Model Concept: Learning

The ability of a neural network to change over time, or trials, its output in response to a set of, or a repetition of inputs.

Models:

  1. A 1000 cell network model for Lateral Amygdala (Kim et al. 2013)
  2. A Model of Selection between Stimulus and Place Strategy in a Hawkmoth (Balkenius et al. 2004)
  3. A large-scale model of the functioning brain (spaun) (Eliasmith et al. 2012)
  4. A model of antennal lobe of bee (Chen JY et al. 2015)
  5. A neurocomputational model of classical conditioning phenomena (Moustafa et al. 2009)
  6. A simple model of neuromodulatory state-dependent synaptic plasticity (Pedrosa and Clopath, 2016)
  7. A single-cell spiking model for the origin of grid-cell patterns (D'Albis & Kempter 2017)
  8. Acetylcholine-modulated plasticity in reward-driven navigation (Zannone et al 2018)
  9. Adaptation of Short-Term Plasticity parameters (Esposito et al. 2015)
  10. Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014)
  11. Alleviating catastrophic forgetting: context gating and synaptic stabilization (Masse et al 2018)
  12. Alternative time representation in dopamine models (Rivest et al. 2009)
  13. An electrophysiological model of GABAergic double bouquet cells (Chrysanthidis et al. 2019)
  14. Behavioral time scale synaptic plasticity underlies CA1 place fields (Bittner et al. 2017)
  15. CA1 pyramidal neurons: binding properties and the magical number 7 (Migliore et al. 2008)
  16. Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011)
  17. Cerebellar gain and timing control model (Yamazaki & Tanaka 2007)(Yamazaki & Nagao 2012)
  18. Cognitive and motor cortico-basal ganglia interactions during decision making (Guthrie et al 2013)
  19. Combining modeling, deep learning for MEA neuron localization, classification (Buccino et al 2018)
  20. Computational endophenotypes in addiction (Fiore et al 2018)
  21. Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
  22. Cortico - Basal Ganglia Loop (Mulcahy et al 2020)
  23. Cortico-striatal plasticity in medium spiny neurons (Gurney et al 2015)
  24. Democratic population decisions result in robust policy-gradient learning (Richmond et al. 2011)
  25. Encoding and retrieval in a model of the hippocampal CA1 microcircuit (Cutsuridis et al. 2009)
  26. FRAT: An amygdala-centered model of fear conditioning (Krasne et al. 2011)
  27. Functional balanced networks with synaptic plasticity (Sadeh et al, 2015)
  28. Hebbian learning in a random network for PFC modeling (Lindsay, et al. 2017)
  29. Hierarchical anti-Hebbian network model for the formation of spatial cells in 3D (Soman et al 2019)
  30. Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
  31. Logarithmic distributions prove that intrinsic learning is Hebbian (Scheler 2017)
  32. Model of cerebellar parallel fiber-Purkinje cell LTD and LTP (Gallimore et al 2018)
  33. Modelling gain modulation in stability-optimised circuits (Stroud et al 2018)
  34. Motor system model with reinforcement learning drives virtual arm (Dura-Bernal et al 2017)
  35. Multimodal stimuli learning in hawkmoths (Balkenius et al. 2008)
  36. Neuronify: An Educational Simulator for Neural Circuits (Dragly et al 2017)
  37. Olfactory bulb mitral and granule cell column formation (Migliore et al. 2007)
  38. Online learning model of olfactory bulb external plexiform layer network (Imam & Cleland 2020)
  39. Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
  40. Robust Reservoir Generation by Correlation-Based Learning (Yamazaki & Tanaka 2008)
  41. STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
  42. Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013)
  43. Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
  44. Single compartment Dorsal Lateral Medium Spiny Neuron w/ NMDA and AMPA (Biddell and Johnson 2013)
  45. Somatodendritic consistency check for temporal feature segmentation (Asabuki & Fukai 2020)
  46. Speed/accuracy trade-off between the habitual and the goal-directed processes (Kermati et al. 2011)
  47. Spike-timing dependent inhibitory plasticity for gating bAPs (Wilmes et al 2017)
  48. Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013)
  49. Supervised learning with predictive coding (Whittington & Bogacz 2017)
  50. Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
  51. Theta phase precession in a model CA3 place cell (Baker and Olds 2007)
Top authors for Learning:
Top concepts studied with Learning:
Top neurons studied with Learning:
Top currents studied with Learning:
Top references cited by these models: