Irregular spiking of pyramidal neurons organizes as scale-invariant neuronal avalanches in the awake state
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[1] T. E. Harris,et al. The Theory of Branching Processes. , 1963 .
[2] T. E. Harris,et al. The Theory of Branching Processes. , 1963 .
[3] H. L. Bryant,et al. Spike initiation by transmembrane current: a white‐noise analysis. , 1976, The Journal of physiology.
[4] M. V. Rossum,et al. In Neural Computation , 2022 .
[5] TJ Gawne,et al. How independent are the messages carried by adjacent inferior temporal cortical neurons? , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[6] A Aertsen,et al. Current Source Density Profiles of Optical Recording Maps: a New Approach to the Analysis of Spatio‐temporal Neural Activity Patterns , 1993, The European journal of neuroscience.
[7] William R. Softky,et al. The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[8] Dan-Mei Chen,et al. Self-organized criticality in a cellular automaton model of pulse-coupled integrate-and-fire neurons , 1995 .
[9] T. Sejnowski,et al. Reliability of spike timing in neocortical neurons. , 1995, Science.
[10] A. Grinvald,et al. Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses , 1996, Science.
[11] H. Sompolinsky,et al. Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity , 1996, Science.
[12] C. Stevens,et al. Input synchrony and the irregular firing of cortical neurons , 1998, Nature Neuroscience.
[13] W. Newsome,et al. The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.
[14] Shimon Marom,et al. Interaction between Duration of Activity and Time Course of Recovery from Slow Inactivation in Mammalian Brain Na+Channels , 1998, The Journal of Neuroscience.
[15] Nicolas Brunel,et al. Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons , 2000, Journal of Physiology-Paris.
[16] Maria V. Sanchez-Vives,et al. Cellular and network mechanisms of rhythmic recurrent activity in neocortex , 2000, Nature Neuroscience.
[17] 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.
[18] N. Nakatsuji,et al. Efficient gene transfer into the embryonic mouse brain using in vivo electroporation. , 2001, Developmental biology.
[19] J. Sethna,et al. Crackling noise , 2001, Nature.
[20] K. Linkenkaer-Hansen,et al. Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations , 2001, The Journal of Neuroscience.
[21] J. Sethna,et al. Crackling noise : Complex systems , 2001 .
[22] J. M. Herrmann,et al. Finite-size effects of avalanche dynamics. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[23] R. Yuste,et al. Attractor dynamics of network UP states in the neocortex , 2003, Nature.
[24] John M. Beggs,et al. Neuronal Avalanches in Neocortical Circuits , 2003, The Journal of Neuroscience.
[25] Nils Bertschinger,et al. Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks , 2004, Neural Computation.
[26] A. Miyawaki,et al. Expanded dynamic range of fluorescent indicators for Ca(2+) by circularly permuted yellow fluorescent proteins. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[27] Yuji Ikegaya,et al. Synfire Chains and Cortical Songs: Temporal Modules of Cortical Activity , 2004, Science.
[28] John M. Beggs,et al. Behavioral / Systems / Cognitive Neuronal Avalanches Are Diverse and Precise Activity Patterns That Are Stable for Many Hours in Cortical Slice Cultures , 2004 .
[29] M. Greicius,et al. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.
[30] Tetsuichiro Saito. In vivo electroporation in the embryonic mouse central nervous system , 2006, Nature Protocols.
[31] D. Plenz,et al. Inverted-U Profile of Dopamine–NMDA-Mediated Spontaneous Avalanche Recurrence in Superficial Layers of Rat Prefrontal Cortex , 2006, The Journal of Neuroscience.
[32] A. Pouget,et al. Neural correlations, population coding and computation , 2006, Nature Reviews Neuroscience.
[33] O. Kinouchi,et al. Optimal dynamical range of excitable networks at criticality , 2006, q-bio/0601037.
[34] D. Plenz,et al. The organizing principles of neuronal avalanches: cell assemblies in the cortex? , 2007, Trends in Neurosciences.
[35] David S. Greenberg,et al. Spatial Organization of Neuronal Population Responses in Layer 2/3 of Rat Barrel Cortex , 2007, The Journal of Neuroscience.
[36] V. Torre,et al. On the Dynamics of the Spontaneous Activity in Neuronal Networks , 2007, PloS one.
[37] M. Fox,et al. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.
[38] J. M. Herrmann,et al. Dynamical synapses causing self-organized criticality in neural networks , 2007, 0712.1003.
[39] K. Svoboda,et al. The Functional Microarchitecture of the Mouse Barrel Cortex , 2007, Neuroscience Research.
[40] S. Kauffman,et al. Measures for information propagation in Boolean networks , 2007 .
[41] Viola Priesemann,et al. Subsampling effects in neuronal avalanche distributions recorded in vivo , 2009, BMC Neuroscience.
[42] A. Aertsen,et al. Conditions for Propagating Synchronous Spiking and Asynchronous Firing Rates in a Cortical Network Model , 2008, The Journal of Neuroscience.
[43] David S. Greenberg,et al. Population imaging of ongoing neuronal activity in the visual cortex of awake rats , 2008, Nature Neuroscience.
[44] D. Plenz,et al. Homeostasis of neuronal avalanches during postnatal cortex development in vitro , 2008, Journal of Neuroscience Methods.
[45] Damian J. Wallace,et al. Single-spike detection in vitro and in vivo with a genetic Ca2+ sensor , 2008, Nature Methods.
[46] L. L. Bologna,et al. Self-organization and neuronal avalanches in networks of dissociated cortical neurons , 2008, Neuroscience.
[47] J. Poulet,et al. Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice , 2008, Nature.
[48] Ilya Shmulevich,et al. Critical networks exhibit maximal information diversity in structure-dynamics relationships. , 2008, Physical review letters.
[49] D. Plenz,et al. Neuronal avalanches organize as nested theta- and beta/gamma-oscillations during development of cortical layer 2/3 , 2008, Proceedings of the National Academy of Sciences.
[50] Biyu J. He,et al. Electrophysiological correlates of the brain's intrinsic large-scale functional architecture , 2008, Proceedings of the National Academy of Sciences.
[51] Takeshi Kaneko,et al. Recurrent Infomax Generates Cell Assemblies, Neuronal Avalanches, and Simple Cell-Like Selectivity , 2009, Neural Computation.
[52] Woodrow L. Shew,et al. Neuronal Avalanches Imply Maximum Dynamic Range in Cortical Networks at Criticality , 2009, The Journal of Neuroscience.
[53] L. F. Abbott,et al. Generating Coherent Patterns of Activity from Chaotic Neural Networks , 2009, Neuron.
[54] Mark E. J. Newman,et al. Power-Law Distributions in Empirical Data , 2007, SIAM Rev..
[55] Sreekanth H. Chalasani,et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators , 2009, Nature Methods.
[56] K. Harris,et al. Spontaneous Events Outline the Realm of Possible Sensory Responses in Neocortical Populations , 2009, Neuron.
[57] J. M. Herrmann,et al. Phase transitions towards criticality in a neural system with adaptive interactions. , 2009, Physical review letters.
[58] D. Plenz,et al. Spontaneous cortical activity in awake monkeys composed of neuronal avalanches , 2009, Proceedings of the National Academy of Sciences.
[59] X. Illa,et al. The effect of thresholding on temporal avalanche statistics , 2008, 0810.0948.
[60] Rafael Yuste,et al. Fast nonnegative deconvolution for spike train inference from population calcium imaging. , 2009, Journal of neurophysiology.
[61] D. Chialvo. Emergent complex neural dynamics , 2010, 1010.2530.
[62] Stefan Mihalas,et al. Self-organized criticality occurs in non-conservative neuronal networks during Up states , 2010, Nature physics.
[63] K. Svoboda,et al. Neural Activity in Barrel Cortex Underlying Vibrissa-Based Object Localization in Mice , 2010, Neuron.
[64] M. A. Muñoz,et al. Self-organization without conservation: are neuronal avalanches generically critical? , 2010, 1001.3256.
[65] J. Touboul,et al. Can Power-Law Scaling and Neuronal Avalanches Arise from Stochastic Dynamics? , 2009, PloS one.
[66] M. Larkum,et al. Frontiers in Neural Circuits Neural Circuits Methods Article , 2022 .
[67] Marc Benayoun,et al. Avalanches in a Stochastic Model of Spiking Neurons , 2010, PLoS Comput. Biol..
[68] Andrew M. Clark,et al. Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.
[69] Florentin Wörgötter,et al. Self-Organized Criticality in Developing Neuronal Networks , 2010, PLoS Comput. Biol..
[70] J. Schiller,et al. Dynamics of Excitability over Extended Timescales in Cultured Cortical Neurons , 2010, The Journal of Neuroscience.
[71] H. S. Meyer,et al. Number and Laminar Distribution of Neurons in a Thalamocortical Projection Column of Rat Vibrissal Cortex , 2010, Cerebral cortex.
[72] M. Nicolelis,et al. Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle , 2010, PloS one.
[73] Alexander S. Ecker,et al. Decorrelated Neuronal Firing in Cortical Microcircuits , 2010, Science.
[74] M. London,et al. Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex , 2010, Nature.
[75] Karel Svoboda,et al. Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice , 2010, Nature.
[76] P. Dayan,et al. Supporting Online Material Materials and Methods Som Text Figs. S1 to S9 References the Asynchronous State in Cortical Circuits , 2022 .
[77] L. de Arcangelis,et al. Learning as a phenomenon occurring in a critical state , 2010, Proceedings of the National Academy of Sciences.
[78] J. Sethna,et al. Universality beyond power laws and the average avalanche shape , 2011 .
[79] Shan Yu,et al. Higher-Order Interactions Characterized in Cortical Activity , 2011, The Journal of Neuroscience.
[80] Changsong Zhou,et al. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations , 2010, Front. Comput. Neurosci..
[81] Avner Wallach,et al. Relational Dynamics in Perception: Impacts on Trial-to-trial Variation , 2011, Front. Comput. Neurosci..
[82] Olaf Sporns,et al. Neurobiologically Realistic Determinants of Self-Organized Criticality in Networks of Spiking Neurons , 2011, PLoS Comput. Biol..
[83] Takeharu Nagai,et al. Quantitative Comparison of Genetically Encoded Ca2+ Indicators in Cortical Pyramidal Cells and Cerebellar Purkinje Cells , 2011, Front. Cell. Neurosci..
[84] Woodrow L. Shew,et al. Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches , 2010, The Journal of Neuroscience.
[85] Morgane M. Roth,et al. Representation of visual scenes by local neuronal populations in layer 2/3 of mouse visual cortex , 2011, Front. Neural Circuits.
[86] Andreas Klaus,et al. Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches , 2011, PloS one.
[87] D. Plenz. Neuronal avalanches and coherence potentials , 2012 .
[88] Dante R. Chialvo,et al. What kind of noise is brain noise: anomalous scaling behavior of the resting brain activity fluctuations , 2010, Front. Physio..
[89] W. Singer,et al. Orientation selectivity and noise correlation in awake monkey area V1 are modulated by the gamma cycle , 2012, Proceedings of the National Academy of Sciences.
[90] Zach D. Haga,et al. Avalanche Analysis from Multielectrode Ensemble Recordings in Cat, Monkey, and Human Cerebral Cortex during Wakefulness and Sleep , 2012, Front. Physio..
[91] John M. Beggs,et al. Being Critical of Criticality in the Brain , 2012, Front. Physio..
[92] A. Litwin-Kumar,et al. Slow dynamics and high variability in balanced cortical networks with clustered connections , 2012, Nature Neuroscience.
[93] M. Magnasco,et al. Self-Regulated Dynamical Criticality in Human ECoG , 2012, Front. Integr. Neurosci..
[94] John M. Beggs,et al. Universal critical dynamics in high resolution neuronal avalanche data. , 2012, Physical review letters.
[95] F. Helmchen,et al. Reorganization of cortical population activity imaged throughout long-term sensory deprivation , 2012, Nature Neuroscience.
[96] Pablo Balenzuela,et al. Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis , 2012, Front. Physio..
[97] Alison L. Barth,et al. Experimental evidence for sparse firing in the neocortex , 2012, Trends in Neurosciences.
[98] Woodrow L. Shew,et al. Maximal Variability of Phase Synchrony in Cortical Networks with Neuronal Avalanches , 2012, The Journal of Neuroscience.
[99] K. Linkenkaer-Hansen,et al. Critical-State Dynamics of Avalanches and Oscillations Jointly Emerge from Balanced Excitation/Inhibition in Neuronal Networks , 2012, The Journal of Neuroscience.
[100] D. Plenz,et al. Balance between excitation and inhibition controls the temporal organization of neuronal avalanches. , 2012, Physical review letters.
[101] Jean-Philippe Thivierge,et al. Extracting functionally feedforward networks from a population of spiking neurons , 2012, Front. Comput. Neurosci..
[102] Woodrow L. Shew,et al. The Functional Benefits of Criticality in the Cortex , 2013, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[103] D. Plenz,et al. Neuronal Avalanches in the Resting MEG of the Human Brain , 2012, The Journal of Neuroscience.
[104] Shimon Marom,et al. Self-organized criticality in single-neuron excitability. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[105] Dante R Chialvo,et al. Brain organization into resting state networks emerges at criticality on a model of the human connectome. , 2012, Physical review letters.
[106] Eric J Friedman,et al. Hierarchical networks, power laws, and neuronal avalanches. , 2013, Chaos.
[107] O. Shriki,et al. Fading Signatures of Critical Brain Dynamics during Sustained Wakefulness in Humans , 2013, The Journal of Neuroscience.
[108] Viola Priesemann,et al. Neuronal Avalanches Differ from Wakefulness to Deep Sleep – Evidence from Intracranial Depth Recordings in Humans , 2013, PLoS Comput. Biol..
[109] K. Linkenkaer-Hansen,et al. Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws , 2013, Proceedings of the National Academy of Sciences.
[110] M. A. Muñoz,et al. Griffiths phases and the stretching of criticality in brain networks , 2013, Nature Communications.
[111] Jochen Triesch,et al. Spike avalanches in vivo suggest a driven, slightly subcritical brain state , 2014, Front. Syst. Neurosci..
[112] Srdjan Ostojic,et al. Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons , 2014, Nature Neuroscience.
[113] D. Marković,et al. Power laws and Self-Organized Criticality in Theory and Nature , 2013, 1310.5527.
[114] Woodrow L. Shew,et al. Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics , 2014, The Journal of Neuroscience.
[115] R. Yuste,et al. Visual stimuli recruit intrinsically generated cortical ensembles , 2014, Proceedings of the National Academy of Sciences.
[116] Andreas Klaus,et al. Scale-Invariant Neuronal Avalanche Dynamics and the Cut-Off in Size Distributions , 2014, PloS one.
[117] D. Plenz,et al. On the temporal organization of neuronal avalanches , 2014, Front. Syst. Neurosci..
[118] Nergis Tomen,et al. Marginally subcritical dynamics explain enhanced stimulus discriminability under attention , 2014, Front. Syst. Neurosci..
[119] Mario Pannunzi,et al. The Influence of Spatiotemporal Structure of Noisy Stimuli in Decision Making , 2014, PLoS Comput. Biol..
[120] M. Copelli,et al. Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches , 2014, PloS one.
[121] Denis Cousineau,et al. Maximum likelihood estimators for truncated and censored power-law distributions show how neuronal avalanches may be misevaluated. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[122] D. Plenz,et al. Criticality in neural systems , 2014 .
[123] 王亚周. Involvement of endoplasmic reticulum stress in the necroptosis ofmicroglia/macrophages after spinal cord injury. , 2015 .
[124] Dietmar Plenz,et al. Critical Slowing Down Governs the Transition to Neuron Spiking , 2015, PLoS Comput. Biol..
[125] Narayan Srinivasa,et al. Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks , 2015, PLoS Comput. Biol..