| | Models |
| 1. |
3D model of the olfactory bulb (Migliore et al. 2014)
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| 2. |
3D olfactory bulb: operators (Migliore et al, 2015)
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| 3. |
A 1000 cell network model for Lateral Amygdala (Kim et al. 2013)
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| 4. |
A basal ganglia model of aberrant learning (Ursino et al. 2018)
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| 5. |
A computational model of systems memory consolidation and reconsolidation (Helfer & Shultz 2019)
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| 6. |
A dendritic disinhibitory circuit mechanism for pathway-specific gating (Yang et al. 2016)
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| 7. |
A model for focal seizure onset, propagation, evolution, and progression (Liou et al 2020)
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| 8. |
A model of ASIC1a and synaptic cleft pH modulating wind-up in wide dynamic range neurons (Delrocq)
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| 9. |
A network model of tail withdrawal in Aplysia (White et al 1993)
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| 10. |
A single-cell spiking model for the origin of grid-cell patterns (D'Albis & Kempter 2017)
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| 11. |
Acetylcholine-modulated plasticity in reward-driven navigation (Zannone et al 2018)
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| 12. |
ACh modulation in olfactory bulb and piriform cortex (de Almeida et al. 2013;Devore S, et al. 2014)
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| 13. |
Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014)
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| 14. |
Biologically-plausible models for spatial navigation (Cannon et al 2003)
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| 15. |
Burst induced synaptic plasticity in Apysia sensorimotor neurons (Phares et al 2003)
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| 16. |
CA1 pyr cell: Inhibitory modulation of spatial selectivity+phase precession (Grienberger et al 2017)
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| 17. |
Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011)
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| 18. |
Cerebellar memory consolidation model (Yamazaki et al. 2015)
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| 19. |
Computing with neural synchrony (Brette 2012)
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| 20. |
Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
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| 21. |
Cortical oscillations and the basal ganglia (Fountas & Shanahan 2017)
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| 22. |
Development and Binocular Matching of Orientation Selectivity in Visual Cortex (Xu et al 2020)
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| 23. |
Diffusive homeostasis in a spiking network model (Sweeney et al. 2015)
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| 24. |
Disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex (Domanski et al 2019)
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| 25. |
Distributed cerebellar plasticity implements adaptable gain control (Garrido et al., 2013)
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| 26. |
Distributed synaptic plasticity and spike timing (Garrido et al. 2013)
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| 27. |
Dynamic dopamine modulation in the basal ganglia: Learning in Parkinson (Frank et al 2004,2005)
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| 28. |
Effects of increasing CREB on storage and recall processes in a CA1 network (Bianchi et al. 2014)
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| 29. |
Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
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| 30. |
Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014)
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| 31. |
Encoding and retrieval in a model of the hippocampal CA1 microcircuit (Cutsuridis et al. 2009)
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| 32. |
Fast convergence of cerebellar learning (Luque et al. 2015)
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| 33. |
First-Spike-Based Visual Categorization Using Reward-Modulated STDP (Mozafari et al. 2018)
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| 34. |
FNS spiking neural simulator; LIFL neuron model, event-driven simulation (Susi et al 2021)
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| 35. |
Formation of synfire chains (Jun and Jin 2007)
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| 36. |
Functional balanced networks with synaptic plasticity (Sadeh et al, 2015)
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| 37. |
Gamma genesis in the basolateral amygdala (Feng et al 2019)
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| 38. |
Gamma-beta alternation in the olfactory bulb (David, Fourcaud-Trocmé et al., 2015)
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| 39. |
Generation of stable heading representations in diverse visual scenes (Kim et al 2019)
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| 40. |
Grid cells from place cells (Castro & Aguiar, 2014)
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| 41. |
Hebbian STDP for modelling the emergence of disparity selectivity (Chauhan et al 2018)
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| 42. |
Homosynaptic plasticity in the tail withdrawal circuit (TWC) of Aplysia (Baxter and Byrne 2006)
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| 43. |
Hotspots of dendritic spine turnover facilitates new spines and NN sparsity (Frank et al 2018)
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| 44. |
Human layer 2/3 cortical microcircuits in health and depression (Yao et al, 2022)
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| 45. |
Hyperconnectivity, slow synapses in PFC mental retardation and autism model (Testa-Silva et al 2011)
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| 46. |
Inhibitory neuron plasticity as a mechanism for ocular dominance plasticity (Bono & Clopath 2019)
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| 47. |
Interplay between somatic and dendritic inhibition promotes place fields (Pedrosa & Clopath 2020)
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| 48. |
Large scale model of the olfactory bulb (Yu et al., 2013)
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| 49. |
Learning spatial transformations through STDP (Davison, Frégnac 2006)
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| 50. |
Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
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| 51. |
Logarithmic distributions prove that intrinsic learning is Hebbian (Scheler 2017)
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| 52. |
MEC PV-positive fast-spiking interneuron network generates theta-nested fast oscillations
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| 53. |
Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
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| 54. |
Minimal model of interictal and ictal discharges “Epileptor-2” (Chizhov et al 2018)
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| 55. |
Modeling dendritic spikes and plasticity (Bono and Clopath 2017)
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| 56. |
Motor system model with reinforcement learning drives virtual arm (Dura-Bernal et al 2017)
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| 57. |
Multistability of clustered states in a globally inhibitory network (Chandrasekaran et al. 2009)
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| 58. |
Network bursts in cultured NN result from different adaptive mechanisms (Masquelier & Deco 2013)
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| 59. |
Neural model of two-interval discrimination (Machens et al 2005)
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| 60. |
Olfactory bulb cluster formation (Migliore et al. 2010)
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| 61. |
Olfactory bulb mitral and granule cell column formation (Migliore et al. 2007)
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| 62. |
Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
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| 63. |
Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009)
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| 64. |
Parallel odor processing by mitral and middle tufted cells in the OB (Cavarretta et al 2016, 2018)
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| 65. |
Place and grid cells in a loop (Rennó-Costa & Tort 2017)
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| 66. |
Polychronization: Computation With Spikes (Izhikevich 2005)
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| 67. |
Rate model of a cortical RS-FS-LTS network (Hayut et al. 2011)
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| 68. |
Realistic barrel cortical column - Matlab (Huang et al., 2022)
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| 69. |
Realistic barrel cortical column - NetPyNE (Huang et al., 2022)
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| 70. |
Reinforcement learning of targeted movement (Chadderdon et al. 2012)
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| 71. |
Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
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| 72. |
Reward modulated STDP (Legenstein et al. 2008)
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| 73. |
Roles of subthalamic nucleus and DBS in reinforcement conflict-based decision making (Frank 2006)
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| 74. |
Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013)
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| 75. |
Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
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| 76. |
Single compartment Dorsal Lateral Medium Spiny Neuron w/ NMDA and AMPA (Biddell and Johnson 2013)
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| 77. |
Sleep-wake transitions in corticothalamic system (Bazhenov et al 2002)
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| 78. |
Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019)
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| 79. |
Spikes,synchrony,and attentive learning by laminar thalamocort. circuits (Grossberg & Versace 2007)
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| 80. |
Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013)
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| 81. |
Stability of complex spike timing-dependent plasticity in cerebellar learning (Roberts 2007)
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| 82. |
STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
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| 83. |
STDP promotes synchrony of inhibitory networks in the presence of heterogeneity (Talathi et al 2008)
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| 84. |
Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
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| 85. |
Synaptic plasticity can produce and enhance direction selectivity (Carver et al, 2008)
|
| 86. |
Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
|
| 87. |
V1 and AL spiking neural network for visual contrast response in mouse (Meijer et al. 2020)
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| 88. |
Vestibulo-Ocular Reflex model in Matlab (Clopath at al. 2014)
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