The mechanics of state-dependent neural correlations
暂无分享,去创建一个
Brent Doiron | Robert Rosenbaum | Ashok Litwin-Kumar | Krešimir Josić | Gabriel K Ocker | A. Litwin-Kumar | B. Doiron | K. Josić | G. K. Ocker | R. Rosenbaum | Ashok Litwin-Kumar | Brent Doiron
[1] M. Tsodyks,et al. Working models of working memory , 2014, Current Opinion in Neurobiology.
[2] C. Petersen,et al. Cholinergic signals in mouse barrel cortex during active whisker sensing. , 2014, Cell reports.
[3] Kenneth D Miller,et al. Processing in layer 4 of the neocortical circuit: new insights from visual and somatosensory cortex , 2001, Current Opinion in Neurobiology.
[4] George H. Denfield,et al. Pupil Fluctuations Track Fast Switching of Cortical States during Quiet Wakefulness , 2014, Neuron.
[5] H. Sompolinsky,et al. Theory of orientation tuning in visual cortex. , 1995, Proceedings of the National Academy of Sciences of the United States of America.
[6] Benjamin Lindner,et al. Spike-count distribution in a neuronal population under weak common stimulation. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[7] Fred Wolf,et al. Correlations and synchrony in threshold neuron models. , 2008, Physical review letters.
[8] Henry Markram,et al. Coding of temporal information by activity-dependent synapses. , 2002, Journal of neurophysiology.
[9] Dmitry R Lyamzin,et al. Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks , 2015, The Journal of Neuroscience.
[10] Maurice J. Chacron,et al. Activation of Parallel Fiber Feedback by Spatially Diffuse Stimuli Reduces Signal and Noise Correlations via Independent Mechanisms in a Cerebellum-Like Structure , 2015, PLoS Comput. Biol..
[11] D. Vere-Jones. SIMPLE STOCHASTIC MODELS FOR THE RELEASE OF QUANTA OF TRANSMITTER FROM A NERVE TERMINAL , 1966 .
[12] D. W. Wheeler,et al. Brightness Induction: Rate Enhancement and Neuronal Synchronization as Complementary Codes , 2006, Neuron.
[13] Jessica A. Cardin,et al. Cellular Mechanisms Underlying Stimulus-Dependent Gain Modulation in Primary Visual Cortex Neurons In Vivo , 2008, Neuron.
[14] Haim Sompolinsky,et al. Chaotic Balanced State in a Model of Cortical Circuits , 1998, Neural Computation.
[15] Srdjan Ostojic,et al. Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons , 2014, Nature Neuroscience.
[16] John Hertz,et al. Cross-Correlations in High-Conductance States of a Model Cortical Network , 2010, Neural Computation.
[17] D. Ferster,et al. Neural mechanisms of orientation selectivity in the visual cortex. , 2000, Annual review of neuroscience.
[18] B. Doiron,et al. Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations. , 2013, Journal of neurophysiology.
[19] Alexander S. Ecker,et al. The Effect of Noise Correlations in Populations of Diversely Tuned Neurons , 2011, The Journal of Neuroscience.
[20] Xiao-Jing Wang,et al. The importance of mixed selectivity in complex cognitive tasks , 2013, Nature.
[21] Nicolas Fourcaud-Trocmé,et al. Correlation-induced Synchronization of Oscillations in Olfactory Bulb Neurons , 2022 .
[22] Kenneth D Harris,et al. Stochastic transitions into silence cause noise correlations in cortical circuits , 2015, Proceedings of the National Academy of Sciences.
[23] K. Svoboda,et al. Genetic Dissection of Neural Circuits , 2008, Neuron.
[24] W. Newsome,et al. The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.
[25] Ovidiu F. Jurjuţ,et al. Effects of Locomotion Extend throughout the Mouse Early Visual System , 2014, Current Biology.
[26] Valentin Dragoi,et al. Correlated Variability in Laminar Cortical Circuits , 2012, Neuron.
[27] K. Harris,et al. Cortical state and attention , 2011, Nature Reviews Neuroscience.
[28] Stefan Rotter,et al. How Structure Determines Correlations in Neuronal Networks , 2011, PLoS Comput. Biol..
[29] D. Hubel,et al. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.
[30] Mark S. Goldman,et al. Enhancement of Information Transmission Efficiency by Synaptic Failures , 2004, Neural Computation.
[31] Wulfram Gerstner,et al. Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition , 2014 .
[32] A. Pouget,et al. Neural correlations, population coding and computation , 2006, Nature Reviews Neuroscience.
[33] P. J. Sjöström,et al. Functional specificity of local synaptic connections in neocortical networks , 2011, Nature.
[34] Brent Doiron,et al. The Spatial Structure of Stimuli Shapes the Timescale of Correlations in Population Spiking Activity , 2012, PLoS Comput. Biol..
[35] Henry Markram,et al. Neural Networks with Dynamic Synapses , 1998, Neural Computation.
[36] Jude F. Mitchell,et al. Spatial Attention Decorrelates Intrinsic Activity Fluctuations in Macaque Area V4 , 2009, Neuron.
[37] Mauricio Barahona,et al. Emergence of Slow-Switching Assemblies in Structured Neuronal Networks , 2015, PLoS Comput. Biol..
[38] Mamiko Niwa,et al. Task Engagement Selectively Modulates Neural Correlations in Primary Auditory Cortex , 2015, The Journal of Neuroscience.
[39] Eric Shea-Brown,et al. Time scales of spike-train correlation for neural oscillators with common drive. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[40] R. Romo,et al. Correlated Neuronal Discharges that Increase Coding Efficiency during Perceptual Discrimination , 2003, Neuron.
[41] R. Guillery,et al. On the actions that one nerve cell can have on another: distinguishing "drivers" from "modulators". , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[42] Eric Shea-Brown,et al. Impact of Network Structure and Cellular Response on Spike Time Correlations , 2011, PLoS Comput. Biol..
[43] Randy M Bruno,et al. Feedforward Mechanisms of Excitatory and Inhibitory Cortical Receptive Fields , 2002, The Journal of Neuroscience.
[44] A. Litwin-Kumar,et al. Slow dynamics and high variability in balanced cortical networks with clustered connections , 2012, Nature Neuroscience.
[45] Byron M. Yu,et al. Dimensionality reduction for large-scale neural recordings , 2014, Nature Neuroscience.
[46] D. Hansel,et al. How Noise Contributes to Contrast Invariance of Orientation Tuning in Cat Visual Cortex , 2002, The Journal of Neuroscience.
[47] J. Poulet,et al. Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice , 2008, Nature.
[48] Moritz Helias,et al. Correlations in spiking neuronal networks with distance dependent connections , 2009, Journal of Computational Neuroscience.
[49] Guangying K. Wu,et al. Defining cortical frequency tuning with recurrent excitatory circuitry , 2007, Nature Neuroscience.
[50] Robert E. Kass,et al. Spike Count Correlation Increases with Length of Time Interval in the Presence of Trial-to-Trial Variation , 2006, Neural Computation.
[51] M. Carandini. Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex , 2004, PLoS biology.
[52] Cheng Ly,et al. Cellular and Circuit Mechanisms Maintain Low Spike Co-Variability and Enhance Population Coding in Somatosensory Cortex , 2012, Front. Comput. Neurosci..
[53] Brent Doiron,et al. Subtractive and Divisive Inhibition: Effect of Voltage-Dependent Inhibitory Conductances and Noise , 2001, Neural Computation.
[54] M. A. Smith,et al. Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex , 2008, The Journal of Neuroscience.
[55] Shawn D. Burton,et al. Impact of neuronal heterogeneity on correlated colored noise-induced synchronization , 2013, Front. Comput. Neurosci..
[56] Timothy D. Hanks,et al. Probabilistic Population Codes for Bayesian Decision Making , 2008, Neuron.
[57] David Hansel,et al. Asynchronous Rate Chaos in Spiking Neuronal Circuits , 2015, bioRxiv.
[58] N. Parga,et al. Short-term Synaptic Depression Causes a Non-monotonic Response to Correlated Stimuli , 2022 .
[59] Valentin Dragoi,et al. Adaptive coding of visual information in neural populations , 2008, Nature.
[60] A. Pouget,et al. Information-limiting correlations , 2014, Nature Neuroscience.
[61] Brent Doiron,et al. Short Term Synaptic Depression Imposes a Frequency Dependent Filter on Synaptic Information Transfer , 2012, PLoS Comput. Biol..
[62] David Ferster,et al. Membrane Potential Synchrony in Primary Visual Cortex during Sensory Stimulation , 2010, Neuron.
[63] Olivier Ledoit,et al. A well-conditioned estimator for large-dimensional covariance matrices , 2004 .
[64] Robert Desimone,et al. Lesions of prefrontal cortex reduce attentional modulation of neuronal responses and synchrony in V4 , 2014, Nature Neuroscience.
[65] B. Ermentrout. Neural networks as spatio-temporal pattern-forming systems , 1998 .
[66] Ad Aertsen,et al. Role of Input Correlations in Shaping the Variability and Noise Correlations of Evoked Activity in the Neocortex , 2015, The Journal of Neuroscience.
[67] Yu Hu,et al. The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes , 2013, PLoS Comput. Biol..
[68] G A Cecchi,et al. Noise in neurons is message dependent. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[69] Brent Doiron,et al. Kv7 channels regulate pairwise spiking covariability in health and disease. , 2014, Journal of neurophysiology.
[70] Sungho Hong,et al. Single Neuron Firing Properties Impact Correlation-Based Population Coding , 2012, The Journal of Neuroscience.
[71] Lief E. Fenno,et al. The development and application of optogenetics. , 2011, Annual review of neuroscience.
[72] Konrad P Kording,et al. How advances in neural recording affect data analysis , 2011, Nature Neuroscience.
[73] Eero P. Simoncelli,et al. Partitioning neuronal variability , 2014, Nature Neuroscience.
[74] Nicholas J. Priebe,et al. Inhibition, Spike Threshold, and Stimulus Selectivity in Primary Visual Cortex , 2008, Neuron.
[75] Robert Rosenbaum,et al. Mechanisms That Modulate the Transfer of Spiking Correlations , 2011, Neural Computation.
[76] Brent Doiron,et al. Balanced neural architecture and the idling brain , 2014, Front. Comput. Neurosci..
[77] D. McCormick,et al. Waking State: Rapid Variations Modulate Neural and Behavioral Responses , 2015, Neuron.
[78] Sompolinsky,et al. Theory of correlations in stochastic neural networks. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[79] Haim Sompolinsky,et al. Stimulus-Dependent Correlations in Threshold-Crossing Spiking Neurons , 2009, Neural Computation.
[80] J T Rubinstein,et al. Threshold fluctuations in an N sodium channel model of the node of Ranvier. , 1995, Biophysical journal.
[81] Martin Vinck,et al. Arousal and Locomotion Make Distinct Contributions to Cortical Activity Patterns and Visual Encoding , 2014, Neuron.
[82] Yong Gu,et al. Perceptual Learning Reduces Interneuronal Correlations in Macaque Visual Cortex , 2011, Neuron.
[83] Yuzhi Chen,et al. Sensory stimulation shifts visual cortex from synchronous to asynchronous states , 2014, Nature.
[84] Néstor Parga,et al. ournal of Statistical Mechanics : J Theory and Experiment Towards a self-consistent description of irregular and asynchronous cortical activity , 2013 .
[85] Brent Doiron,et al. Neural Correlation Is Stimulus Modulated by Feedforward Inhibitory Circuitry , 2012, The Journal of Neuroscience.
[86] Alexander Thiele,et al. Attention-Induced Variance and Noise Correlation Reduction in Macaque V1 Is Mediated by NMDA Receptors , 2013, Neuron.
[87] Moritz Helias,et al. Decorrelation of Neural-Network Activity by Inhibitory Feedback , 2012, PLoS Comput. Biol..
[88] Tai Sing Lee,et al. Local field potentials indicate network state and account for neuronal response variability , 2010, Journal of Computational Neuroscience.
[89] P. Dayan,et al. Supporting Online Material Materials and Methods Som Text Figs. S1 to S9 References the Asynchronous State in Cortical Circuits , 2022 .
[90] Jaime de la Rocha,et al. Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ , 2007 .
[91] Nicolas Brunel,et al. Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates , 1999, Neural Computation.
[92] W. Bair,et al. Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior , 2001, The Journal of Neuroscience.
[93] Brent Doiron,et al. Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[94] Nathaniel N. Urban,et al. Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains , 2011, PLoS Comput. Biol..
[95] L. Pinneo. On noise in the nervous system. , 1966, Psychological review.
[96] Alex D. Bird,et al. Long-term plasticity determines the postsynaptic response to correlated afferents with multivesicular short-term synaptic depression , 2014, BMC Neuroscience.
[97] W. Regehr,et al. Short-term synaptic plasticity. , 2002, Annual review of physiology.
[98] J. White,et al. Channel noise in neurons , 2000, Trends in Neurosciences.
[99] A. Destexhe,et al. Synaptic background activity enhances the responsiveness of neocortical pyramidal neurons. , 2000, Journal of neurophysiology.
[100] Xiao-Jing Wang,et al. What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. , 2003, Journal of neurophysiology.
[101] Ronen Segev,et al. A thesaurus for a neural population code , 2015, eLife.
[102] G. Ermentrout,et al. Gamma rhythms and beta rhythms have different synchronization properties. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[103] György Buzsáki,et al. Neural Syntax: Cell Assemblies, Synapsembles, and Readers , 2010, Neuron.
[104] M. Carandini,et al. The Nature of Shared Cortical Variability , 2015, Neuron.
[105] L Schimansky-Geier,et al. Transmission of noise coded versus additive signals through a neuronal ensemble. , 2001, Physical review letters.
[106] Suchin S. Gururangan,et al. Analysis of Graph Invariants in Functional Neocortical Circuitry Reveals Generalized Features Common to Three Areas of Sensory Cortex , 2014, PLoS Comput. Biol..
[107] Néstor Parga,et al. Auto- and crosscorrelograms for the spike response of leaky integrate-and-fire neurons with slow synapses. , 2006, Physical review letters.
[108] Christos Constantinidis,et al. Correlated discharges in the primate prefrontal cortex before and after working memory training , 2012, The European journal of neuroscience.
[109] Eero P. Simoncelli,et al. Spatio-temporal correlations and visual signalling in a complete neuronal population , 2008, Nature.
[110] R. Shapley,et al. New perspectives on the mechanisms for orientation selectivity , 1997, Current Opinion in Neurobiology.
[111] Nicholas J. Priebe,et al. Direction Selectivity of Excitation and Inhibition in Simple Cells of the Cat Primary Visual Cortex , 2005, Neuron.
[112] Y. Dan,et al. Neuromodulation of Brain States , 2012, Neuron.
[113] Maurice J Chacron,et al. Population coding by electrosensory neurons. , 2008, Journal of neurophysiology.
[114] A. Zador,et al. Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex , 2003, Nature.
[115] J. Schiller,et al. Dynamics of Excitability over Extended Timescales in Cultured Cortical Neurons , 2010, The Journal of Neuroscience.
[116] Matteo Carandini,et al. Five key factors determining pairwise correlations in visual cortex , 2015, Journal of neurophysiology.
[117] S. Prescott,et al. Gain control of firing rate by shunting inhibition: Roles of synaptic noise and dendritic saturation , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[118] Alexander S. Ecker,et al. Decorrelated Neuronal Firing in Cortical Microcircuits , 2010, Science.
[119] Robert Rosenbaum,et al. The Effects of Pooling on Spike Train Correlations , 2011, Front. Neurosci..
[120] Brent Doiron,et al. Oscillatory activity in electrosensory neurons increases with the spatial correlation of the stochastic input stimulus. , 2004, Physical review letters.
[121] Adam Kohn,et al. Correlations in V1 Are Reduced by Stimulation Outside the Receptive Field , 2014, The Journal of Neuroscience.
[122] David A Markowitz,et al. Rate-specific synchrony: Using noisy oscillations to detect equally active neurons , 2008, Proceedings of the National Academy of Sciences.
[123] Eric Shea-Brown,et al. Correlation and synchrony transfer in integrate-and-fire neurons: basic properties and consequences for coding. , 2008, Physical review letters.
[124] L. Abbott,et al. Neural network dynamics. , 2005, Annual review of neuroscience.
[125] Alexander S. Ecker,et al. State Dependence of Noise Correlations in Macaque Primary Visual Cortex , 2014, Neuron.
[126] T. Branco,et al. The probability of neurotransmitter release: variability and feedback control at single synapses , 2009, Nature Reviews Neuroscience.
[127] D. McCormick,et al. Neocortical Network Activity In Vivo Is Generated through a Dynamic Balance of Excitation and Inhibition , 2006, The Journal of Neuroscience.
[128] Pulin Gong,et al. Propagating Waves Can Explain Irregular Neural Dynamics , 2015, The Journal of Neuroscience.
[129] W. Newsome,et al. Context-Dependent Changes in Functional Circuitry in Visual Area MT , 2008, Neuron.
[130] Dario L. Ringach,et al. Dynamics of orientation tuning in macaque primary visual cortex , 1997, Nature.
[132] Nicolas Brunel,et al. How Connectivity, Background Activity, and Synaptic Properties Shape the Cross-Correlation between Spike Trains , 2009, The Journal of Neuroscience.
[133] Naoshige Uchida,et al. Odor Representations in Olfactory Cortex: Distributed Rate Coding and Decorrelated Population Activity , 2012, Neuron.
[134] Lisa M. Giocomo,et al. Computational Models of Grid Cells , 2011, Neuron.
[135] M. Cohen,et al. Measuring and interpreting neuronal correlations , 2011, Nature Neuroscience.
[136] Michael Okun,et al. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities , 2008, Nature Neuroscience.
[137] Frances S. Chance,et al. Gain Modulation from Background Synaptic Input , 2002, Neuron.
[138] Andrew M. Clark,et al. Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.
[139] R. Yuste. From the neuron doctrine to neural networks , 2015, Nature Reviews Neuroscience.
[140] Michael Graupner,et al. Synaptic Input Correlations Leading to Membrane Potential Decorrelation of Spontaneous Activity in Cortex , 2013, The Journal of Neuroscience.
[141] J. Maunsell,et al. Attention improves performance primarily by reducing interneuronal correlations , 2009, Nature Neuroscience.
[142] Bard Ermentrout,et al. Correlation transfer in stochastically driven neural oscillators over long and short time scales. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.
[143] Timothy Q. Gentner,et al. Associative Learning Enhances Population Coding by Inverting Interneuronal Correlation Patterns , 2013, Neuron.
[144] Douglas A Ruff,et al. Attention can increase or decrease spike count correlations between pairs of neurons depending on their role in a task , 2014, Nature Neuroscience.
[145] Brent Doiron,et al. Correlated neural variability in persistent state networks , 2012, Proceedings of the National Academy of Sciences.
[146] A. Aertsen,et al. Spike synchronization and rate modulation differentially involved in motor cortical function. , 1997, Science.
[147] L. Maler,et al. Inhibition evoked from primary afferents in the electrosensory lateral line lobe of the weakly electric fish (Apteronotus leptorhynchus). , 1998, Journal of neurophysiology.
[148] Moritz Helias,et al. The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics , 2013, PLoS Comput. Biol..
[149] Alexander S. Ecker,et al. Improved Estimation and Interpretation of Correlations in Neural Circuits , 2015, PLoS Comput. Biol..