Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity
Open accessAbstract
In vivo, in vitro and computational studies were used to investigate the impact of the synaptic background activity observed in neocortical neurons in vivo. We simulated background activity in vitro using two stochastic Ornstein-Uhlenbeck processes describing glutamatergic and GABAergic synaptic conductances, which were injected into a cell in real time using the dynamic clamp technique. With parameters chosen to mimic in vivo conditions, layer 5 rat prefrontal cortex cells recorded in vitro were depolarized by about 15 mV, their membrane fluctuated with a S.D. of about 4 mV, their input resistances decreased five-fold, their spontaneous firing had a high coefficient of variation and an average firing rate of about 5-10 Hz. Brief changes in the variance of the alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) synaptic conductance fluctuations induced time-locked spiking without significantly changing the average membrane potential of the cell. These transients mimicked increases in the correlation of excitatory inputs. Background activity was highly effective in modulating the firing-rate/current curve of the cell: the variance of the simulated gamma-aminobutyric acid (GABA) and AMPA conductances individually set the input/output gain, the mean excitatory and inhibitory conductances set the working point, and the mean inhibitory conductance controlled the input resistance. An average ratio of inhibitory to excitatory mean conductances close to 4 was optimal in generating membrane potential fluctuations with high coefficients of variation. We conclude that background synaptic activity can dynamically modulate the input/output properties of individual neocortical neurons in vivo.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Unlike synaptically driven Vm fluctuations, changes in membrane conductance and depolarization cause lateral, or additive, shifts in the I/O transfer function of a neuron without changes in neuronal gain.
“Unlike synaptically driven Vm fluctuations, changes in membrane conductance and depolarization cause lateral, or additive, shifts in the I/O transfer function of a neuron without changes in neuronal gain57,58,60,61,83,84.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [83]
Temporally coincident changes in conductance state and synaptic fluctuations exert a powerful effect on neuronal gain at the single-cell level.
“Together, temporally coincident changes in conductance state and synaptic fluctuations exert a powerful effect on neuronal gain at the single-cell level57,58,60,61,83,84.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [83]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905 · see citing works
On the Theory of the Brownian Motion
Uhlenbeck, G. E., & Ornstein, L. S. (1930) · Physical Review · doi:10.1103/physrev.36.823 · Cited by 4,618 · see citing works
Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention
Fries, P., Reynolds, J. H., Rorie, A. E., & Desimone, R. (2001) · Science · doi:10.1126/science.1055465 · Cited by 2,786 · see citing works
The NEURON Simulation Environment
Hines, M. L., & Carnevale, N. T. (1997) · Neural Computation · doi:10.1162/neco.1997.9.6.1179 · Cited by 2,630 · see citing works
Sakmann, B. J., & Neher, E. (1995) · Springer eBooks · doi:10.1007/978-1-4419-1229-9 · Cited by 2,543 · see citing works
Shadlen, M. N., & Newsome, W. T. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-10-03870.1998 · Cited by 2,178 · see citing works
Reliability of spike timing in neocortical neurons
Mainen, Z. F., & Sejnowski, T. J. (1995) · Science · doi:10.1126/science.7770778 · Cited by 1,950 · see citing works
Steriade, M., Nunez, A., & Amzica, F. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-08-03252.1993 · Cited by 1,903 · see citing works
Softky, W., & Koch, C. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-01-00334.1993 · Cited by 1,689 · see citing works
Theory of stochastic resonance
McNamara, B., & Wiesenfeld, K. A. (1989) · Physical Review A · doi:10.1103/physreva.39.4854 · Cited by 1,563 · see citing works
Correlated neuronal activity and the flow of neural information
Salinas, E., & Sejnowski, T. J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35086012 · Cited by 1,333 · see citing works
Noise, neural codes and cortical organization
Shadlen, M. N., & Newsome, W. T. (1994) · Current Opinion in Neurobiology · doi:10.1016/0959-4388(94)90059-0 · Cited by 1,240 · see citing works
The high-conductance state of neocortical neurons in vivo
Alain Destexhe, A., Rudolph, M., & Paré, D. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1198 · Cited by 1,077 · see citing works
Self-citationGain Modulation from Background Synaptic Input
Chance, F. S., Abbott, L. F., & Reyes, A. D. (2002) · Neuron · doi:10.1016/s0896-6273(02)00820-6 · Cited by 1,012 · see citing works
DeFelipe, J., & Fariñas, I. (1992) · Progress in Neurobiology · doi:10.1016/0301-0082(92)90015-7 · Cited by 975 · see citing works
Intracellular Features Predicted by Extracellular Recordings in the Hippocampus In Vivo
Henze, D. A., Borhegyi, Z., Csicsvari, J., Mamiya, A., Harris, K. D., & Buzsáki, G. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.1.390 · Cited by 942 · see citing works
On the theory of brownian motion
Mazur, P. (1959) · Physica · doi:10.1016/s0031-8914(59)91931-7 · Cited by 933 · see citing works
Neuronal Networks of the Hippocampus
Traub, R. D., & Miles, R. (1991) · doi:10.1017/cbo9780511895401 · Cited by 802 · see citing works
A Network Model of Catecholamine Effects: Gain, Signal-to-Noise Ratio, and Behavior
Servan‐Schreiber, D., Printz, H., & Cohen, J. D. (1990) · Science · doi:10.1126/science.2392679 · Cited by 770 · see citing works
Attention modulates synchronized neuronal firing in primate somatosensory cortex
Steinmetz, P. N., Roy, A., Fitzgerald, P. J., Hsiao, S. S., Johnson, K. O., & Niebur, E. (2000) · Nature · doi:10.1038/35004588 · Cited by 725 · see citing works
Cellular basis of EEG slow rhythms: a study of dynamic corticothalamic relationships
Contreras, D., & Steriade, M. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-01-00604.1995 · Cited by 700 · see citing works
Broadband neural encoding in the cricket cereal sensory system enhanced by stochastic resonance
Levin, J. E., & Miller, J. P. (1996) · Nature · doi:10.1038/380165a0 · Cited by 677 · see citing works
Liquid junction potentials and small cell effects in patch-clamp analysis
Barry, P. H., & Lynch, J. W. (1991) · The Journal of Membrane Biology · doi:10.1007/bf01870526 · Cited by 675 · see citing works
Visual input evokes transient and strong shunting inhibition in visual cortical neurons
Graham, L. J., Monier, C., & Frégnac, Y. (1998) · Nature · doi:10.1038/30735 · Cited by 669 · see citing works
Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons
Destexhe, A., Rudolph, M., Fellous, J.-M., & Sejnowski, T. J. (2001) · Neuroscience · doi:10.1016/s0306-4522(01)00344-x · Cited by 642 · see citing works
Self-citationAlain Destexhe, A., Mainen, Z. F., & B, T. J. S. A. (1994) · Journal of Computational Neuroscience · doi:10.1007/bf00961734 · Cited by 627 · see citing works
Impact of Network Activity on the Integrative Properties of Neocortical Pyramidal Neurons In Vivo
Alain Destexhe, A., & Paré, D. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.81.4.1531 · Cited by 621 · see citing works
Barry, P. H. (1994) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(94)90031-0 · Cited by 611 · see citing works
Neuromodulation and cortical function: modeling the physiological basis of behavior
Hasselmo, M. E. (1995) · Behavioural Brain Research · doi:10.1016/0166-4328(94)00113-t · Cited by 552 · see citing works
Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons
Holt, G. R., Softky, W. R., Christof Koch, A., & Douglas, R. J. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.75.5.1806 · Cited by 526 · see citing works
Synaptic background activity influences spatiotemporal integration in single pyramidal cells.
Bernander, Ö., Douglas, R. J., Martin, K. A. C., & Koch, C. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.24.11569 · Cited by 518 · see citing works
Stochastic resonance in neuron models
Longtin, A. (1993) · Journal of Statistical Physics · doi:10.1007/bf01053970 · Cited by 517 · see citing works
Impact of Correlated Synaptic Input on Output Firing Rate and Variability in Simple Neuronal Models
Salinas, E., & Sejnowski, T. J. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-16-06193.2000 · Cited by 472 · see citing works
Paré, D., Shink, É., Gaudreau, H., Alain Destexhe, A., & Lang, E. J. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.3.1450 · Cited by 453 · see citing works
Dynamic clamp: computer-generated conductances in real neurons
Sharp, A. A., O'Neil, M. B., Abbott, L. F., & Marder, E. E. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.69.3.992 · Cited by 431 · see citing works
How independent are the messages carried by adjacent inferior temporal cortical neurons?
Gawne, T. J., & Richmond, B. (1993) · Journal of Neuroscience · doi:10.1523/jneurosci.13-07-02758.1993 · Cited by 425 · see citing works
Cellular Mechanisms Contributing to Response Variability of Cortical NeuronsIn Vivo
Azouz, R., & Gray, C. M. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-06-02209.1999 · Cited by 408 · see citing works
Neural Representation and the Cortical Code
deCharms, R. C., & Zador, A. M. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.613 · Cited by 392 · see citing works
Spike Transmission and Synchrony Detection in Networks of GABAergic Interneurons
Galarreta, M., & Hestrin, S. (2001) · Science · doi:10.1126/science.1061395 · Cited by 389 · see citing works
Contreras, D., Timofeev, I., & Steriade, M. (1996) · The Journal of Physiology · doi:10.1113/jphysiol.1996.sp021488 · Cited by 374 · see citing works
Activity Coregulates Quantal AMPA and NMDA Currents at Neocortical Synapses
Watt, A. J., van Rossum, M. C. W., MacLeod, K. M., Nelson, S. B., & Turrigiano, G. G. (2000) · Neuron · doi:10.1016/s0896-6273(00)81202-7 · Cited by 350 · see citing works
A Limit to the Speed of Processing in Ultra-Rapid Visual Categorization of Novel Natural Scenes
Fabre‐Thorpe, M., Arnaud Delorme, A., Marlot, C., & Thorpe, S. J. (2001) · Journal of Cognitive Neuroscience · doi:10.1162/089892901564234 · Cited by 339 · see citing works
The mathematics of Brownian motion and Johnson noise
Gillespie, D. T. (1996) · American Journal of Physics · doi:10.1119/1.18210 · Cited by 331 · see citing works
Keysers, C., Xiao, D. K., Földiák, P., & Perrett, D. I. (2001) · Journal of Cognitive Neuroscience · doi:10.1162/089892901564199 · Cited by 330 · see citing works
Information Processing in Dendritic Trees
Mel, B. W. (1994) · Neural Computation · doi:10.1162/neco.1994.6.6.1031 · Cited by 290 · see citing works
Lewis, B. L. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.12.1168 · Cited by 287 · see citing works
Synaptic Background Activity Enhances the Responsiveness of Neocortical Pyramidal Neurons
Hô, N., & Destexhe, A. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.3.1488 · Cited by 281 · see citing works
Huguenard, J. R., Hamill, O. P., & Prince, D. A. (1988) · Journal of Neurophysiology · doi:10.1152/jn.1988.59.3.778 · Cited by 277 · see citing works
Dendritic morphology of pyramidal neurones of the visual cortex of the rat: III. Spine distributions
Larkman, A. U. (1991) · The Journal of Comparative Neurology · doi:10.1002/cne.903060209 · Cited by 274 · see citing works
Troyer, T. W., & Miller, K. D. (1997) · Neural Computation · doi:10.1162/neco.1997.9.5.971 · Cited by 246 · see citing works
Impact of Synaptic Unreliability on the Information Transmitted by Spiking Neurons
Zador, A. M. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.3.1219 · Cited by 242 · see citing works
Noise From Voltage-Gated Ion Channels May Influence Neuronal Dynamics in the Entorhinal Cortex
White, J. A., Klink, R., Alonso, Á., & Kay, A. R. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.262 · Cited by 237 · see citing works
Model of Transient Oscillatory Synchronization in the Locust Antennal Lobe
Bazhenov, M., Stopfer, M., Rabinovich, M. I., Huerta, R., Abarbanel, H. D. I., B, T. J. S. A., & Laurent, G. (2001) · Neuron · doi:10.1016/s0896-6273(01)00284-7 · Cited by 229 · see citing works
Stochastic resonance improves signal detection in hippocampal CA1 neurons.
Stacey, W. C., & Durand, D. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.83.3.1394 · Cited by 223 · see citing works
Nonsaturation of AMPA and NMDA receptors at hippocampal synapses
McAllister, A. K., & Stevens, C. F. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.100126497 · Cited by 219 · see citing works
Trial-to-Trial Variability and State-Dependent Modulation of Auditory-Evoked Responses in Cortex
Kisley, M. A., & Gerstein, G. L. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-23-10451.1999 · Cited by 193 · see citing works
Frequency Dependence of Spike Timing Reliability in Cortical Pyramidal Cells and Interneurons
Fellous, J., Houweling, A. R., Modi, R. H., Rao, R. P. N., Tiesinga, P. H. E., & B, T. J. S. A. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.85.4.1782 · Cited by 151 · see citing works
Self-citationNeuronal networks of the hippocampus
(1992) · Comparative Biochemistry and Physiology Part A Physiology · doi:10.1016/0300-9629(92)90749-g · Cited by 147 · see citing works
Synaptic Noise Improves Detection of Subthreshold Signals in Hippocampal CA1 Neurons
Stacey, W. C., & Durand, D. M. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.3.1104 · Cited by 142 · see citing works
Precise Firing Events Are Conserved across Neurons
Reinagel, P., & Reid, R. C. (2002) · Journal of Neuroscience · doi:10.1523/jneurosci.22-16-06837.2002 · Cited by 119 · see citing works
Tiesinga, P. H. E., José, J. V., & Sejnowski, T. J. (2000) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.62.8413 · Cited by 113 · see citing works
Self-citationJaeger, D., & Bower, J. M. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-14-06090.1999 · Cited by 113 · see citing works
Spike timing in the mammalian visual system
Bair, W. (1999) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(99)80067-1 · Cited by 99 · see citing works
Computational Models of Neuromodulation
Fellous, J., & Linster, C. (1998) · Neural Computation · doi:10.1162/089976698300017476 · Cited by 98 · see citing works
Self-citationOn the stochastic dynamics of neuronal interaction
Sejnowski, T. J. (1976) · Biological Cybernetics · doi:10.1007/bf00365086 · Cited by 85 · see citing works
Self-citationBerg, H. (1996) · Bioelectrochemistry and Bioenergetics · doi:10.1016/s0302-4598(96)90039-2 · Cited by 84 · see citing works
Correlation Detection and Resonance in Neural Systems with Distributed Noise Sources
Rudolph, M., & Destexhe, A. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.3662 · Cited by 75 · see citing works
Self-citationInfluence of Temporal Correlation of Synaptic Input on the Rate and Variability of Firing in Neurons
Svirskis, G., & Rinzel, J. (2000) · Biophysical Journal · doi:10.1016/s0006-3495(00)76321-1 · Cited by 72 · see citing works
Optimizing Synaptic Conductance Calculation for Network Simulations
Lytton, W. W. (1996) · Neural Computation · doi:10.1162/neco.1996.8.3.501 · Cited by 72 · see citing works
Hughes, S. W., Cope, D. W., & Crunelli, V. (1998) · Neuroscience · doi:10.1016/s0306-4522(98)00170-5 · Cited by 49 · see citing works
Voltage Offsets in Patch-Clamp Experiments
Neher, E. (1995) · Springer eBooks · doi:10.1007/978-1-4419-1229-9_6 · Cited by 48 · see citing works
Zador, A. M. (1999) · Neuron · doi:10.1016/s0896-6273(00)80770-9 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Faisal, A. A., Selen, L. P. J., & Wolpert, D. M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2258 · Cited by 2,883 · see citing works
The high-conductance state of neocortical neurons in vivo
Alain Destexhe, A., Rudolph, M., & Paré, D. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1198 · Cited by 1,077 · see citing works
Self-citationAttentional modulation of visual processing
Reynolds, J. H., & Chelazzi, L. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131039 · Cited by 1,158 · see citing works
What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
McDonnell, M. D., & Abbott, D. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000348 · Cited by 774 · see citing works
Dendritic Excitability and Synaptic Plasticity
Sjöström, P. J., Rancz, E. A., Roth, A., & Häusser, M. (2008) · Physiological Reviews · doi:10.1152/physrev.00016.2007 · Cited by 721 · see citing works
Cellular mechanisms of brain state-dependent gain modulation in visual cortex
Polack, P.-O., Friedman, J., & Golshani, P. (2013) · Nature Neuroscience · doi:10.1038/nn.3464 · Cited by 628 · see citing works
Silver, R. A. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2864 · Cited by 481 · see citing works
Imaging input and output of neocortical networks <i>in vivo</i>
Kerr, J. N. D., Greenberg, D., & Helmchen, F. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506029102 · Cited by 474 · see citing works
Mechanisms underlying gain modulation in the cortex
Ferguson, K. A., & Cardin, J. A. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0253-y · Cited by 327 · see citing works
Jarsky, T., Roxin, A., Kath, W. L., & Spruston, N. (2005) · Nature Neuroscience · doi:10.1038/nn1599 · Cited by 301 · see citing works
Barrages of Synaptic Activity Control the Gain and Sensitivity of Cortical Neurons
Shu, Y., Hasenstaub, A., Badoual, M., Bal, T., & McCormick, D. A. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-32-10388.2003 · Cited by 298 · see citing works
The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions
Neske, G. T. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2015.00088 · Cited by 283 · see citing works
Neuronal Computations with Stochastic Network States
Alain Destexhe, A., & Contreras, D. (2006) · Science · doi:10.1126/science.1127241 · Cited by 257 · see citing works
Molecular Components and Functions of the Endocannabinoid System in Mouse Prefrontal Cortex
Lafourcade, M., Elezgarai, I., Mato, S., Bakiri, Y., Grandes, P., & Manzoni, O. J. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000709 · Cited by 249 · see citing works
Synaptic depression enables neuronal gain control
Rothman, J. S., Cathala, L., Steuber, V., & Silver, R. A. (2009) · Nature · doi:10.1038/nature07604 · Cited by 243 · see citing works
State changes rapidly modulate cortical neuronal responsiveness
Hasenstaub, A., Sachdev, R. N. S., & McCormick, D. A. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.2184-07.2007 · Cited by 196 · see citing works
Persistent Cortical Activity: Mechanisms of Generation and Effects on Neuronal Excitability
McCormick, D. A. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg104 · Cited by 199 · see citing works
Stochastic Methods in Neuroscience
Alain Destexhe, A., & Rudolph, M. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199235070.001.0001 · Cited by 193 · see citing works
Self-citationAstrocytes convert network excitation to tonic inhibition of neurons
Héja, L., Nyitrai, G., Kékesi, O., Dobolyi, Á., Szabó, P. T., Fiáth, R., Ulbert, I., Pal-Szenthe, B., Palkovits, M., & Kardos, J. (2012) · BMC Biology · doi:10.1186/1741-7007-10-26 · Cited by 176 · see citing works
Liu, B.-H., Li, Y.-T., Ma, W.-P., Pan, C.-J., Zhang, L. I., & Tao, H. W. (2011) · Neuron · doi:10.1016/j.neuron.2011.06.017 · Cited by 173 · see citing works
Stochastic theory of nonequilibrium steady states and its applications. Part I
Zhang, X., Qian, H., & Qian, M. (2011) · Physics Reports · doi:10.1016/j.physrep.2011.09.002 · Cited by 173 · see citing works
Subthalamic Nucleus Deep Brain Stimulation: Basic Concepts and Novel Perspectives
Hamani, C., Florence, G., Heinsen, H., Plantinga, B. R., Temel, Y., Uludaǧ, K., Alho, E. J. L., Teixeira, M. J., Amaro, E., & Fonoff, E. T. (2017) · eNeuro · doi:10.1523/eneuro.0140-17.2017 · Cited by 169 · see citing works
Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex
DeWeese, M. R., & Zador, A. M. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.2813-06.2006 · Cited by 155 · see citing works
Inhibitory synchrony as a mechanism for attentional gain modulation
Tiesinga, P. H. E., Fellous, J., Salinas, E., José, J. V., & B, T. J. S. A. (2004) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2005.09.002 · Cited by 157 · see citing works
Self-citationEfficient Estimation of Detailed Single-Neuron Models
Huys, Q. J. M., Ahrens, M. B., & Paninski, L. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00079.2006 · Cited by 141 · see citing works
Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli
Siegle, J. H., Pritchett, D. L., & Moore, C. I. (2014) · Nature Neuroscience · doi:10.1038/nn.3797 · Cited by 139 · see citing works
Higgs, M. H., Slee, S. J., & Spain, W. J. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1792-06.2006 · Cited by 124 · see citing works
Pavlov, I., Savtchenko, L. P., Kullmann, D. M., Semyanov, A. V., & Walker, M. C. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.2747-09.2009 · Cited by 113 · see citing works
Attentional modulation of firing rate and synchrony in a model cortical network
Buia, C., & Tiesinga, P. H. E. (2006) · Journal of Computational Neuroscience · doi:10.1007/s10827-006-6358-0 · Cited by 112 · see citing works
Regulation of Irregular Neuronal Firing by Autaptic Transmission
Guo, D., Wu, S., Chen, M., Perc, M., Zhang, Y., Ma, J., Cui, Y., Xu, P., Xia, Y., & Yao, D. (2016) · Scientific Reports · doi:10.1038/srep26096 · Cited by 107 · see citing works
A Method to Estimate Synaptic Conductances From Membrane Potential Fluctuations
Rudolph, M., Piwkowska, Z., Badoual, M., Bal, T., & Alain Destexhe, A. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01223.2003 · Cited by 105 · see citing works
Self-citationIntrinsic Noise in Cultured Hippocampal Neurons: Experiment and Modeling
Diba, K., Lester, H. A., & Christof Koch, A. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.1721-04.2004 · Cited by 103 · see citing works
Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance
Richardson, M. J. E., & Gerstner, W. (2005) · Neural Computation · doi:10.1162/0899766053429444 · Cited by 101 · see citing works
Characterization of Subthreshold Voltage Fluctuations in Neuronal Membranes
Rudolph, M., & Alain Destexhe, A. (2003) · Neural Computation · doi:10.1162/089976603322385081 · Cited by 99 · see citing works
Self-citationConditional Bursting Enhances Resonant Firing in Neocortical Layer 2–3 Pyramidal Neurons
Higgs, M. H., & Spain, W. J. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.3728-08.2009 · Cited by 98 · see citing works
Beyond bistability: Biophysics and temporal dynamics of working memory
Durstewitz, D., & Seamans, J. K. (2005) · Neuroscience · doi:10.1016/j.neuroscience.2005.06.094 · Cited by 93 · see citing works
Ronesi, J. A., & Lovinger, D. M. (2004) · The Journal of Physiology · doi:10.1113/jphysiol.2004.068460 · Cited by 95 · see citing works
Cardin, J. A., Palmer, L. A., & Contreras, D. (2008) · Neuron · doi:10.1016/j.neuron.2008.05.002 · Cited by 90 · see citing works
Snapshots of the Brain in Action: Local Circuit Operations through the Lens of γ Oscillations
Cardin, J. A. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1021-16.2016 · Cited by 89 · see citing works
Cerebellar network plasticity: From genes to fast oscillation
Cheron, G. A., Servais, L., & Dan, B. (2008) · Neuroscience · doi:10.1016/j.neuroscience.2008.01.074 · Cited by 86 · see citing works
Gain modulation by serotonin in pyramidal neurones of the rat prefrontal cortex
Zhang, Z., & Arsenault, D. (2005) · The Journal of Physiology · doi:10.1113/jphysiol.2005.086066 · Cited by 82 · see citing works
Short-Term Synaptic Depression Causes a Non-Monotonic Response to Correlated Stimuli
de la Rocha, J., & Parga, N. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.0631-05.2005 · Cited by 80 · see citing works
Chaotic resonance in Hodgkin–Huxley neuron
Baysal, V., Saraç, Z., & Yılmaz, E. (2019) · Nonlinear Dynamics · doi:10.1007/s11071-019-05047-w · Cited by 78 · see citing works
For things needing your attention: the role of neocortical gamma in sensory perception
Pritchett, D. L., Siegle, J. H., Deister, C. A., & Moore, C. I. (2015) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.02.004 · Cited by 78 · see citing works
Florence, G., Sameshima, K., Fonoff, E. T., & Hamani, C. (2015) · The Neuroscientist · doi:10.1177/1073858415591964 · Cited by 77 · see citing works
Arsiero, M., Lüscher, H.-R., Lundstrom, B. N., & Giugliano, M. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.4937-06.2007 · Cited by 75 · see citing works
Rudolph, M., & Alain Destexhe, A. (2006) · Neural Computation · doi:10.1162/neco.2006.18.9.2146 · Cited by 76 · see citing works
Self-citationSingle Neuron Firing Properties Impact Correlation-Based Population Coding
Hong, S., Ratté, S., Prescott, S. A., & De Schutter, E. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3735-11.2012 · Cited by 72 · see citing works
Miura, K., Tsubo, Y., Okada, M., & Fukai, T. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2452-07.2007 · Cited by 72 · see citing works
Gain Modulation of Neuronal Responses by Subtractive and Divisive Mechanisms of Inhibition
Ayaz, A., & Chance, F. S. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90547.2008 · Cited by 72 · see citing works
Cellular mechanisms of temporal sensitivity in visual cortex neurons
Cardin, J. A., Kumbhani, R. D., Contreras, D., & Palmer, L. A. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5279-09.2010 · Cited by 62 · see citing works
Adermark, L., & Lovinger, D. M. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.3842-08.2009 · Cited by 71 · see citing works
Young, C. K., & Eggermont, J. (2009) · Progress in neurobiology · doi:10.1016/j.pneurobio.2009.06.002 · Cited by 74 · see citing works
Origin of intrinsic irregular firing in cortical interneurons
Stiefel, K. M., Englitz, B., & B, T. J. S. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1305219110 · Cited by 69 · see citing works
Mishra, J., Fellous, J., & B, T. J. S. A. (2006) · Neural Networks · doi:10.1016/j.neunet.2006.08.005 · Cited by 65 · see citing works
Self-citationVoltage Fluctuations in Neurons: Signal or Noise?
Yarom, Y., & Hounsgaard, J. (2011) · Physiological Reviews · doi:10.1152/physrev.00019.2010 · Cited by 65 · see citing works
Gansel, K. S. (2022) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2022.900715 · Cited by 62 · see citing works
Synchronization as a mechanism for attentional gain modulation
Tiesinga, P. H. E., Fellous, J., Salinas, E., José, J. V., & B, T. J. S. A. (2004) · Neurocomputing · doi:10.1016/j.neucom.2004.01.108 · Cited by 56 · see citing works
Self-citationInteracting Particle Solutions of Fokker–Planck Equations Through Gradient–Log–Density Estimation
Maoutsa, D., Reich, S., & Opper, M. (2020) · Entropy · doi:10.3390/e22080802 · Cited by 55 · see citing works
Sensitivity to theta-burst timing permits LTP in dorsal striatal adult brain slice
Hawes, S., Gillani, F., Evans, R. C., Benkert, E. A., & Blackwell, K. T. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00115.2013 · Cited by 49 · see citing works
Dynamic Clamp Analyses of Cardiac, Endocrine, and Neural Function
Goaillard, J., & Marder, E. E. (2006) · Physiology · doi:10.1152/physiol.00063.2005 · Cited by 54 · see citing works
Lundstrom, B. N., Famulare, M., Sorensen, L. B., Spain, W. J., & Fairhall, A. L. (2009) · Journal of Computational Neuroscience · doi:10.1007/s10827-009-0142-x · Cited by 53 · see citing works
Spike Resonance Properties in Hippocampal O-LM Cells Are Dependent on Refractory Dynamics
Kispersky, T. J., Fernandez, F. R., Economo, M. N., & White, J. A. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.1361-11.2012 · Cited by 52 · see citing works
Mechanisms of Functional Hypoconnectivity in the Medial Prefrontal Cortex ofMecp2Null Mice
Sceniak, M. P., Lang, M., Enomoto, A. C., Howell, C., Hermes, D. J., & Katz, D. M. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv002 · Cited by 53 · see citing works
Impacts of autapse on chaotic resonance in single neurons and small-world neuronal networks
Baysal, V., Erkan, E., & Yılmaz, E. (2021) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0237 · Cited by 53 · see citing works
Neuromorphic applications in medicine
Aboumerhi, K., Güemes, A., Liu, H., Tenore, F. V., & Etienne‐Cummings, R. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/aceca3 · Cited by 50 · see citing works
Mejías, J. F., & Torres, J. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017255 · Cited by 50 · see citing works
Gain Control in CA1 Pyramidal Cells Using Changes in Somatic Conductance
Fernandez, F. R., & White, J. A. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.3995-09.2010 · Cited by 47 · see citing works
Intrinsic Mechanisms for Adaptive Gain Rescaling in Barrel Cortex
Díaz-Quesada, M., & Maravall, M. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.4931-07.2008 · Cited by 48 · see citing works
Temporal pattern separation in hippocampal neurons through multiplexed neural codes
Madar, A. D., Ewell, L. A., & Jones, M. V. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006932 · Cited by 48 · see citing works
Stochastic resonance in a locally excited system of bistable oscillators
Gosak, M., Perc, M., & Kralj, S. (2011) · The European Physical Journal B · doi:10.1140/epjb/e2011-10573-8 · Cited by 47 · see citing works
Some Insights Into Computational Models of (Patho)physiological Brain Activity
Suffczyński, P., Wendling, F., Bellanger, J.-J., & Lopes, F. H. D. S. (2006) · Proceedings of the IEEE · doi:10.1109/jproc.2006.871773 · Cited by 47 · see citing works
Generation of Sharp Wave-Ripple Events by Disinhibition
Evangelista, R., Cano, G., Cooper, C., Schmitz, D., Maier, N., & Kempter, R. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.2174-19.2020 · Cited by 46 · see citing works
Piwkowska, Z., Pospischil, M., Brette, R., Sliwa, J., Rudolph, M., Bal, T., & Alain Destexhe, A. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.11.010 · Cited by 47 · see citing works
Self-citationFellous, J. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg098 · Cited by 47 · see citing works
Self-citationFernandez, F. R., Broicher, T., Truong, A., & White, J. A. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5076-10.2011 · Cited by 44 · see citing works
Dynamic Spatiotemporal Synaptic Integration in Cortical Neurons: Neuronal Gain, Revisited
Azouz, R. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00542.2005 · Cited by 43 · see citing works
Tsubo, Y., Isomura, Y., & Fukai, T. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002461 · Cited by 43 · see citing works
Farinella, M., Ruedt, D. T., Gleeson, P., Lanore, F., & Silver, R. A. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003590 · Cited by 50 · see citing works
The Dyslexia-Associated Gene Dcdc2 Is Required for Spike-Timing Precision in Mouse Neocortex
Che, A., Girgenti, M. J., & LoTurco, J. J. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.08.018 · Cited by 41 · see citing works
Background Synaptic Conductance and Precision of EPSP-Spike Coupling at Pyramidal Cells
Zsiros, V., & Hestrin, S. (2005) · Journal of Neurophysiology · doi:10.1152/jn.01027.2004 · Cited by 41 · see citing works
Extracting Information from the Power Spectrum of Synaptic Noise
Alain Destexhe, A., & Rudolph, M. (2004) · Journal of Computational Neuroscience · doi:10.1023/b:jcns.0000044875.90630.88 · Cited by 40 · see citing works
Self-citationLundstrom, B. N., Hong, S., Higgs, M. H., & Fairhall, A. L. (2008) · Neural Computation · doi:10.1162/neco.2007.05-07-536 · Cited by 39 · see citing works
Tamás, G., Szabadics, J., Lörincz, A., & Somogyi, P. (2004) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2004.03719.x · Cited by 39 · see citing works
Björefeldt, A., Andréasson, U., Daborg, J., Riebe, I., Wasling, P., Zetterberg, H., & Hanse, E. (2014) · The Journal of Physiology · doi:10.1113/jphysiol.2014.284711 · Cited by 38 · see citing works
Neuromorphic meets neuromechanics, part I: the methodology and implementation
Niu, C. M., Jalaleddini, K., Sohn, W. J., Rocamora, J., Sanger, T. D., & Valero‐Cuevas, F. J. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa593c · Cited by 38 · see citing works
Enhanced Responsiveness and Low-Level Awareness in Stochastic Network States
Zerlaut, Y., & Alain Destexhe, A. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.001 · Cited by 37 · see citing works
Intrinsic Gain Modulation and Adaptive Neural Coding
Hong, S., Lundstrom, B. N., & Fairhall, A. L. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000119 · Cited by 38 · see citing works
Corner, M. A. (2008) · Brain Research Reviews · doi:10.1016/j.brainresrev.2008.08.001 · Cited by 37 · see citing works
Powers, R. K., Dai, Y., Bell, B. M., Percival, D. B., & Binder, M. D. (2004) · The Journal of Physiology · doi:10.1113/jphysiol.2004.069039 · Cited by 37 · see citing works
State Dependence of Network Output: Modeling and Experiments
Farzan Nadim, A., Březina, V., Alain Destexhe, A., & Linster, C. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.3796-08.2008 · Cited by 36 · see citing works
Li, Y., Fan, S., Yan, J. Y., Li, B., Chen, F., Xia, J., Yu, Z., & Hu, Z. (2010) · Hippocampus · doi:10.1002/hipo.20745 · Cited by 35 · see citing works
Synaptic Bombardment Modulates Muscarinic Effects in Forelimb Motor Cortex
Desai, N. S., & Walcott, E. C. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.4310-05.2006 · Cited by 34 · see citing works
Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?
Keck, C., Savin, C., & Lücke, J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002432 · Cited by 32 · see citing works
Rice, A. D., Fuglevand, A. J., Laine, C. M., & Fregosi, R. F. (2011) · Journal of Neurophysiology · doi:10.1152/jn.01078.2010 · Cited by 33 · see citing works
Özer, M., & Uzuntarla, M. (2008) · Physics Letters A · doi:10.1016/j.physleta.2008.05.003 · Cited by 33 · see citing works
Kovalsky, Y., Amir, R., & Devor, M. G. (2007) · Experimental Neurology · doi:10.1016/j.expneurol.2007.10.018 · Cited by 32 · see citing works
Richardson, M. J. E., & Gerstner, W. (2006) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.2203409 · Cited by 32 · see citing works
Stimulus Competition by Inhibitory Interference
Tiesinga, P. H. E. (2005) · Neural Computation · doi:10.1162/0899766054796905 · Cited by 32 · see citing works
Wang, W., Darvas, M., Storey, G. P., Bamford, I. J., Gibbs, J. T., Palmiter, R. D., & Bamford, N. S. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0014-13.2013 · Cited by 30 · see citing works
- Authors
- Fellous, J.-M., Rudolph, M., Destexhe, A., & Sejnowski, T. J.
- Affiliations
- Salk Institute for Biological Studies (US)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Fellous, J.-M
- ORCID
- Fellous, J.-M
- Venue
- Neuroscience
- Publisher
- Elsevier BV
- Published
- 2003-01
- Volume
- 122
- Issue
- 3
- Pages
- 811-829
- ISSN
- 0306-4522 (ISSN-L)
- PMC
- PMC2928821
- OpenAlex
- W2125421120
- Cited by
- 273
- References
- 72
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 6 · 2023: 7 · 2022: 9 · 2021: 4 · 2020: 7 · 2019: 10 · 2018: 9 · 2017: 11 · 2016: 7 · 2015: 10 · 2014: 10 · 2013: 15 · 2012: 16
- FWCI
- 7.98
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Keywords
- neocortical neurons, prefrontal cortex, layer 5 neurons, Ornstein-Uhlenbeck process, input resistance, firing rate, membrane potential fluctuations, dynamic clamp
- MeSH terms
- Animals, Computer Simulation, Membrane Potentials, Models, Neurological, Neural Conduction, Neural Inhibition, Synaptic Transmission, Neurons, Probability, Synapses, Time Factors, Electric Impedance, Rats, Sprague-Dawley, Patch-Clamp Techniques, Neocortex, Rats, In Vitro Techniques
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review