Frontiers in Synaptic Neuroscience Synaptic Neuroscience

A phenomenological model of synaptic plasticity is able to account for a large body of experimental data on spike-timing-dependent plasticity (STDP). The basic ingredient of the model is the correlation of presynaptic spike arrival with postsynaptic voltage. The local membrane voltage is used twice: a first term accounts for the instantaneous voltage and the second one for a low-pass filtered voltage trace. Spike-timing effects emerge as a special case. We hypothesize that the voltage dependence can explain differential effects of STDP in dendrites, since the amplitude and time course of backpropagating action potentials or dendritic spikes influences the plasticity results in the model. The dendritic effects are simulated by variable choices of voltage time course at the site of the synapse, i.e., without an explicit model of the spatial structure of the neuron.

[1]  M. Bear,et al.  Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-D-aspartate receptor blockade. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Mark C. W. van Rossum,et al.  Stable Hebbian Learning from Spike Timing-Dependent Plasticity , 2000, The Journal of Neuroscience.

[3]  J. Lisman,et al.  A mechanism for the Hebb and the anti-Hebb processes underlying learning and memory. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Wulfram Gerstner,et al.  Phenomenological models of synaptic plasticity based on spike timing , 2008, Biological Cybernetics.

[5]  Markus Diesmann,et al.  Spike-Timing-Dependent Plasticity in Balanced Random Networks , 2007, Neural Computation.

[6]  Wulfram Gerstner,et al.  How Good Are Neuron Models? , 2009, Science.

[7]  Wulfram Gerstner,et al.  Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression , 2008, PLoS Comput. Biol..

[8]  Henry Markram,et al.  An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing , 2001, Neural Computation.

[9]  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.

[10]  Johannes J. Letzkus,et al.  Requirement of dendritic calcium spikes for induction of spike‐timing‐dependent synaptic plasticity , 2006, The Journal of physiology.

[11]  H. Abarbanel,et al.  Dynamical model of long-term synaptic plasticity , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Walter Senn,et al.  Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics , 2007, Neural Computation.

[13]  Mark C. W. van Rossum,et al.  State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture , 2009, PLoS Comput. Biol..

[14]  Wulfram Gerstner,et al.  A neuronal learning rule for sub-millisecond temporal coding , 1996, Nature.

[15]  Eugene M. Izhikevich,et al.  Simple model of spiking neurons , 2003, IEEE Trans. Neural Networks.

[16]  L. Abbott,et al.  Synaptic plasticity: taming the beast , 2000, Nature Neuroscience.

[17]  M. Poo,et al.  Calcium stores regulate the polarity and input specificity of synaptic modification , 2000, Nature.

[18]  U. Karmarkar,et al.  A model of spike-timing dependent plasticity: one or two coincidence detectors? , 2002, Journal of neurophysiology.

[19]  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.

[20]  H. Markram,et al.  Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997, Science.

[21]  Wulfram Gerstner,et al.  Firing patterns in the adaptive exponential integrate-and-fire model , 2008, Biological Cybernetics.

[22]  P. J. Sjöström,et al.  A Cooperative Switch Determines the Sign of Synaptic Plasticity in Distal Dendrites of Neocortical Pyramidal Neurons , 2006, Neuron.

[23]  Y. Dan,et al.  Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.

[24]  W. Gerstner,et al.  Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity , 2006, The Journal of Neuroscience.

[25]  P. J. Sjöström,et al.  Neocortical LTD via Coincident Activation of Presynaptic NMDA and Cannabinoid Receptors , 2003, Neuron.

[26]  A. Polsky,et al.  Properties of basal dendrites of layer 5 pyramidal neurons: a direct patch-clamp recording study , 2007, Nature Neuroscience.

[27]  J. Lisman,et al.  A Model of Synaptic Memory A CaMKII/PP1 Switch that Potentiates Transmission by Organizing an AMPA Receptor Anchoring Assembly , 2001, Neuron.

[28]  L. Cooper,et al.  A unified model of NMDA receptor-dependent bidirectional synaptic plasticity , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[29]  Erik De Schutter,et al.  Complex Parameter Landscape for a Complex Neuron Model , 2006, PLoS Comput. Biol..

[30]  Henry Markram,et al.  An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials , 1997, ICANN.

[31]  W. Gerstner,et al.  Connectivity reflects coding: a model of voltage-based STDP with homeostasis , 2010, Nature Neuroscience.

[32]  Nicolas Brunel,et al.  STDP in a Bistable Synapse Model Based on CaMKII and Associated Signaling Pathways , 2007, PLoS Comput. Biol..

[33]  A. Artola,et al.  Synaptic Activity Modulates the Induction of Bidirectional Synaptic Changes in Adult Mouse Hippocampus , 2000, The Journal of Neuroscience.

[34]  Wulfram Gerstner,et al.  Universality in neural networks: the importance of the ‘mean firing rate’ , 1992, Biological Cybernetics.

[35]  Florentin Wörgötter,et al.  How the Shape of Pre- and Postsynaptic Signals Can Influence STDP: A Biophysical Model , 2004, Neural Computation.

[36]  Wulfram Gerstner,et al.  Spiking Neuron Models , 2002 .

[37]  W. Gerstner,et al.  Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis , 2009 .

[38]  A. Polsky,et al.  Synaptic Integration in Tuft Dendrites of Layer 5 Pyramidal Neurons: A New Unifying Principle , 2009, Science.

[39]  W. Gerstner,et al.  Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. , 2008, Journal of neurophysiology.

[40]  Eugene M. Izhikevich,et al.  Relating STDP to BCM , 2003, Neural Computation.

[41]  J. Lisman A mechanism for memory storage insensitive to molecular turnover: a bistable autophosphorylating kinase. , 1985, Proceedings of the National Academy of Sciences of the United States of America.

[42]  L. Abbott,et al.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.

[43]  Carson C. Chow,et al.  Calcium time course as a signal for spike-timing-dependent plasticity. , 2005, Journal of neurophysiology.

[44]  G. Stuart,et al.  Membrane Potential Changes in Dendritic Spines during Action Potentials and Synaptic Input , 2009, The Journal of Neuroscience.

[45]  Henry Markram,et al.  A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Neuron Models by Experimental Data , 2007, Front. Neurosci..

[46]  W. Singer,et al.  Different voltage-dependent thresholds for inducing long-term depression and long-term potentiation in slices of rat visual cortex , 1990, Nature.

[47]  Johannes J. Letzkus,et al.  Learning Rules for Spike Timing-Dependent Plasticity Depend on Dendritic Synapse Location , 2006, The Journal of Neuroscience.

[48]  V. Han,et al.  Synaptic plasticity in a cerebellum-like structure depends on temporal order , 1997, Nature.

[49]  Xiao-Jing Wang,et al.  The Stability of a Stochastic CaMKII Switch: Dependence on the Number of Enzyme Molecules and Protein Turnover , 2005, PLoS biology.

[50]  Y. Dan,et al.  Spike-timing-dependent synaptic plasticity depends on dendritic location , 2005, Nature.

[51]  S. Kelso,et al.  Hebbian synapses in hippocampus. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[52]  Dean V. Buonomano,et al.  Mechanisms and significance of spike-timing dependent plasticity , 2002, Biological Cybernetics.

[53]  P. J. Sjöström,et al.  Endocannabinoid-dependent neocortical layer-5 LTD in the absence of postsynaptic spiking. , 2004, Journal of neurophysiology.

[54]  Wulfram Gerstner,et al.  Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments , 2007, Neurocomputing.

[55]  Y. Dan,et al.  Contribution of individual spikes in burst-induced long-term synaptic modification. , 2006, Journal of neurophysiology.

[56]  David W. Nauen,et al.  Coactivation and timing-dependent integration of synaptic potentiation and depression , 2005, Nature Neuroscience.

[57]  Wulfram Gerstner,et al.  Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. , 2005, Journal of neurophysiology.

[58]  Daniel D. Lee,et al.  Equilibrium properties of temporally asymmetric Hebbian plasticity. , 2000, Physical review letters.

[59]  R. Kempter,et al.  Hebbian learning and spiking neurons , 1999 .

[60]  G. Bi,et al.  Synaptic modification by correlated activity: Hebb's postulate revisited. , 2001, Annual review of neuroscience.

[61]  Walter Senn,et al.  Beyond spike timing: the role of nonlinear plasticity and unreliable synapses , 2002, Biological Cybernetics.

[62]  P. J. Sjöström,et al.  Rate, Timing, and Cooperativity Jointly Determine Cortical Synaptic Plasticity , 2001, Neuron.

[63]  Patrick D. Roberts,et al.  Computational Consequences of Temporally Asymmetric Learning Rules: I. Differential Hebbian Learning , 1999, Journal of Computational Neuroscience.

[64]  D. Debanne,et al.  Long‐term synaptic plasticity between pairs of individual CA3 pyramidal cells in rat hippocampal slice cultures , 1998, The Journal of physiology.

[65]  S. Wang,et al.  Malleability of Spike-Timing-Dependent Plasticity at the CA3–CA1 Synapse , 2006, The Journal of Neuroscience.

[66]  J. Leo van Hemmen,et al.  Modeling Synaptic Plasticity in Conjunction with the Timing of Pre- and Postsynaptic Action Potentials , 2000, Neural Computation.