Models that contain the Region : Neocortex

Re-display model names with descriptions
    Models
1. A fast model of voltage-dependent NMDA Receptors (Moradi et al. 2013)
2. A Fast Rhythmic Bursting Cell: in vivo cell modeling (Lee 2007)
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 of cross frequency coupling (Chehelcheraghi et al 2017)
8. A neurocomputational model of classical conditioning phenomena (Moustafa et al. 2009)
9. A single column thalamocortical network model (Traub et al 2005)
10. A spiking model of cortical broadcast and competition (Shanahan 2008)
11. A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
12. Accurate and fast simulation of channel noise in conductance-based model neurons (Linaro et al 2011)
13. Action potential-evoked Na+ influx are similar in axon and soma (Fleidervish et al. 2010)
14. Allen Institute: Gad2-IRES-Cre VISp layer 5 472447460
15. Allen Institute: Gad2-IRES-Cre VISp layer 5 473561729
16. Allen Institute: Htr3a-Cre VISp layer 2/3 472352327
17. Allen Institute: Htr3a-Cre VISp layer 2/3 472421285
18. Allen Institute: Nr5a1-Cre VISp layer 2/3 473862496
19. Allen Institute: Nr5a1-Cre VISp layer 4 329322394
20. Allen Institute: Nr5a1-Cre VISp layer 4 472306544
21. Allen Institute: Nr5a1-Cre VISp layer 4 472442377
22. Allen Institute: Nr5a1-Cre VISp layer 4 472451419
23. Allen Institute: Nr5a1-Cre VISp layer 4 472915634
24. Allen Institute: Nr5a1-Cre VISp layer 4 473834758
25. Allen Institute: Nr5a1-Cre VISp layer 4 473863035
26. Allen Institute: Nr5a1-Cre VISp layer 4 473871429
27. Allen Institute: Ntsr1-Cre VISp layer 4 472430904
28. Allen Institute: Pvalb-IRES-Cre VISp layer 2/3 472306616
29. Allen Institute: Pvalb-IRES-Cre VISp layer 5 471085845
30. Allen Institute: Pvalb-IRES-Cre VISp layer 5 472349114
31. Allen Institute: Pvalb-IRES-Cre VISp layer 5 472912177
32. Allen Institute: Pvalb-IRES-Cre VISp layer 5 473465774
33. Allen Institute: Pvalb-IRES-Cre VISp layer 5 473862421
34. Allen Institute: Pvalb-IRES-Cre VISp layer 6a 471081668
35. Allen Institute: Pvalb-IRES-Cre VISp layer 6a 472301074
36. Allen Institute: Pvalb-IRES-Cre VISp layer 6a 473860269
37. Allen Institute: Rbp4-Cre VISp layer 5 472424854
38. Allen Institute: Rbp4-Cre VISp layer 6a 473871592
39. Allen Institute: Rorb-IRES2-Cre-D VISp layer 2/3 472299294
40. Allen Institute: Rorb-IRES2-Cre-D VISp layer 2/3 472434498
41. Allen Institute: Rorb-IRES2-Cre-D VISp layer 4 473863510
42. Allen Institute: Rorb-IRES2-Cre-D VISp layer 5 471087975
43. Allen Institute: Rorb-IRES2-Cre-D VISp layer 5 473561660
44. Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472300877
45. Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472427533
46. Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472912107
47. Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 473465456
48. Allen Institute: Scnn1a-Tg2-Cre VISp layer 5 472306460
49. Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 329321704
50. Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 472363762
51. Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 473862845
52. Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 473872986
53. Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 472455509
54. Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 473863578
55. Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 473871773
56. Allen Institute: Sst-IRES-Cre VISp layer 2/3 471086533
57. Allen Institute: Sst-IRES-Cre VISp layer 2/3 472304676
58. Allen Institute: Sst-IRES-Cre VISp layer 4 472304539
59. Allen Institute: Sst-IRES-Cre VISp layer 5 472299363
60. Allen Institute: Sst-IRES-Cre VISp layer 5 472450023
61. Allen Institute: Sst-IRES-Cre VISp layer 5 473835796
62. Allen Institute: Sst-IRES-Cre VISp layer 6a 472440759
63. AP back-prop. explains threshold variability and rapid rise (McCormick et al. 2007, Yu et al. 2008)
64. Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009)
65. Axonal Projection and Interneuron Types (Helmstaedter et al. 2008)
66. Basal ganglia-corticothalamic (BGCT) network (Chen et al., 2014)
67. Biophysically realistic neural modeling of the MEG mu rhythm (Jones et al. 2009)
68. Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)
69. Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
70. Compartmentalization of GABAergic inhibition by dendritic spines (Chiu et al. 2013)
71. Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
72. Computational aspects of feedback in neural circuits (Maass et al 2006)
73. Computational Surgery (Lytton et al. 2011)
74. Computer models of corticospinal neurons replicate in vitro dynamics (Neymotin et al. 2017)
75. CONFIGR: a vision-based model for long-range figure completion (Carpenter et al. 2007)
76. Cortex-Basal Ganglia-Thalamus network model (Kumaravelu et al. 2016)
77. Cortical Layer 5b pyr. cell with [Na+]i mechanisms, from Hay et al 2011 (Zylbertal et al 2017)
78. Cortical network model of posttraumatic epileptogenesis (Bush et al 1999)
79. Current Dipole in Laminar Neocortex (Lee et al. 2013)
80. Dendritic Discrimination of Temporal Input Sequences (Branco et al. 2010)
81. Dendritic Na+ spike initiation and backpropagation of APs in active dendrites (Nevian et al. 2007)
82. Development of orientation-selective simple cell receptive fields (Rishikesh and Venkatesh, 2003)
83. Distal inhibitory control of sensory-evoked excitation (Egger, Schmitt et al. 2015)
84. Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
85. Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014)
86. Emergence of Connectivity Motifs in Networks of Model Neurons (Vasilaki, Giugliano 2014)
87. Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011)
88. Engaging distinct oscillatory neocortical circuits (Vierling-Claassen et al. 2010)
89. Event-related simulation of neural processing in complex visual scenes (Mihalas et al. 2011)
90. Excitability of PFC Basal Dendrites (Acker and Antic 2009)
91. Extraction and classification of three cortical neuron types (Mensi et al. 2012)
92. Firing neocortical layer V pyramidal neuron (Reetz et al. 2014; Stadler et al. 2014)
93. Four cortical interneuron subtypes (Kubota et al. 2011)
94. Fronto-parietal visuospatial WM model with HH cells (Edin et al 2007)
95. Functional consequences of cortical circuit abnormalities on gamma in schizophrenia (Spencer 2009)
96. Hierarchical network model of perceptual decision making (Wimmer et al 2015)
97. High dimensional dynamics and low dimensional readouts in neural microcircuits (Haeusler et al 2006)
98. Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008)
99. Human L2/3 pyramidal cells with low Cm values (Eyal et al. 2016)
100. Huntington`s disease model (Gambazzi et al. 2010)
101. Hyperconnectivity, slow synapses in PFC mental retardation and autism model (Testa-Silva et al 2011)
102. I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
103. Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010)
104. Information-processing in lamina-specific cortical microcircuits (Haeusler and Maass 2006)
105. Inhibition and glial-K+ interaction leads to diverse seizure transition modes (Ho & Truccolo 2016)
106. Inhibition of bAPs and Ca2+ spikes in a multi-compartment pyramidal neuron model (Wilmes et al 2016)
107. Inhibitory control by an integral feedback signal in prefrontal cortex (Miller and Wang 2006)
108. Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011)
109. Investigation of different targets in deep brain stimulation for Parkinson`s (Pirini et al. 2009)
110. Irregular spiking in NMDA-driven prefrontal cortex neurons (Durstewitz and Gabriel 2006)
111. L5 PFC microcircuit used to study persistent activity (Papoutsi et al. 2014, 2013)
112. L5 pyr. cell spiking control by oscillatory inhibition in distal apical dendrites (Li et al 2013)
113. L5b PC model constrained for BAC firing and perisomatic current step firing (Hay et al., 2011)
114. Large cortex model with map-based neurons (Rulkov et al 2004)
115. Large-scale model of neocortical slice in vitro exhibiting persistent gamma (Tomsett et al. 2014)
116. Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
117. Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009)
118. Mechanisms for stable, robust, and adaptive development of orientation maps (Stevens et al. 2013)
119. Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015)
120. Microcircuits of L5 thick tufted pyramidal cells (Hay & Segev 2015)
121. Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)
122. Motor cortex microcircuit simulation based on brain activity mapping (Chadderdon et al. 2014)
123. Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)
124. Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)
125. Network topologies for producing limited sustained activation (Kaiser and Hilgetag 2010)
126. Neural mass model of the neocortex under sleep regulation (Costa et al 2016)
127. Neural mass model of the sleeping cortex (Weigenand et al 2014)
128. Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016)
129. Orientation selectivity in inhibition-dominated recurrent networks (Sadeh and Rotter, 2015)
130. Persistent synchronized bursting activity in cortical tissues (Golomb et al 2005)
131. Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)
132. Pipette and membrane patch geometry effects on GABAa currents patch-clamp exps (Moroni et al. 2011)
133. Polychronization: Computation With Spikes (Izhikevich 2005)
134. Prefrontal–striatal Parkinsons comp. model of multicue category learning (Moustafa and Gluck 2011)
135. Preserving axosomatic spiking features despite diverse dendritic morphology (Hay et al., 2013)
136. Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012)
137. Reinforcement learning of targeted movement (Chadderdon et al. 2012)
138. Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
139. Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)
140. Reward modulated STDP (Legenstein et al. 2008)
141. Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012)
142. Selective control of cortical axonal spikes by a slowly inactivating K+ current (Shu et al. 2007)
143. Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
144. Spike propagation in dendrites with stochastic ion channels (Diba et al. 2006)
145. Spontaneous weakly correlated excitation and inhibition (Tan et al. 2013)
146. Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999)
147. State and location dependence of action potential metabolic cost (Hallermann et al., 2012)
148. Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)
149. Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
150. Temporal integration by stochastic recurrent network (Okamoto et al. 2007)
151. Theory of sequence memory in neocortex (Hawkins & Ahmad 2016)

Re-display model names with descriptions