Model Concept: Synaptic Plasticity

The model is used to investigate the mechanisms and/or effects of synaptic plasticity.

Models:

  1. 3D model of the olfactory bulb (Migliore et al. 2014)
  2. 3D olfactory bulb: operators (Migliore et al, 2015)
  3. A 1000 cell network model for Lateral Amygdala (Kim et al. 2013)
  4. A Computational Model of Bidirectional Plasticity Regulation by betaCaMKII (Pinto et al. 2019)
  5. A basal ganglia model of aberrant learning (Ursino et al. 2018)
  6. A computational model of systems memory consolidation and reconsolidation (Helfer & Shultz 2019)
  7. A dendritic disinhibitory circuit mechanism for pathway-specific gating (Yang et al. 2016)
  8. A kinetic model unifying presynaptic short-term facilitation and depression (Lee et al. 2009)
  9. A model for focal seizure onset, propagation, evolution, and progression (Liou et al 2020)
  10. A model of cerebellar LTD including RKIP inactivation of Raf and MEK (Hepburn et al 2017)
  11. A model of optimal learning with redundant synaptic connections (Hiratani & Fukai 2018)
  12. A network model of tail withdrawal in Aplysia (White et al 1993)
  13. A simple model of neuromodulatory state-dependent synaptic plasticity (Pedrosa and Clopath, 2016)
  14. A single-cell spiking model for the origin of grid-cell patterns (D'Albis & Kempter 2017)
  15. ACh modulation in olfactory bulb and piriform cortex (de Almeida et al. 2013;Devore S, et al. 2014)
  16. AMPA receptor trafficking and its role in heterosynaptic plasticity (Antunes et al 2018)
  17. Acetylcholine-modulated plasticity in reward-driven navigation (Zannone et al 2018)
  18. Active dendrites shape signaling microdomains in hippocampal neurons (Basak & Narayanan 2018)
  19. Activity dependent changes in dendritic spine density and spine structure (Crook et al. 2007)
  20. Adaptation of Short-Term Plasticity parameters (Esposito et al. 2015)
  21. Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014)
  22. Amyloid-beta effects on release probability and integration at CA3-CA1 synapses (Romani et al. 2013)
  23. BCM-like synaptic plasticity with conductance-based models (Narayanan Johnston, 2010)
  24. Behavioral time scale synaptic plasticity underlies CA1 place fields (Bittner et al. 2017)
  25. Biologically-plausible models for spatial navigation (Cannon et al 2003)
  26. Biophysical and phenomenological models of spike-timing dependent plasticity (Badoual et al. 2006)
  27. Burst induced synaptic plasticity in Apysia sensorimotor neurons (Phares et al 2003)
  28. CA1 pyramidal cell receptor dependent cAMP dynamics (Chay et al. 2016)
  29. CA1 pyramidal neuron dendritic spine with plasticity (O`Donnell et al. 2011)
  30. CA1 pyramidal neuron: Dendritic Na+ spikes are required for LTP at distal synapses (Kim et al 2015)
  31. CA1 pyramidal neuron: synaptically-induced bAP predicts synapse location (Sterratt et al. 2012)
  32. Ca2+ requirements for Long-Term Depression in Purkinje Cells (Criseida Zamora et al 2018)
  33. CaMKII system exhibiting bistability with respect to calcium (Graupner and Brunel 2007)
  34. Calcium waves and mGluR-dependent synaptic plasticity in CA1 pyr. neurons (Ashhad & Narayanan 2013)
  35. Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011)
  36. Cerebellar long-term depression (LTD) (Antunes and De Schutter 2012)
  37. Cerebellar memory consolidation model (Yamazaki et al. 2015)
  38. Computing with neural synchrony (Brette 2012)
  39. Cortical Layer 5b pyr. cell with [Na+]i mechanisms, from Hay et al 2011 (Zylbertal et al 2017)
  40. Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
  41. Cortical oscillations and the basal ganglia (Fountas & Shanahan 2017)
  42. Cortico-striatal plasticity in medium spiny neurons (Gurney et al 2015)
  43. Development and Binocular Matching of Orientation Selectivity in Visual Cortex (Xu et al 2020)
  44. Diffusive homeostasis in a spiking network model (Sweeney et al. 2015)
  45. Discrimination on behavioral time-scales mediated by reaction-diffusion in dendrites (Bhalla 2017)
  46. Disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex (Domanski et al 2019)
  47. Dopamine activation of signaling pathways in a medium spiny projection neuron (Oliveira et al. 2012)
  48. Dynamic dopamine modulation in the basal ganglia: Learning in Parkinson (Frank et al 2004,2005)
  49. Electrical compartmentalization in neurons (Wybo et al 2019)
  50. Endocannabinoid dynamics gate spike-timing dependent depression and potentiation (Cui et al 2016)
  51. Facilitation through buffer saturation (Matveev et al. 2004)
  52. Factors contribution to GDP-induced [Cl-]i transients (Lombardi et al 2019)
  53. Feedforward network undergoing Up-state-mediated plasticity (Gonzalez-Rueda et al. 2018)
  54. Four-pathway phenomenological synaptic plasticity model (Ebner et al. 2019)
  55. Functional balanced networks with synaptic plasticity (Sadeh et al, 2015)
  56. Generation of stable heading representations in diverse visual scenes (Kim et al 2019)
  57. Gq coupled signaling pathways involved in striatal synaptic plasticity (Kim et al. 2013)
  58. Grid cells from place cells (Castro & Aguiar, 2014)
  59. Hebbian STDP for modelling the emergence of disparity selectivity (Chauhan et al 2018)
  60. Heterosynaptic Spike-Timing-Dependent Plasticity (Hiratani & Fukai 2017)
  61. Homeostatic synaptic plasticity (Rabinowitch and Segev 2006a,b)
  62. Homosynaptic plasticity in the tail withdrawal circuit (TWC) of Aplysia (Baxter and Byrne 2006)
  63. Hotspots of dendritic spine turnover facilitates new spines and NN sparsity (Frank et al 2018)
  64. Inhibition of bAPs and Ca2+ spikes in a multi-compartment pyramidal neuron model (Wilmes et al 2016)
  65. Inhibitory neuron plasticity as a mechanism for ocular dominance plasticity (Bono & Clopath 2019)
  66. Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011)
  67. Interplay between somatic and dendritic inhibition promotes place fields (Pedrosa & Clopath 2020)
  68. Kinetic NMDA receptor model (Kampa et al 2004)
  69. Large scale model of the olfactory bulb (Yu et al., 2013)
  70. Learning spatial transformations through STDP (Davison, Frégnac 2006)
  71. Leech Mechanosensory Neurons: Synaptic Facilitation by Reflected APs (Baccus 1998)
  72. Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
  73. Logarithmic distributions prove that intrinsic learning is Hebbian (Scheler 2017)
  74. Minimal model of interictal and ictal discharges “Epileptor-2” (Chizhov et al 2018)
  75. Model of cerebellar parallel fiber-Purkinje cell LTD and LTP (Gallimore et al 2018)
  76. Modeling dendritic spikes and plasticity (Bono and Clopath 2017)
  77. Multiscale interactions between chemical and electric signaling in LTP (Bhalla 2011)
  78. Multiscale simulation of the striatal medium spiny neuron (Mattioni & Le Novere 2013)
  79. NeuroMatic: software for acquisition, analysis and simulation of e-phys data (Rothman & Silver 2018)
  80. Olfactory bulb mitral and granule cell column formation (Migliore et al. 2007)
  81. Online learning model of olfactory bulb external plexiform layer network (Imam & Cleland 2020)
  82. Opposing roles for Na+/Ca2+ exchange and Ca2+-activated K+ currents during STDP (O`Halloran 2020)
  83. Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
  84. Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009)
  85. PKMZ synthesis and AMPAR regulation in late long-term synaptic potentiation (Helfer & Shultz 2018)
  86. Place and grid cells in a loop (Rennó-Costa & Tort 2017)
  87. Reinforcement learning of targeted movement (Chadderdon et al. 2012)
  88. Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
  89. Reproducing infra-slow oscillations with dopaminergic modulation (Kobayashi et al 2017)
  90. Roles of essential kinases in induction of late hippocampal LTP (Smolen et al., 2006)
  91. Roles of subthalamic nucleus and DBS in reinforcement conflict-based decision making (Frank 2006)
  92. STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
  93. STDP and NMDAR Subunits (Gerkin et al. 2007)
  94. STDP depends on dendritic synapse location (Letzkus et al. 2006)
  95. Self-influencing synaptic plasticity (Tamosiunaite et al. 2007)
  96. Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013)
  97. Short term plasticity of synapses onto V1 layer 2/3 pyramidal neuron (Varela et al 1997)
  98. Somatodendritic consistency check for temporal feature segmentation (Asabuki & Fukai 2020)
  99. Spatially-varying glutamate diffusion coefficient at CA1 synaptic cleft space (Gupta et al. 2016)
  100. Spike timing detection in different forms of LTD (Doi et al 2005)
  101. Spike-timing dependent inhibitory plasticity for gating bAPs (Wilmes et al 2017)
  102. Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013)
  103. Spine fusion and branching affects synaptic response (Rusakov et al 1996, 1997)
  104. Stability of complex spike timing-dependent plasticity in cerebellar learning (Roberts 2007)
  105. Stochastic LTP/LTD conditioning of a synapse (Migliore and Lansky 1999)
  106. Striatal Spiny Projection Neuron (SPN) plasticity rule (Jedrzejewska-Szmek et al 2016)
  107. Striatal Spiny Projection Neuron, inhibition enhances spatial specificity (Dorman et al 2018)
  108. Supervised learning with predictive coding (Whittington & Bogacz 2017)
  109. Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy (Ruijter et al 2017)
  110. Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
  111. Tag Trigger Consolidation (Clopath and Ziegler et al. 2008)
  112. Theta phase precession in a model CA3 place cell (Baker and Olds 2007)
  113. Two forms of synaptic depression by neuromodulation of presynaptic Ca2+ channels (Burke et al 2018)
  114. Vestibulo-Ocular Reflex model in Matlab (Clopath at al. 2014)
Top authors for Synaptic Plasticity:
Top concepts studied with Synaptic Plasticity:
Top neurons studied with Synaptic Plasticity:
Top currents studied with Synaptic Plasticity:
Top references cited by these models: