| | Models |
| 1. |
A computational model of systems memory consolidation and reconsolidation (Helfer & Shultz 2019)
|
| 2. |
A full-scale cortical microcircuit spiking network model (Shimoura et al 2018)
|
| 3. |
A microcircuit model of the frontal eye fields (Heinzle et al. 2007)
|
| 4. |
A Model Circuit of Thalamocortical Convergence (Behuret et al. 2013)
|
| 5. |
A multilayer cortical model to study seizure propagation across microdomains (Basu et al. 2015)
|
| 6. |
A Neural mass computational model of the Thalamocorticothalamic circuitry (Bhattacharya et al. 2011)
|
| 7. |
A neural mass model for critical assessment of brain connectivity (Ursino et al 2020)
|
| 8. |
A single column thalamocortical network model (Traub et al 2005)
|
| 9. |
A spiking model of cortical broadcast and competition (Shanahan 2008)
|
| 10. |
A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
|
| 11. |
Alpha rhythm in vitro visual cortex (Traub et al 2020)
|
| 12. |
Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009)
|
| 13. |
Biophysically realistic neural modeling of the MEG mu rhythm (Jones et al. 2009)
|
| 14. |
Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)
|
| 15. |
Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
|
| 16. |
Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
|
| 17. |
Computational aspects of feedback in neural circuits (Maass et al 2006)
|
| 18. |
Computational Surgery (Lytton et al. 2011)
|
| 19. |
Cortex-Basal Ganglia-Thalamus network model (Kumaravelu et al. 2016)
|
| 20. |
Cortical Basal Ganglia Network Model during Closed-loop DBS (Fleming et al 2020)
|
| 21. |
Cortical Interneuron & Pyramidal Cell Model of Cortical Spreading Depression (Stein & Harris 2022)
|
| 22. |
Current Dipole in Laminar Neocortex (Lee et al. 2013)
|
| 23. |
Deconstruction of cortical evoked potentials generated by subthalamic DBS (Kumaravelu et al 2018)
|
| 24. |
Development of orientation-selective simple cell receptive fields (Rishikesh and Venkatesh, 2003)
|
| 25. |
Distal inhibitory control of sensory-evoked excitation (Egger, Schmitt et al. 2015)
|
| 26. |
Distributed working memory in large-scale macaque brain model (Mejias and Wang, 2022)
|
| 27. |
Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016)
|
| 28. |
Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
|
| 29. |
Electrodecrements in in vitro model of infantile spasms (Traub et al 2020)
|
| 30. |
Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014)
|
| 31. |
Emergence of Connectivity Motifs in Networks of Model Neurons (Vasilaki, Giugliano 2014)
|
| 32. |
Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011)
|
| 33. |
Emergence of spatiotemporal sequences in spiking neuronal networks (Spreizer et al 2019)
|
| 34. |
Engaging distinct oscillatory neocortical circuits (Vierling-Claassen et al. 2010)
|
| 35. |
Event-related simulation of neural processing in complex visual scenes (Mihalas et al. 2011)
|
| 36. |
Fronto-parietal visuospatial WM model with HH cells (Edin et al 2007)
|
| 37. |
Functional consequences of cortical circuit abnormalities on gamma in schizophrenia (Spencer 2009)
|
| 38. |
Hierarchical network model of perceptual decision making (Wimmer et al 2015)
|
| 39. |
High dimensional dynamics and low dimensional readouts in neural microcircuits (Haeusler et al 2006)
|
| 40. |
Human L5 Cortical Circuit (Guet-McCreight)
|
| 41. |
Human layer 2/3 cortical microcircuits in health and depression (Yao et al, 2022)
|
| 42. |
Huntington`s disease model (Gambazzi et al. 2010)
|
| 43. |
Hyperconnectivity, slow synapses in PFC mental retardation and autism model (Testa-Silva et al 2011)
|
| 44. |
I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
|
| 45. |
Information-processing in lamina-specific cortical microcircuits (Haeusler and Maass 2006)
|
| 46. |
Inhibition and glial-K+ interaction leads to diverse seizure transition modes (Ho & Truccolo 2016)
|
| 47. |
Inhibitory control by an integral feedback signal in prefrontal cortex (Miller and Wang 2006)
|
| 48. |
Investigation of different targets in deep brain stimulation for Parkinson`s (Pirini et al. 2009)
|
| 49. |
Irregular spiking in NMDA-driven prefrontal cortex neurons (Durstewitz and Gabriel 2006)
|
| 50. |
Knox implementation of Destexhe 1998 spike and wave oscillation model (Knox et al 2018)
|
| 51. |
L5 PFC microcircuit used to study persistent activity (Papoutsi et al. 2014, 2013)
|
| 52. |
Large cortex model with map-based neurons (Rulkov et al 2004)
|
| 53. |
Large scale neocortical model for PGENESIS (Crone et al 2019)
|
| 54. |
Large-scale model of neocortical slice in vitro exhibiting persistent gamma (Tomsett et al. 2014)
|
| 55. |
LFP signature of monosynaptic thalamocortical connection (Hagen et al 2017)
|
| 56. |
Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
|
| 57. |
LIP and FEF rhythmic attention model (Aussel et al. 2023)
|
| 58. |
Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009)
|
| 59. |
Mechanisms for stable, robust, and adaptive development of orientation maps (Stevens et al. 2013)
|
| 60. |
Microcircuits of L5 thick tufted pyramidal cells (Hay & Segev 2015)
|
| 61. |
Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)
|
| 62. |
Motor cortex microcircuit simulation based on brain activity mapping (Chadderdon et al. 2014)
|
| 63. |
Multi-area layer-resolved spiking network model of resting-state dynamics in macaque visual cortex
|
| 64. |
Multiscale model of primary motor cortex circuits predicts in vivo dynamics (Dura-Bernal et al 2023)
|
| 65. |
Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)
|
| 66. |
Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)
|
| 67. |
Network topologies for producing limited sustained activation (Kaiser and Hilgetag 2010)
|
| 68. |
Neural Mass Model for relationship between Brain Rhythms + Functional Connectivity (Ricci et al '21)
|
| 69. |
NN for proto-object based contour integration and figure-ground segregation (Hu & Niebur 2017)
|
| 70. |
Orientation selectivity in inhibition-dominated recurrent networks (Sadeh and Rotter, 2015)
|
| 71. |
Persistent synchronized bursting activity in cortical tissues (Golomb et al 2005)
|
| 72. |
Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)
|
| 73. |
PING, ING and CHING network models for Gamma oscillations in cortex (Susin and Destexhe 2021)
|
| 74. |
Polychronization: Computation With Spikes (Izhikevich 2005)
|
| 75. |
Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012)
|
| 76. |
Reducing variability in motor cortex activity by GABA (Hoshino et al. 2019)
|
| 77. |
Reinforcement learning of targeted movement (Chadderdon et al. 2012)
|
| 78. |
Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
|
| 79. |
Reward modulated STDP (Legenstein et al. 2008)
|
| 80. |
Sensory-evoked responses of L5 pyramidal tract neurons (Egger et al 2020)
|
| 81. |
Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
|
| 82. |
Spontaneous weakly correlated excitation and inhibition (Tan et al. 2013)
|
| 83. |
Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999)
|
| 84. |
Stoney vs Histed: Quantifying spatial effects of intracortical microstims (Kumaravelu et al 2022)
|
| 85. |
Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)
|
| 86. |
Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
|
| 87. |
Systematic integration of data into multi-scale models of mouse primary V1 (Billeh et al 2020)
|
| 88. |
Temporal integration by stochastic recurrent network (Okamoto et al. 2007)
|
| 89. |
Thalamo-cortical microcircuit (TCM) (AmirAli Farokhniaee and Madeleine M. Lowery 2021)
|
| 90. |
The origin of different spike and wave-like events (Hall et al 2017)
|
| 91. |
Theory of sequence memory in neocortex (Hawkins & Ahmad 2016)
|
| 92. |
Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019)
|
| 93. |
Unbalanced peptidergic inhibition in superficial cortex underlies seizure activity (Hall et al 2015)
|
| 94. |
V1 and AL spiking neural network for visual contrast response in mouse (Meijer et al. 2020)
|
| 95. |
Visual physiology of the layer 4 cortical circuit in silico (Arkhipov et al 2018)
|
