the frequency response of spiking neurons
    • Brunel N, Chance FS, Fourcaud N, Abbott LF, (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.S.2    Fourcaud, N.3    Abbott, L.F.4
  • 38
    • 80052031291 scopus 로고    scopus 로고
    • Rate dynamics of leaky integrate-and-fire neurons with strong synapses
    • Nordlie E, Tetzlaff T, Einevoll GT, (2010) Rate dynamics of leaky integrate-and-fire neurons with strong synapses. Front Comput Neurosci 4: 149.
    • (2010) Front Comput Neurosci , vol.4 , pp. 149
    • Nordlie, E.1    Tetzlaff, T.2    Einevoll, G.T.3
  • 39
    • 68849117446 scopus 로고    scopus 로고
    • Complementary responses to mean and variance modulations in the perfect integrate-and-fire model
    • Pressley J, Troyer TW, (2009) Complementary responses to mean and variance modulations in the perfect integrate-and-fire model. Biol Cybern 101: 63-70.
    • (2009) Biol Cybern , vol.101 , pp. 63-70
    • Pressley, J.1    Troyer, T.W.2
  • 40
    • 0015353310 scopus 로고
    • The relationship between the firing rate of a single neuron and the level of activity in a population of neurons
    • Knight BW, (1972) The relationship between the firing rate of a single neuron and the level of activity in a population of neurons. J Gen Physiol 59: 767-778.
    • (1972) J Gen Physiol , vol.59 , pp. 767-778
    • Knight, B.W.1
  • 41
    • 54149099557 scopus 로고    scopus 로고
    • The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro
    • Köndgen H, Geisler C, Fusi S, Wang XJ, Lüscher HR, et al. (2008) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18: 2086-2097.
    • (2008) Cereb Cortex , vol.18 , pp. 2086-2097
    • Köndgen, H.1    Geisler, C.2    Fusi, S.3    Wang, X.J.4    Lüscher, H.R.5
  • 42
    • 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: 1006-1010.
    • (2009) J Neurosci , vol.29 , pp. 1006-1010
    • Boucsein, C.1    Tetzlaff, T.2    Meier, R.3    Aertsen, A.4    Naundorf, B.5
  • 43
    • 63549111803 scopus 로고    scopus 로고
    • Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminarelectrode recordings in the rat barrel system
    • Blomquist P, Devor A, Indahl UG, Ulbert I, Einevoll GT, et al. (2009) Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminarelectrode recordings in the rat barrel system. PLoS Comput Biol 5: e1000328.
    • (2009) PLoS Comput Biol , vol.5
    • Blomquist, P.1    Devor, A.2    Indahl, U.G.3    Ulbert, I.4    Einevoll, G.T.5
  • 44
    • 0015357448 scopus 로고
    • Dynamics of encoding in a population of neurons
    • Knight BW, (1972) Dynamics of encoding in a population of neurons. J Gen Physiol 59: 734-766.
    • (1972) J Gen Physiol , vol.59 , pp. 734-766
    • Knight, B.W.1
  • 45
    • 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: 2934-2937.
    • (2001) Phys Rev Lett , vol.86 , pp. 2934-2937
    • Lindner, B.1    Schimansky-Geier, L.2
  • 46
    • 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: 2057-2110.
    • (2002) Neural Comput , vol.14 , pp. 2057-2110
    • Fourcaud, N.1    Brunel, N.2
  • 48
    • 0036088498 scopus 로고    scopus 로고
    • LGN input to simple cells and contrast-invariant orientation tuning: An analysis
    • Troyer TW, Krukowski AE, Miller KD, (2002) LGN input to simple cells and contrast-invariant orientation tuning: An analysis. J Neurophysiol 87: 2741-2752.
    • (2002) J Neurophysiol , vol.87 , pp. 2741-2752
    • Troyer, T.W.1    Krukowski, A.E.2    Miller, K.D.3
  • 49
    • 2942724635 scopus 로고    scopus 로고
    • Mathematical analysis and simulations of the neural circuit for locomotion in lampreys
    • Zhaoping L, Lewis A, Scarpetta S, (2004) Mathematical analysis and simulations of the neural circuit for locomotion in lampreys. Phys Rev Lett 92: 198106.
    • (2004) Phys Rev Lett , vol.92 , pp. 198106
    • Zhaoping, L.1    Lewis, A.2    Scarpetta, S.3
  • 50
    • 60449120140 scopus 로고    scopus 로고
    • Balanced amplification: A new mechanism of selective amplification of neural activity patterns
    • Murphy BK, Miller KD, (2009) Balanced amplification: A new mechanism of selective amplification of neural activity patterns. Neuron 61: 635-648.
    • (2009) Neuron , vol.61 , pp. 635-648
    • Murphy, B.K.1    Miller, K.D.2
  • 51
    • 47049115638 scopus 로고    scopus 로고
    • Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons
    • Moreno-Bote R, Renart A, Parga N, (2008) Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons. Neural Comput 20: 1651-1705.
    • (2008) Neural Comput , vol.20 , pp. 1651-1705
    • Moreno-Bote, R.1    Renart, A.2    Parga, N.3
  • 52
    • 0034796381 scopus 로고    scopus 로고
    • Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey
    • Shadlen MN, Newsome WT, (2001) Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol 86: 1916-1936.
    • (2001) J Neurophysiol , vol.86 , pp. 1916-1936
    • Shadlen, M.N.1    Newsome, W.T.2
  • 53
    • 75949115986 scopus 로고    scopus 로고
    • Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice
    • Gentet L, Avermann M, Matyas F, Staiger JF, Petersen CC, (2010) Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice. Neuron 65: 422-435.
    • (2010) Neuron , vol.65 , pp. 422-435
    • Gentet, L.1    Avermann, M.2    Matyas, F.3    Staiger, J.F.4    Petersen, C.C.5
  • 55
    • 84859413691 scopus 로고    scopus 로고
    • Recurrent interactions in spiking networks with arbitrary topology
    • Pernice V, Staude B, Cardanobile S, Rotter S, (2012) Recurrent interactions in spiking networks with arbitrary topology. Phys Rev E 85: 031916.
    • (2012) Phys Rev E , vol.85 , pp. 031916
    • Pernice, V.1    Staude, B.2    Cardanobile, S.3    Rotter, S.4
  • 56
    • 84861158957 scopus 로고    scopus 로고
    • Impact of network structure and cellular response on spike time correlations
    • Trousdale J, Hu Y, Shea-Brown E, Josic K, (2012) Impact of network structure and cellular response on spike time correlations. PLoS Comput Biol 8: e1002408.
    • (2012) PLoS Comput Biol , vol.8
    • Trousdale, J.1    Hu, Y.2    Shea-Brown, E.3    Josic, K.4
  • 57
    • 0027498486 scopus 로고
    • The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs
    • Softky WR, Koch C, (1993) The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J Neurosci 13: 334-350.
    • (1993) J Neurosci , vol.13 , pp. 334-350
    • Softky, W.R.1    Koch, C.2
  • 58
    • 18244424967 scopus 로고    scopus 로고
    • The ground state of cortical feed-forward networks
    • Tetzlaff T, Geisel T, Diesmann M, (2002) The ground state of cortical feed-forward networks. Neurocomputing 44-46: 673-678.
    • (2002) Neurocomputing , vol.44-46 , pp. 673-678
    • Tetzlaff, T.1    Geisel, T.2    Diesmann, M.3
  • 59
    • 0142028099 scopus 로고    scopus 로고
    • Activity dynamics and propagation of synchronous spiking in locally connected random networks
    • 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.
    • (2003) Biol Cybern , vol.88 , pp. 395-408
    • Mehring, C.1    Hehl, U.2    Kubo, M.3    Diesmann, M.4    Aertsen, A.5
  • 60
    • 0038604429 scopus 로고    scopus 로고
    • On embedding synfire chains in a balanced network
    • Aviel Y, Mehring C, Abeles M, Horn D, (2003) On embedding synfire chains in a balanced network. Neural Comput 15: 1321-1340.
    • (2003) Neural Comput , vol.15 , pp. 1321-1340
    • Aviel, Y.1    Mehring, C.2    Abeles, M.3    Horn, D.4
  • 61
    • 13844319430 scopus 로고    scopus 로고
    • Memory capacity of balanced networks
    • Aviel Y, Horn D, Abeles M, (2005) Memory capacity of balanced networks. Neural Comput 17: 691-713.
    • (2005) Neural Comput , vol.17 , pp. 691-713
    • Aviel, Y.1    Horn, D.2    Abeles, M.3
  • 62
    • 0032535029 scopus 로고    scopus 로고
    • Synaptic modifications in cultured hippocampal neurons: Dependence on spike timing, synaptic strength, and postsynaptic cell type
    • Bi G, Poo M, (1998) Synaptic modifications in cultured hippocampal neurons: Dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18: 10464-10472.
    • (1998) J Neurosci , vol.18 , pp. 10464-10472
    • Bi, G.1    Poo, M.2
  • 63
    • 68949211777 scopus 로고    scopus 로고
    • Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity - strengthening correlated input pathways
    • Gilson M, Burkitt AN, Grayden DB, Thomas DA, van Hemmen JL, (2009) Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity- strengthening correlated input pathways. Biol Cybern 101: 81-102.
    • (2009) Biol Cybern , vol.101 , pp. 81-102
    • Gilson, M.1    Burkitt, A.N.2    Grayden, D.B.3    Thomas, D.A.4    van Hemmen, J.L.5
  • 64
    • 34247621946 scopus 로고    scopus 로고
    • Spike-timing-dependent plasticity for neurons with recurrent connections
    • Burkitt AN, Gilson M, van Hemmen J, (2007) Spike-timing-dependent plasticity for neurons with recurrent connections. Biol Cybern 96: 533-546.
    • (2007) Biol Cybern , vol.96 , pp. 533-546
    • Burkitt, A.N.1    Gilson, M.2    van Hemmen, J.3
  • 65
    • 84864601933 scopus 로고    scopus 로고
    • Stdp in oscillatory recurrent networks: theoretical conditions for desynchronization and applications to deep brain stimulation
    • Pfister JP, Tass PA, (2010) Stdp in oscillatory recurrent networks: theoretical conditions for desynchronization and applications to deep brain stimulation. Front Comput Neurosci 454doi: 10.3389/fncom.2010.00022.
    • (2010) Front Comput Neurosci , vol.454
    • Pfister, J.P.1    Tass, P.A.2
  • 66
    • 33244473227 scopus 로고    scopus 로고
    • Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback
    • Lindner B, Doiron B, Longtin A, (2005) Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback. Phys Rev E 72: 061919.
    • (2005) Phys Rev E , vol.72 , pp. 061919
    • Lindner, B.1    Doiron, B.2    Longtin, A.3
  • 67
    • 77649304853 scopus 로고    scopus 로고
    • Systematic uctuation expansion for neural network activity equations
    • Buice MA, Cowan JD, Chow CC, (2009) Systematic uctuation expansion for neural network activity equations. Neural Comput 22: 377-426.
    • (2009) Neural Comput , vol.22 , pp. 377-426
    • Buice, M.A.1    Cowan, J.D.2    Chow, C.C.3
  • 69
    • 33750582231 scopus 로고    scopus 로고
    • Eigenvalue spectra of random matrices for neural networks
    • Rajan K, Abbott L, (2006) Eigenvalue spectra of random matrices for neural networks. Phys Rev Lett 97: 188104.
    • (2006) Phys Rev Lett , vol.97 , pp. 188104
    • Rajan, K.1    Abbott, L.2
  • 70
    • 0000697741 scopus 로고
    • Chaos in random neural networks
    • Sompolinsky, Crisanti, Sommers
    • Sompolinsky, Crisanti, Sommers (1988) Chaos in random neural networks. Phys Rev Lett 61: 259-262.
    • (1988) Phys Rev Lett , vol.61 , pp. 259-262
  • 71
    • 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: 1203-1243.
    • (2009) Neural Comput , vol.21 , pp. 1203-1243
    • Toyoizumi, T.1    Rad, K.R.2    Paninski, L.3
  • 72
    • 0034479938 scopus 로고    scopus 로고
    • Dynamics of neuronal populations: The equilibrium solution
    • Sirovich L, Omurtag A, Knight BW, (2000) Dynamics of neuronal populations: The equilibrium solution. SIAM J Appl Math 60: 2009-2028.
    • (2000) SIAM J Appl Math , vol.60 , pp. 2009-2028
    • Sirovich, L.1    Omurtag, A.2    Knight, B.W.3
  • 73
    • 34447565928 scopus 로고    scopus 로고
    • Exit times for a class of piecewise exponential markov processes with two-sided jumps
    • Jacobsen M, Jensen AT, (2007) Exit times for a class of piecewise exponential markov processes with two-sided jumps. Stoch Proc Appl 117: 1330-1356.
    • (2007) Stoch Proc Appl , vol.117 , pp. 1330-1356
    • Jacobsen, M.1    Jensen, A.T.2
  • 74
    • 84866097511 scopus 로고
    • Renewal Theory
    • London: Chapman and Hall
    • Cox DR (1962) Renewal Theory. Science Paperbacks. London: Chapman and Hall.
    • (1962) Science Paperbacks
    • Cox, D.R.1
  • 76
    • 38349142170 scopus 로고    scopus 로고
    • Efficient evaluation of neuron populations receiving colored-noise current based on a refractory density method
    • Chizhov AV, Graham LJ, (2008) Efficient evaluation of neuron populations receiving colored-noise current based on a refractory density method. Phys Rev E 77: 011910.
    • (2008) Phys Rev E , vol.77 , pp. 011910
    • Chizhov, A.V.1    Graham, L.J.2
  • 77
    • 0036479959 scopus 로고    scopus 로고
    • Temporal correlations in stochastic networks of spiking neurons
    • Meyer C, van Vreeswijk C, (2002) Temporal correlations in stochastic networks of spiking neurons. Neural Comput 14: 369-404.
    • (2002) Neural Comput , vol.14 , pp. 369-404
    • Meyer, C.1    van Vreeswijk, C.2
  • 79
    • 67349159604 scopus 로고    scopus 로고
    • Structural plasticity controlled by calcium based correlation detection
    • Helias M, Rotter S, Gewaltig M, Diesmann M, (2008) Structural plasticity controlled by calcium based correlation detection. Front Comput Neurosci 2doi:10.3389/neuro.10.007.2008.
    • (2008) Front Comput Neurosci , vol.2
    • Helias, M.1    Rotter, S.2    Gewaltig, M.3    Diesmann, M.4
  • 80
    • 77956587282 scopus 로고    scopus 로고
    • Multiquantal release underlies the distribution of synaptic efficacies in the neocortex
    • Loebel A, Silberberg G, Helbig D, Markram H, Tsodyks M, et al. (2009) Multiquantal release underlies the distribution of synaptic efficacies in the neocortex. Front Comput Neurosci 3: 27.
    • (2009) Front Comput Neurosci , vol.3 , pp. 27
    • Loebel, A.1    Silberberg, G.2    Helbig, D.3    Markram, H.4    Tsodyks, M.5
  • 81
  • 82
    • 0002920216 scopus 로고
    • Point spectra of some mutually exciting point process
    • Hawkes A, (1971) Point spectra of some mutually exciting point process. J R Statist Soc Ser B 33: 438-443.
    • (1971) J R Statist Soc Ser B , vol.33 , pp. 438-443
    • Hawkes, A.1
  • 84
    • 36149019489 scopus 로고
    • On the first passage time probability problem
    • Siegert AJ, (1951) On the first passage time probability problem. Phys Rev 81: 617-623.
    • (1951) Phys Rev , vol.81 , pp. 617-623
    • Siegert, A.J.1
  • 85
    • 78049438383 scopus 로고    scopus 로고
    • Equilibrium and response properties of the integrate-and-fire neuron in discrete time
    • Helias M, Deger M, Diesmann M, Rotter S, (2010) Equilibrium and response properties of the integrate-and-fire neuron in discrete time. Front Comput Neurosci 3doi:10.3389/neuro.10.029.2009.
    • (2010) Front Comput Neurosci , vol.3
    • Helias, M.1    Deger, M.2    Diesmann, M.3    Rotter, S.4
  • 87
    • 0033220632 scopus 로고    scopus 로고
    • Exact digital simulation of time-invariant linear systems with applications to neuronal modeling
    • Rotter S, Diesmann M, (1999) Exact digital simulation of time-invariant linear systems with applications to neuronal modeling. Biol Cybern 81: 381-402.
    • (1999) Biol Cybern , vol.81 , pp. 381-402
    • Rotter, S.1    Diesmann, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.