The temporal paradox of Hebbian learning and homeostatic plasticity
暂无分享,去创建一个
[1] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[2] G. Zajicek,et al. The Wisdom of the Body , 1934, Nature.
[3] J. Knott. The organization of behavior: A neuropsychological theory , 1951 .
[4] John H. Holland,et al. Tests on a cell assembly theory of the action of the brain, using a large digital computer , 1956, IRE Trans. Inf. Theory.
[5] Danielle M. Santarelli,et al. The Developing Brain , 2017 .
[6] G. Lynch,et al. Heterosynaptic depression: a postsynaptic correlate of long-term potentiation , 1977, Nature.
[7] E. Oja. Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.
[8] E. Bienenstock,et al. Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[9] W. Singer,et al. Modulation of visual cortical plasticity by acetylcholine and noradrenaline , 1986, Nature.
[10] W. Abraham,et al. Priming of associative long-term depression in the dentate gyrus by θ frequency synaptic activity , 1992, Neuron.
[11] R. Malenka,et al. The influence of prior synaptic activity on the induction of long-term potentiation. , 1992, Science.
[12] Kenneth D. Miller,et al. The Role of Constraints in Hebbian Learning , 1994, Neural Computation.
[13] M. Bear,et al. Metaplasticity: the plasticity of synaptic plasticity , 1996, Trends in Neurosciences.
[14] H. Markram,et al. Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997, Science.
[15] D. Johnston,et al. Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997 .
[16] U. Frey,et al. Synaptic tagging: implications for late maintenance of hippocampal long-term potentiation , 1998, Trends in Neurosciences.
[17] Niraj S. Desai,et al. Activity-dependent scaling of quantal amplitude in neocortical neurons , 1998, Nature.
[18] Li I. Zhang,et al. A critical window for cooperation and competition among developing retinotectal synapses , 1998, Nature.
[19] G. Bi,et al. Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.
[20] R. Kempter,et al. Hebbian learning and spiking neurons , 1999 .
[21] C. Rittenhouse,et al. Monocular deprivation induces homosynaptic long-term depression in visual cortex , 1999, Nature.
[22] Mark C. W. van Rossum,et al. Stable Hebbian Learning from Spike Timing-Dependent Plasticity , 2000, The Journal of Neuroscience.
[23] L. Abbott,et al. Synaptic plasticity: taming the beast , 2000, Nature Neuroscience.
[24] L. Abbott,et al. Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.
[25] J. Leo van Hemmen,et al. Modeling Synaptic Plasticity in Conjunction with the Timing of Pre- and Postsynaptic Action Potentials , 2000, Neural Computation.
[26] Henry Markram,et al. An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing , 2001, Neural Computation.
[27] Daniel D. Lee,et al. Equilibrium properties of temporally asymmetric Hebbian plasticity. , 2000, Physical review letters.
[28] Wulfram Gerstner,et al. Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning , 2001, Neural Computation.
[29] G. Bi,et al. Synaptic modification by correlated activity: Hebb's postulate revisited. , 2001, Annual review of neuroscience.
[30] Wickliffe C Abraham,et al. NMDA receptor‐mediated metaplasticity during the induction of long‐term depression by low‐frequency stimulation , 2002, The European journal of neuroscience.
[31] Y. Dan,et al. Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.
[32] Andrew B. Kahng,et al. Variability , 2002, IEEE Des. Test Comput..
[33] D. Debanne,et al. Long-term plasticity of intrinsic excitability: learning rules and mechanisms. , 2003, Learning & memory.
[34] 장윤희,et al. Y. , 2003, Industrial and Labor Relations Terms.
[35] M. Poo,et al. Reversal and Stabilization of Synaptic Modifications in a Developing Visual System , 2003, Science.
[36] M. Quirk,et al. Hippocampal CA3 NMDA Receptors Are Crucial for Memory Acquisition of One-Time Experience , 2003, Neuron.
[37] S. Royer,et al. Conservation of total synaptic weight through balanced synaptic depression and potentiation , 2003, Nature.
[38] Haim Sompolinsky,et al. Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity , 2003, The Journal of Neuroscience.
[39] Zhen Yan,et al. Bidirectional Regulation of Ca2+/Calmodulin-Dependent Protein Kinase II Activity by Dopamine D4 Receptors in Prefrontal Cortex , 2004, Molecular Pharmacology.
[40] Z. Rossetti,et al. Pulse of Nitric Oxide Release in Response to Activation of N-Methyl-d-aspartate Receptors in the Rat Striatum: Rapid Desensitization, Inhibition by Receptor Antagonists, and Potentiation by Glycine , 2004, Journal of Pharmacology and Experimental Therapeutics.
[41] Nathan Intrator,et al. Theory of Cortical Plasticity , 2004 .
[42] R. Kesner,et al. Differential contributions of dorsal hippocampal subregions to memory acquisition and retrieval in contextual fear‐conditioning , 2004, Hippocampus.
[43] C. Malsburg. Self-organization of orientation sensitive cells in the striate cortex , 2004, Kybernetik.
[44] L. Abbott,et al. Cascade Models of Synaptically Stored Memories , 2005, Neuron.
[45] A. Kirkwood,et al. Cross-modal regulation of synaptic AMPA receptors in primary sensory cortices by visual experience , 2006, Nature Neuroscience.
[46] W. Gerstner,et al. Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity , 2006, The Journal of Neuroscience.
[47] Lubica Benusková,et al. STDP rule endowed with the BCM sliding threshold accounts for hippocampal heterosynaptic plasticity , 2007, Journal of Computational Neuroscience.
[48] E. Marder,et al. Variability, compensation and homeostasis in neuron and network function , 2006, Nature Reviews Neuroscience.
[49] G. Davis. Homeostatic control of neural activity: from phenomenology to molecular design. , 2006, Annual review of neuroscience.
[50] W. Schultz. Multiple dopamine functions at different time courses. , 2007, Annual review of neuroscience.
[51] Markus Diesmann,et al. Spike-Timing-Dependent Plasticity in Balanced Random Networks , 2007, Neural Computation.
[52] W. Abraham,et al. "Heterosynaptic" LTD in the dentate gyrus of anesthetized rat requires homosynaptic activity. , 2007, Journal of neurophysiology.
[53] W. Abraham. Metaplasticity: tuning synapses and networks for plasticity , 2008, Nature Reviews Neuroscience.
[54] P. J. Sjöström,et al. Dendritic excitability and synaptic plasticity. , 2008, Physiological reviews.
[55] Richard M. Murray,et al. Feedback Systems An Introduction for Scientists and Engineers , 2007 .
[56] G. Turrigiano,et al. Rapid Synaptic Scaling Induced by Changes in Postsynaptic Firing , 2008, Neuron.
[57] G. Turrigiano. The Self-Tuning Neuron: Synaptic Scaling of Excitatory Synapses , 2008, Cell.
[58] Idan Segev,et al. Two opposing plasticity mechanisms pulling a single synapse , 2008, Trends in Neurosciences.
[59] Michael P. Stryker,et al. Report Tumor Necrosis Factor-a Mediates One Component of Competitive, Experience-dependent Plasticity in Developing Visual Cortex , 2022 .
[60] Lu Chen,et al. Synaptic Signaling by All-Trans Retinoic Acid in Homeostatic Synaptic Plasticity , 2008, Neuron.
[61] Wulfram Gerstner,et al. Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression , 2008, PLoS Comput. Biol..
[62] D. Johnston,et al. Active dendrites: colorful wings of the mysterious butterflies , 2008, Trends in Neurosciences.
[63] Mark C. W. van Rossum,et al. Memory retention and spike-timing-dependent plasticity. , 2009, Journal of neurophysiology.
[64] Matthieu Gilson,et al. Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity–strengthening correlated input pathways , 2009, Biological Cybernetics.
[65] G. Bi,et al. Gain in sensitivity and loss in temporal contrast of STDP by dopaminergic modulation at hippocampal synapses , 2009, Proceedings of the National Academy of Sciences.
[66] Mark C. W. van Rossum,et al. State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture , 2009, PLoS Comput. Biol..
[67] Gordon Pipa,et al. SORN: A Self-Organizing Recurrent Neural Network , 2009, Front. Comput. Neurosci..
[68] J. Wickens,et al. Timing is not Everything: Neuromodulation Opens the STDP Gate , 2010, Front. Syn. Neurosci..
[69] R. Morris,et al. Making memories last: the synaptic tagging and capture hypothesis , 2010, Nature Reviews Neuroscience.
[70] W. Gerstner,et al. Connectivity reflects coding: a model of voltage-based STDP with homeostasis , 2010, Nature Neuroscience.
[71] Niraj S. Desai,et al. Homeostatic Plasticity and STDP: Keeping a Neuron's Cool in a Fluctuating World , 2010, Front. Syn. Neurosci..
[72] Niraj S Desai,et al. Pyramidal Neuron Conductance State Gates Spike-Timing-Dependent Plasticity , 2010, The Journal of Neuroscience.
[73] Timothy O’Leary,et al. Neuronal homeostasis: time for a change? , 2011, The Journal of physiology.
[74] Kristen M Harris,et al. Coordination of size and number of excitatory and inhibitory synapses results in a balanced structural plasticity along mature hippocampal CA1 dendrites during LTP , 2011, Hippocampus.
[75] Markus Diesmann,et al. Limits to the Development of Feed-Forward Structures in Large Recurrent Neuronal Networks , 2011, Front. Comput. Neurosci..
[76] Henning Sprekeler,et al. Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks , 2011, Science.
[77] J. Pfister,et al. A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations , 2011, Proceedings of the National Academy of Sciences.
[78] Wulfram Gerstner,et al. A History of Spike-Timing-Dependent Plasticity , 2011, Front. Syn. Neurosci..
[79] G. Turrigiano. Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement. , 2011, Annual review of neuroscience.
[80] N. Brunel,et al. Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location , 2012, Proceedings of the National Academy of Sciences.
[81] Yotam Luz,et al. Balancing Feed-Forward Excitation and Inhibition via Hebbian Inhibitory Synaptic Plasticity , 2012, PLoS Comput. Biol..
[82] Y. Frégnac,et al. Stable Learning in Stochastic Network States , 2012, The Journal of Neuroscience.
[83] Thomas Nevian,et al. Astrocyte signaling controls spike timing–dependent depression at neocortical synapses , 2012, Nature Neuroscience.
[84] G. Turrigiano. Homeostatic synaptic plasticity: local and global mechanisms for stabilizing neuronal function. , 2012, Cold Spring Harbor perspectives in biology.
[85] Kenneth D. Harris,et al. The Convallis Rule for Unsupervised Learning in Cortical Networks , 2013, PLoS Comput. Biol..
[86] K. Fox,et al. The role of nitric oxide in pre-synaptic plasticity and homeostasis , 2013, Front. Cell. Neurosci..
[87] Christopher M. Lee,et al. Heterosynaptic Plasticity Prevents Runaway Synaptic Dynamics , 2013, The Journal of Neuroscience.
[88] Surya Ganguli,et al. A memory frontier for complex synapses , 2013, NIPS.
[89] Wulfram Gerstner,et al. Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector , 2013, PLoS Comput. Biol..
[90] Eve Marder,et al. Homeostatic Regulation of Neuronal Excitability , 2013, Scholarpedia.
[91] K. Miller,et al. Modeling the Dynamic Interaction of Hebbian and Homeostatic Plasticity , 2014, Neuron.
[92] Arianna Maffei,et al. Inhibitory Plasticity Dictates the Sign of Plasticity at Excitatory Synapses , 2014, The Journal of Neuroscience.
[93] Nicolas Liaudet,et al. Astrocyte Ca2+ signalling: an unexpected complexity , 2014, Nature Reviews Neuroscience.
[94] Daniel E. Feldman,et al. Rapid homeostasis by disinhibition during whisker map plasticity , 2014, Proceedings of the National Academy of Sciences.
[95] Eve Marder,et al. Cell types, network homeostasis, and pathological compensation from a biologically plausible ion channel expression model. , 2014, Neuron.
[96] Eve Marder,et al. Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model , 2014, Neuron.
[97] A. Litwin-Kumar,et al. Formation and maintenance of neuronal assemblies through synaptic plasticity , 2014, Nature Communications.
[98] Everton J. Agnes,et al. Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks , 2015, Nature Communications.
[99] David J. Freedman,et al. Inferring learning rules from distribution of firing rates in cortical neurons , 2015, Nature Neuroscience.
[100] Lubica Benusková,et al. A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent “Heterosynaptic” LTD in the Dentate Gyrus In Vivo , 2015, PLoS Comput. Biol..
[101] Henry Markram,et al. Network-timing-dependent plasticity , 2015, Front. Cell. Neurosci..
[102] W. Gerstner,et al. Synaptic Consolidation: From Synapses to Behavioral Modeling , 2015, The Journal of Neuroscience.
[103] L. Parajuli,et al. Heterosynaptic structural plasticity on local dendritic segments of hippocampal CA1 neurons. , 2015, Cell reports.
[104] Matthieu Gilson,et al. Models of Metaplasticity: A Review of Concepts , 2015, Front. Comput. Neurosci..
[105] Jeanette Kotaleski,et al. A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks , 2015, bioRxiv.
[106] Stuart D. Greenhill,et al. Hebbian and Homeostatic Plasticity Mechanisms in Regular Spiking and Intrinsic Bursting Cells of Cortical Layer 5 , 2015, Neuron.
[107] Julijana Gjorgjieva,et al. Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity , 2015, The Journal of Neuroscience.
[108] Baktash Babadi,et al. Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity , 2016, PLoS Comput. Biol..
[109] Wulfram Gerstner,et al. Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation , 2016, PLoS Comput. Biol..
[110] N. Brunel,et al. Astrocytes: Orchestrating synaptic plasticity? , 2015, Neuroscience.
[111] Henning Sprekeler,et al. Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons , 2016, PLoS Comput. Biol..
[112] W. Gerstner,et al. Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules , 2016, Front. Neural Circuits.
[113] Tobias Bonhoeffer,et al. Cell-specific restoration of stimulus preference after monocular deprivation in the visual cortex , 2016, Science.
[114] Maxim Bazhenov,et al. Partial Breakdown of Input Specificity of STDP at Individual Synapses Promotes New Learning , 2016, The Journal of Neuroscience.
[115] Stefano Fusi,et al. Computational principles of synaptic memory consolidation , 2016, Nature Neuroscience.
[116] Claudia Clopath,et al. Receptive field formation by interacting excitatory and inhibitory synaptic plasticity , 2016, bioRxiv.
[117] Y. Hsu,et al. A metaplasticity view of the interaction between homeostatic and Hebbian plasticity , 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.
[118] John Lisman,et al. Glutamatergic synapses are structurally and biochemically complex because of multiple plasticity processes: long-term potentiation, long-term depression, short-term potentiation and scaling , 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.
[119] W. Gerstner,et al. Hebbian plasticity requires compensatory processes on multiple timescales , 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.
[120] Paul W. Munro,et al. Emergent Dynamical Properties of the BCM Learning Rule , 2017, The Journal of Mathematical Neuroscience.
[121] G. Turrigiano. The dialectic of Hebb and homeostasis , 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.