Skip to main content
Erschienen in: Journal of Computational Neuroscience 3/2010

01.12.2010

Local field potentials indicate network state and account for neuronal response variability

verfasst von: Ryan C. Kelly, Matthew A. Smith, Robert E. Kass, Tai Sing Lee

Erschienen in: Journal of Computational Neuroscience | Ausgabe 3/2010

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Multineuronal recordings have revealed that neurons in primary visual cortex (V1) exhibit coordinated fluctuations of spiking activity in the absence and in the presence of visual stimulation. From the perspective of understanding a single cell’s spiking activity relative to a behavior or stimulus, these network fluctuations are typically considered to be noise. We show that these events are highly correlated with another commonly recorded signal, the local field potential (LFP), and are also likely related to global network state phenomena which have been observed in a number of neural systems. Moreover, we show that attributing a component of cell firing to these network fluctuations via explicit modeling of the LFP improves the recovery of cell properties. This suggests that the impact of network fluctuations may be estimated using the LFP, and that a portion of this network activity is unrelated to the stimulus and instead reflects ongoing cortical activity. Thus, the LFP acts as an easily accessible bridge between the network state and the spiking activity.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Abbott, L. F., & Dayan, P. (1999). The effect of correlated variability on the accuracy of a population code. Neural Computation, 11, 91–101.CrossRefPubMed Abbott, L. F., & Dayan, P. (1999). The effect of correlated variability on the accuracy of a population code. Neural Computation, 11, 91–101.CrossRefPubMed
Zurück zum Zitat Areili, A., Sterkin, A., Grinvald, A., & Aertson, A. (1996). Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses. Science, 273(5283), 1868–1871.CrossRef Areili, A., Sterkin, A., Grinvald, A., & Aertson, A. (1996). Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses. Science, 273(5283), 1868–1871.CrossRef
Zurück zum Zitat Averbeck, B. B., Latham, P. E., & Pouget, A. P. (2006). Neural correlations, population coding and computation. Nature Reviews. Neuroscience, 7, 358–366.CrossRefPubMed Averbeck, B. B., Latham, P. E., & Pouget, A. P. (2006). Neural correlations, population coding and computation. Nature Reviews. Neuroscience, 7, 358–366.CrossRefPubMed
Zurück zum Zitat Bair, W., Zohary, E., & Newsome, W. T. (2001). Correlated firing in macaque visual area MT: Time scales and relationship to behavior. Journal of Neuroscience, 21, 1676–1697.PubMed Bair, W., Zohary, E., & Newsome, W. T. (2001). Correlated firing in macaque visual area MT: Time scales and relationship to behavior. Journal of Neuroscience, 21, 1676–1697.PubMed
Zurück zum Zitat Berens, P., Keliris, G., Ecker, A., Logothetis, N., & Tolias, A. (2008). Feature selectivity of the gamma-band of the local field potential in primate primary visual cortex. Frontiers in Neuroscience, 2, 199–207.CrossRefPubMed Berens, P., Keliris, G., Ecker, A., Logothetis, N., & Tolias, A. (2008). Feature selectivity of the gamma-band of the local field potential in primate primary visual cortex. Frontiers in Neuroscience, 2, 199–207.CrossRefPubMed
Zurück zum Zitat Buzsaki, G. (2004). Large-scale recording of neuronal ensembles. Nature Neuroscience, 7, 446–451.CrossRefPubMed Buzsaki, G. (2004). Large-scale recording of neuronal ensembles. Nature Neuroscience, 7, 446–451.CrossRefPubMed
Zurück zum Zitat Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002). Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. Journal of Neurophysiology, 88, 2530–2546.CrossRefPubMed Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002). Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. Journal of Neurophysiology, 88, 2530–2546.CrossRefPubMed
Zurück zum Zitat David, S., Vinje, W., & Gallant, J. (2004). Natural stimulus statistics alter the receptive field structure of V1 neurons. Journal of Neuroscience, 24, 6991–7006.CrossRefPubMed David, S., Vinje, W., & Gallant, J. (2004). Natural stimulus statistics alter the receptive field structure of V1 neurons. Journal of Neuroscience, 24, 6991–7006.CrossRefPubMed
Zurück zum Zitat Destexhe, A., & Contreras, D. (2006). Neuronal computations with stochastic network states. Science, 314, 85–90.CrossRefPubMed Destexhe, A., & Contreras, D. (2006). Neuronal computations with stochastic network states. Science, 314, 85–90.CrossRefPubMed
Zurück zum Zitat DeValois, R. L., Albrecht, D. G., & Thorell, L. G. (1982). Spatial frequency selectivity of cells in macaque visual cortex. Vision Research, 22, 545–559.CrossRef DeValois, R. L., Albrecht, D. G., & Thorell, L. G. (1982). Spatial frequency selectivity of cells in macaque visual cortex. Vision Research, 22, 545–559.CrossRef
Zurück zum Zitat Eggermont, J., & Smith, G. (1995). Synchrony between single-unit activity and local field potentials in relation to periodicity coding in primary auditory cortex. Journal of Neurophysiology, 73, 227–245.PubMed Eggermont, J., & Smith, G. (1995). Synchrony between single-unit activity and local field potentials in relation to periodicity coding in primary auditory cortex. Journal of Neurophysiology, 73, 227–245.PubMed
Zurück zum Zitat Foster, K. H., Gaska, J. P., Nagler, M., & Pollen, D. A. (1985). Spatial and temporal frequency selectivity of neurones in visual cortical areas V1 and V2 of the Macaque monkey. Journal of Physiology, 365, 331–363.PubMed Foster, K. H., Gaska, J. P., Nagler, M., & Pollen, D. A. (1985). Spatial and temporal frequency selectivity of neurones in visual cortical areas V1 and V2 of the Macaque monkey. Journal of Physiology, 365, 331–363.PubMed
Zurück zum Zitat Frien, A., Eckhorn, R., Bauer, R., Woelbern, T., & Gabriel, A. (2000). Fast oscillations display sharper orientation tuning than slower components of the same recordings in striate cortex of the awake monkey. European Journal of Neuroscience, 12, 1453–1465.CrossRefPubMed Frien, A., Eckhorn, R., Bauer, R., Woelbern, T., & Gabriel, A. (2000). Fast oscillations display sharper orientation tuning than slower components of the same recordings in striate cortex of the awake monkey. European Journal of Neuroscience, 12, 1453–1465.CrossRefPubMed
Zurück zum Zitat Gray, C. M., Maldonado, P. E., Wilson, M., & McNaughton, B. (1995). Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. Journal of Neuroscience Methods, 63, 43–54.CrossRefPubMed Gray, C. M., Maldonado, P. E., Wilson, M., & McNaughton, B. (1995). Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. Journal of Neuroscience Methods, 63, 43–54.CrossRefPubMed
Zurück zum Zitat Hardin, J. W., & Hilbe, J. (2007). Generalized linear models and extensions. College Station: Stata. Hardin, J. W., & Hilbe, J. (2007). Generalized linear models and extensions. College Station: Stata.
Zurück zum Zitat Haslinger, R., Ulbert, I., Moore, C., Brown, E., & Devor, A. (2006). Analysis of LFP phase predicts sensort response of barrel cortex. Journal of Neurophysiology, 96, 1658–1663.CrossRefPubMed Haslinger, R., Ulbert, I., Moore, C., Brown, E., & Devor, A. (2006). Analysis of LFP phase predicts sensort response of barrel cortex. Journal of Neurophysiology, 96, 1658–1663.CrossRefPubMed
Zurück zum Zitat He, B., Snyder, A., Zempel, J., Smyth, M., & Raichle, M. (2008). Electrophysiological correlates of the brains intrinsic large-scale functional architecture. Proceedings of the National Academy of Sciences of the United States of America, 105, 16039–16044.CrossRefPubMed He, B., Snyder, A., Zempel, J., Smyth, M., & Raichle, M. (2008). Electrophysiological correlates of the brains intrinsic large-scale functional architecture. Proceedings of the National Academy of Sciences of the United States of America, 105, 16039–16044.CrossRefPubMed
Zurück zum Zitat Henrie, J., & Shapley, R. (2005). LFP power spectra in V1 cortex: The graded effect of stimulus contrast. Journal of Neurophysiology, 94, 479–490.CrossRefPubMed Henrie, J., & Shapley, R. (2005). LFP power spectra in V1 cortex: The graded effect of stimulus contrast. Journal of Neurophysiology, 94, 479–490.CrossRefPubMed
Zurück zum Zitat Huang, X., & Lisberger, S. (2009). Noise correlations in cortical area MT and their potential impact on trial-by-trial variation in the direction and speed of smooth pursuit eye movements. Journal of Neurophysiology, 101, 3012–3030.CrossRefPubMed Huang, X., & Lisberger, S. (2009). Noise correlations in cortical area MT and their potential impact on trial-by-trial variation in the direction and speed of smooth pursuit eye movements. Journal of Neurophysiology, 101, 3012–3030.CrossRefPubMed
Zurück zum Zitat Johnson, H., & Buonomano, D. (2007). Development and plasticity of spontaneous activity and up states in cortical organotypic slices. Journal of Neuroscience, 27(22), 5915–5925.CrossRefPubMed Johnson, H., & Buonomano, D. (2007). Development and plasticity of spontaneous activity and up states in cortical organotypic slices. Journal of Neuroscience, 27(22), 5915–5925.CrossRefPubMed
Zurück zum Zitat Kass, R., & Ventura, V. (2001). A spike-train probability model. Neural Computation, 13, 1713–1720.CrossRefPubMed Kass, R., & Ventura, V. (2001). A spike-train probability model. Neural Computation, 13, 1713–1720.CrossRefPubMed
Zurück zum Zitat Katzner, S., Nauhaus, I., Benucci, A., Bonin, V., Ringach, D., & Carandini, M. (2009). Local origin of field potentials in visual cortex. Neuron, 61, 35–41.CrossRefPubMed Katzner, S., Nauhaus, I., Benucci, A., Bonin, V., Ringach, D., & Carandini, M. (2009). Local origin of field potentials in visual cortex. Neuron, 61, 35–41.CrossRefPubMed
Zurück zum Zitat Kelly, R. C., Smith, M. A., Samonds, J. M., Kohn, A., Bonds, A. B., Movshon, J. A., et al. (2007). Comparison of recordings from microelectrode arrays and single electrodes in the visual cortex. Journal of Neuroscience, 27, 261–264.CrossRefPubMed Kelly, R. C., Smith, M. A., Samonds, J. M., Kohn, A., Bonds, A. B., Movshon, J. A., et al. (2007). Comparison of recordings from microelectrode arrays and single electrodes in the visual cortex. Journal of Neuroscience, 27, 261–264.CrossRefPubMed
Zurück zum Zitat Kohn, A., & Smith, M. A. (2005). Stimulus dependence of neuronal correlation in primary visual cortex of the Macaque. Journal of Neuroscience, 25, 3661–3673.CrossRefPubMed Kohn, A., & Smith, M. A. (2005). Stimulus dependence of neuronal correlation in primary visual cortex of the Macaque. Journal of Neuroscience, 25, 3661–3673.CrossRefPubMed
Zurück zum Zitat Kohn, A., Zandvakili, A., & Smith, M. A. (2009). Correlations and brain states: From electrophysiology to functional imaging. Current Opinion in Neurobiology, 19, 434–438.CrossRefPubMed Kohn, A., Zandvakili, A., & Smith, M. A. (2009). Correlations and brain states: From electrophysiology to functional imaging. Current Opinion in Neurobiology, 19, 434–438.CrossRefPubMed
Zurück zum Zitat Körding, K., Kayser, C., Einhäuser, W., & König, P. (2004). How are complex cell properties adapted to the statistics of natural stimuli? Journal of Neurophysiology, 91, 206–212.CrossRefPubMed Körding, K., Kayser, C., Einhäuser, W., & König, P. (2004). How are complex cell properties adapted to the statistics of natural stimuli? Journal of Neurophysiology, 91, 206–212.CrossRefPubMed
Zurück zum Zitat Kreiman, G., Hung, C., Kraskov, A., Quiroga, R., Poggio, T., & DiCarlo, J. (2006). Object selectivity of local field potentials and spikes in the Macaque inferior temporal cortex. Neuron, 49, 433–445.CrossRefPubMed Kreiman, G., Hung, C., Kraskov, A., Quiroga, R., Poggio, T., & DiCarlo, J. (2006). Object selectivity of local field potentials and spikes in the Macaque inferior temporal cortex. Neuron, 49, 433–445.CrossRefPubMed
Zurück zum Zitat Kruse, W., & Eckhorn, R. (1996). Inhibition of sustained gamma oscillations (35–80 Hz) by fast transient responses in cat visual cortex. Proceedings of the National Academy of Sciences, 93, 6112–6117.CrossRef Kruse, W., & Eckhorn, R. (1996). Inhibition of sustained gamma oscillations (35–80 Hz) by fast transient responses in cat visual cortex. Proceedings of the National Academy of Sciences, 93, 6112–6117.CrossRef
Zurück zum Zitat Lampl, I., Reichova, I., & Ferster, D. (1999). Synchronous membrane potential fluctuations in neurons of the cat visual cortex. Neuron, 22, 361–374.CrossRefPubMed Lampl, I., Reichova, I., & Ferster, D. (1999). Synchronous membrane potential fluctuations in neurons of the cat visual cortex. Neuron, 22, 361–374.CrossRefPubMed
Zurück zum Zitat Legatt, A. D., Arezzo, J., & Vaughan, H. G. (1980). Averaged multiple unit activity as an estimate of phasic changes in local neuronal activity: Effects of volume-conducted potentials. Journal of Neuroscience Methods, 2, 203–217.CrossRefPubMed Legatt, A. D., Arezzo, J., & Vaughan, H. G. (1980). Averaged multiple unit activity as an estimate of phasic changes in local neuronal activity: Effects of volume-conducted potentials. Journal of Neuroscience Methods, 2, 203–217.CrossRefPubMed
Zurück zum Zitat Leopold, D. A., Murayama, Y., & Logothetis, N. K. (2003). Very slow activity fluctuations in monkey visual cortex: Implications for functional brain imaging. Cerebral Cortex, 13, 422–433.CrossRefPubMed Leopold, D. A., Murayama, Y., & Logothetis, N. K. (2003). Very slow activity fluctuations in monkey visual cortex: Implications for functional brain imaging. Cerebral Cortex, 13, 422–433.CrossRefPubMed
Zurück zum Zitat Liu, J., & Newsome, W. (2006). Local field potential in cortical area MT: Stimulus tuning and behavioral correlations. Journal of Neuroscience, 26, 7779–7790.CrossRefPubMed Liu, J., & Newsome, W. (2006). Local field potential in cortical area MT: Stimulus tuning and behavioral correlations. Journal of Neuroscience, 26, 7779–7790.CrossRefPubMed
Zurück zum Zitat Luczak, A., Bartho, P., Marguet, S., Buzsaki, G., & Harris, K. (2007). Sequential structure of neocortical spontaneous activity in vivo. Proceedings of the National Academy of Sciences of the United States of America, 104, 347–352.CrossRefPubMed Luczak, A., Bartho, P., Marguet, S., Buzsaki, G., & Harris, K. (2007). Sequential structure of neocortical spontaneous activity in vivo. Proceedings of the National Academy of Sciences of the United States of America, 104, 347–352.CrossRefPubMed
Zurück zum Zitat Mitzdorf, U. (1987). Properties of the evoked potential generators: Current source-density analysis of visually evoked potentials in the cat cortex. International Journal of Neuroscience, 33, 33–59.CrossRefPubMed Mitzdorf, U. (1987). Properties of the evoked potential generators: Current source-density analysis of visually evoked potentials in the cat cortex. International Journal of Neuroscience, 33, 33–59.CrossRefPubMed
Zurück zum Zitat Nauhaus, I., Busse, L., Carandini, M., & D.L., R. (2009). Stimulus contrast modulates functional connectivity in visual cortex. Nature Neuroscience, 12, 70–76.CrossRefPubMed Nauhaus, I., Busse, L., Carandini, M., & D.L., R. (2009). Stimulus contrast modulates functional connectivity in visual cortex. Nature Neuroscience, 12, 70–76.CrossRefPubMed
Zurück zum Zitat Nir, Y., Mukamel, R., Dinstein, I., Privman, E., Harel, M., Fisch, L., et al. (2008). Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex. Nature Neuroscience, 11(9), 1100–1108.CrossRefPubMed Nir, Y., Mukamel, R., Dinstein, I., Privman, E., Harel, M., Fisch, L., et al. (2008). Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex. Nature Neuroscience, 11(9), 1100–1108.CrossRefPubMed
Zurück zum Zitat Paninski, L. (2004). Maximum likelihood estimation of cascade point-process encoding models. Network: Computation in Neural Systems, 15, 243–262.CrossRef Paninski, L. (2004). Maximum likelihood estimation of cascade point-process encoding models. Network: Computation in Neural Systems, 15, 243–262.CrossRef
Zurück zum Zitat Paninski, L., Brown, E., Iyengar, S., & Kass, R. (2009). Statistical models of spike trains. In C. Liang, & G. Lord (Eds.), Stochastic methods in neuroscience (pp. 278–303). Oxford: Clarendon. Paninski, L., Brown, E., Iyengar, S., & Kass, R. (2009). Statistical models of spike trains. In C. Liang, & G. Lord (Eds.), Stochastic methods in neuroscience (pp. 278–303). Oxford: Clarendon.
Zurück zum Zitat Paninski, L., Pillow, J., & Lewi, J. (2007). Statistical models for neural encoding, decoding, and optimal stimulus design. Progress in Brain Research, 165, 493.CrossRefPubMed Paninski, L., Pillow, J., & Lewi, J. (2007). Statistical models for neural encoding, decoding, and optimal stimulus design. Progress in Brain Research, 165, 493.CrossRefPubMed
Zurück zum Zitat Petersen, C., Grinvald, A., & Sakmann, B. (2003). Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell recordings and neuron reconstructions. Journal of Neuroscience, 23, 1298–1309.PubMed Petersen, C., Grinvald, A., & Sakmann, B. (2003). Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell recordings and neuron reconstructions. Journal of Neuroscience, 23, 1298–1309.PubMed
Zurück zum Zitat Pillow, J. (2007). Likelihood-based approaches to modeling the neural code. In K. Doya, S. Ishii, A. Pouget, & R. Rao, (Eds.), Bayesian brain: Probabilistic approaches to neural coding (pp. 53–70). Cambridge: MIT. Pillow, J. (2007). Likelihood-based approaches to modeling the neural code. In K. Doya, S. Ishii, A. Pouget, & R. Rao, (Eds.), Bayesian brain: Probabilistic approaches to neural coding (pp. 53–70). Cambridge: MIT.
Zurück zum Zitat Pillow, J., & Latham, P. (2008). Neural characterization in partially observed populations of spiking neurons. Advances in Neural Information Processing Systems, 20, 1161–1168. Pillow, J., & Latham, P. (2008). Neural characterization in partially observed populations of spiking neurons. Advances in Neural Information Processing Systems, 20, 1161–1168.
Zurück zum Zitat Pillow, J., Shlens, J., Paninski, L., Sher, A., Litke, A., Chichilnisky, E., et al. (2008). Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature, 454, 995–999.CrossRefPubMed Pillow, J., Shlens, J., Paninski, L., Sher, A., Litke, A., Chichilnisky, E., et al. (2008). Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature, 454, 995–999.CrossRefPubMed
Zurück zum Zitat Rasch, M., Gretton, A., Murayama, Y., Maass, W., & Logothetis, N. (2008). Inferring spike trains from local field potentials. Journal of Neurophysiology, 99, 1461–1476.CrossRefPubMed Rasch, M., Gretton, A., Murayama, Y., Maass, W., & Logothetis, N. (2008). Inferring spike trains from local field potentials. Journal of Neurophysiology, 99, 1461–1476.CrossRefPubMed
Zurück zum Zitat Ringach, D., Hawken, M., & Shapley, R. (2002). Receptive field structure of neurons in monkey primary visual cortex revealed by stimulation with natural image sequences. Journal of Visualization, 2, 12–24.CrossRef Ringach, D., Hawken, M., & Shapley, R. (2002). Receptive field structure of neurons in monkey primary visual cortex revealed by stimulation with natural image sequences. Journal of Visualization, 2, 12–24.CrossRef
Zurück zum Zitat Rousche, P. J., & Normann, R. A. (1992). A method for pneumatically inserting an array of penetrating electrodes into cortical tissue. Annals of Biomedical Engineering, 20, 413–422.CrossRefPubMed Rousche, P. J., & Normann, R. A. (1992). A method for pneumatically inserting an array of penetrating electrodes into cortical tissue. Annals of Biomedical Engineering, 20, 413–422.CrossRefPubMed
Zurück zum Zitat Samonds, J. M., & Bonds, A. B. (2005). Gamma oscillation maintains stimulus structure-dependent synchronization in cat visual cortex. Journal of Neurophysiology, 93, 223–236.CrossRefPubMed Samonds, J. M., & Bonds, A. B. (2005). Gamma oscillation maintains stimulus structure-dependent synchronization in cat visual cortex. Journal of Neurophysiology, 93, 223–236.CrossRefPubMed
Zurück zum Zitat Shadlen, M. N., & Newsome, W. T. (1998). The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding. Journal of Neuroscience, 18, 3870–3896.PubMed Shadlen, M. N., & Newsome, W. T. (1998). The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding. Journal of Neuroscience, 18, 3870–3896.PubMed
Zurück zum Zitat Shlens, J., Field, G., Gauthier, J., Greschner, M., Sher, A., Litke, A., & Chichilnisky, E. (2009). The structure of large-scale synchronized firing in primate retina. Journal of Neuroscience, 29, 5022–5031.CrossRefPubMed Shlens, J., Field, G., Gauthier, J., Greschner, M., Sher, A., Litke, A., & Chichilnisky, E. (2009). The structure of large-scale synchronized firing in primate retina. Journal of Neuroscience, 29, 5022–5031.CrossRefPubMed
Zurück zum Zitat Shoham, S., Fellows, M., & Normann, R. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods, 127, 111–122.CrossRefPubMed Shoham, S., Fellows, M., & Normann, R. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods, 127, 111–122.CrossRefPubMed
Zurück zum Zitat Siegel, M., & Koenig, P. (2003). A functional gamma-band defined by stimulus-dependent synchronization in area 18 of awake behaving cats. Journal of Neuroscience, 23, 4251–4260.PubMed Siegel, M., & Koenig, P. (2003). A functional gamma-band defined by stimulus-dependent synchronization in area 18 of awake behaving cats. Journal of Neuroscience, 23, 4251–4260.PubMed
Zurück zum Zitat Smith, M. A., Bair, W., & Movshon, J. A. (2002). Signals in macaque V1 neurons that support the perception of Glass patterns. Journal of Neuroscience, 22, 8334–8345.PubMed Smith, M. A., Bair, W., & Movshon, J. A. (2002). Signals in macaque V1 neurons that support the perception of Glass patterns. Journal of Neuroscience, 22, 8334–8345.PubMed
Zurück zum Zitat Smith, M. A., & Kohn, A. (2008). Spatial and temporal scales of neuronal correlation in primary visual cortex. Journal of Neuroscience, 28, 12591–12603.CrossRefPubMed Smith, M. A., & Kohn, A. (2008). Spatial and temporal scales of neuronal correlation in primary visual cortex. Journal of Neuroscience, 28, 12591–12603.CrossRefPubMed
Zurück zum Zitat Tsodyks, M., Kenet, T., Grinvald, A., & Arieli, A. (1999). Linking spontaneous activity of single cortical neurons and the underlying functional architecture. Science, 286(5446), 1943–1946.CrossRefPubMed Tsodyks, M., Kenet, T., Grinvald, A., & Arieli, A. (1999). Linking spontaneous activity of single cortical neurons and the underlying functional architecture. Science, 286(5446), 1943–1946.CrossRefPubMed
Zurück zum Zitat Xing, D., Yeh, C., & Shapley, R. (2009). Spatial spread of the local field potential and its laminar variation in visual cortex. Journal of Neuroscience, 29, 11540–11549.CrossRefPubMed Xing, D., Yeh, C., & Shapley, R. (2009). Spatial spread of the local field potential and its laminar variation in visual cortex. Journal of Neuroscience, 29, 11540–11549.CrossRefPubMed
Zurück zum Zitat Zohary, E., Shadlen, M. N., & Newsome, W. T. (1994). Correlated neuronal discharge rate and its implications for psychophysical performance. Nature, 370, 140–143.CrossRefPubMed Zohary, E., Shadlen, M. N., & Newsome, W. T. (1994). Correlated neuronal discharge rate and its implications for psychophysical performance. Nature, 370, 140–143.CrossRefPubMed
Metadaten
Titel
Local field potentials indicate network state and account for neuronal response variability
verfasst von
Ryan C. Kelly
Matthew A. Smith
Robert E. Kass
Tai Sing Lee
Publikationsdatum
01.12.2010
Verlag
Springer US
Erschienen in
Journal of Computational Neuroscience / Ausgabe 3/2010
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI
https://doi.org/10.1007/s10827-009-0208-9

Weitere Artikel der Ausgabe 3/2010

Journal of Computational Neuroscience 3/2010 Zur Ausgabe

Premium Partner