Models that contain the Region : Neocortex

Re-display model names with descriptions
    Models
1.  2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex (Deitcher et al 2017)
2.  A computational model of systems memory consolidation and reconsolidation (Helfer & Shultz 2019)
3.  A fast model of voltage-dependent NMDA Receptors (Moradi et al. 2013)
4.  A Fast Rhythmic Bursting Cell: in vivo cell modeling (Lee 2007)
5.  A full-scale cortical microcircuit spiking network model (Shimoura et al 2018)
6.  A microcircuit model of the frontal eye fields (Heinzle et al. 2007)
7.  A Model Circuit of Thalamocortical Convergence (Behuret et al. 2013)
8.  A multilayer cortical model to study seizure propagation across microdomains (Basu et al. 2015)
9.  A Neural mass computational model of the Thalamocorticothalamic circuitry (Bhattacharya et al. 2011)
10.  A neural mass model for critical assessment of brain connectivity (Ursino et al 2020)
11.  A neural mass model of cross frequency coupling (Chehelcheraghi et al 2017)
12.  A neurocomputational model of classical conditioning phenomena (Moustafa et al. 2009)
13.  A single column thalamocortical network model (Traub et al 2005)
14.  A spiking model of cortical broadcast and competition (Shanahan 2008)
15.  A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
16.  Accurate and fast simulation of channel noise in conductance-based model neurons (Linaro et al 2011)
17.  Action potential-evoked Na+ influx are similar in axon and soma (Fleidervish et al. 2010)
18.  Action potential-evoked Na+ influx similar in axon and soma (Fleidervish et al. 2010) (Python)
19.  Allen Institute: Gad2-IRES-Cre VISp layer 5 472447460
20.  Allen Institute: Gad2-IRES-Cre VISp layer 5 473561729
21.  Allen Institute: Htr3a-Cre VISp layer 2/3 472352327
22.  Allen Institute: Htr3a-Cre VISp layer 2/3 472421285
23.  Allen Institute: Nr5a1-Cre VISp layer 2/3 473862496
24.  Allen Institute: Nr5a1-Cre VISp layer 4 329322394
25.  Allen Institute: Nr5a1-Cre VISp layer 4 472306544
26.  Allen Institute: Nr5a1-Cre VISp layer 4 472442377
27.  Allen Institute: Nr5a1-Cre VISp layer 4 472451419
28.  Allen Institute: Nr5a1-Cre VISp layer 4 472915634
29.  Allen Institute: Nr5a1-Cre VISp layer 4 473834758
30.  Allen Institute: Nr5a1-Cre VISp layer 4 473863035
31.  Allen Institute: Nr5a1-Cre VISp layer 4 473871429
32.  Allen Institute: Ntsr1-Cre VISp layer 4 472430904
33.  Allen Institute: Pvalb-IRES-Cre VISp layer 2/3 472306616
34.  Allen Institute: Pvalb-IRES-Cre VISp layer 5 471085845
35.  Allen Institute: Pvalb-IRES-Cre VISp layer 5 472349114
36.  Allen Institute: Pvalb-IRES-Cre VISp layer 5 472912177
37.  Allen Institute: Pvalb-IRES-Cre VISp layer 5 473465774
38.  Allen Institute: Pvalb-IRES-Cre VISp layer 5 473862421
39.  Allen Institute: Pvalb-IRES-Cre VISp layer 6a 471081668
40.  Allen Institute: Pvalb-IRES-Cre VISp layer 6a 472301074
41.  Allen Institute: Pvalb-IRES-Cre VISp layer 6a 473860269
42.  Allen Institute: Rbp4-Cre VISp layer 5 472424854
43.  Allen Institute: Rbp4-Cre VISp layer 6a 473871592
44.  Allen Institute: Rorb-IRES2-Cre-D VISp layer 2/3 472299294
45.  Allen Institute: Rorb-IRES2-Cre-D VISp layer 2/3 472434498
46.  Allen Institute: Rorb-IRES2-Cre-D VISp layer 4 473863510
47.  Allen Institute: Rorb-IRES2-Cre-D VISp layer 5 471087975
48.  Allen Institute: Rorb-IRES2-Cre-D VISp layer 5 473561660
49.  Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472300877
50.  Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472427533
51.  Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 472912107
52.  Allen Institute: Scnn1a-Tg2-Cre VISp layer 4 473465456
53.  Allen Institute: Scnn1a-Tg2-Cre VISp layer 5 472306460
54.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 329321704
55.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 472363762
56.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 473862845
57.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 473872986
58.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 472455509
59.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 473863578
60.  Allen Institute: Scnn1a-Tg3-Cre VISp layer 5 473871773
61.  Allen Institute: Sst-IRES-Cre VISp layer 2/3 471086533
62.  Allen Institute: Sst-IRES-Cre VISp layer 2/3 472304676
63.  Allen Institute: Sst-IRES-Cre VISp layer 4 472304539
64.  Allen Institute: Sst-IRES-Cre VISp layer 5 472299363
65.  Allen Institute: Sst-IRES-Cre VISp layer 5 472450023
66.  Allen Institute: Sst-IRES-Cre VISp layer 5 473835796
67.  Allen Institute: Sst-IRES-Cre VISp layer 6a 472440759
68.  Alpha rhythm in vitro visual cortex (Traub et al 2020)
69.  AP back-prop. explains threshold variability and rapid rise (McCormick et al. 2007, Yu et al. 2008)
70.  Apical Length Governs Computational Diversity of Layer 5 Pyramidal Neurons (Galloni et al 2020)
71.  Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009)
72.  Ave. neuron model for slow-wave sleep in cortex Tatsuki 2016 Yoshida 2018 Rasmussen 2017 (all et al)
73.  Axonal Projection and Interneuron Types (Helmstaedter et al. 2008)
74.  Basal ganglia-corticothalamic (BGCT) network (Chen et al., 2014)
75.  Biochemically detailed model of LTP and LTD in a cortical spine (Maki-Marttunen et al 2020)
76.  Biophysically realistic neural modeling of the MEG mu rhythm (Jones et al. 2009)
77.  Biophysically realistic neuron models for simulation of cortical stimulation (Aberra et al. 2018)
78.  Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)
79.  Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
80.  Combining modeling, deep learning for MEA neuron localization, classification (Buccino et al 2018)
81.  Compartmentalization of GABAergic inhibition by dendritic spines (Chiu et al. 2013)
82.  Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
83.  Comprehensive models of human cortical pyramidal neurons (Eyal et al 2018)
84.  Computational aspects of feedback in neural circuits (Maass et al 2006)
85.  Computational Surgery (Lytton et al. 2011)
86.  Computer models of corticospinal neurons replicate in vitro dynamics (Neymotin et al. 2017)
87.  CONFIGR: a vision-based model for long-range figure completion (Carpenter et al. 2007)
88.  Cortex-Basal Ganglia-Thalamus network model (Kumaravelu et al. 2016)
89.  Cortical Basal Ganglia Network Model during Closed-loop DBS (Fleming et al 2020)
90.  Cortical Layer 5b pyr. cell with [Na+]i mechanisms, from Hay et al 2011 (Zylbertal et al 2017)
91.  Cortical network model of posttraumatic epileptogenesis (Bush et al 1999)
92.  Current Dipole in Laminar Neocortex (Lee et al. 2013)
93.  Deconstruction of cortical evoked potentials generated by subthalamic DBS (Kumaravelu et al 2018)
94.  Dendritic action potentials and computation in human layer 2/3 cortical neurons (Gidon et al 2020)
95.  Dendritic action potentials and computation in human layer 2/3 cortical neurons (Gidon et al 2020)
96.  Dendritic Discrimination of Temporal Input Sequences (Branco et al. 2010)
97.  Dendritic Na+ spike initiation and backpropagation of APs in active dendrites (Nevian et al. 2007)
98.  Development of orientation-selective simple cell receptive fields (Rishikesh and Venkatesh, 2003)
99.  Distal inhibitory control of sensory-evoked excitation (Egger, Schmitt et al. 2015)
100.  Distinct integration properties of noisy inputs in active dendritic subunits (Poleg-Polsky 2019)
101.  Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016)
102.  Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
103.  Electrodecrements in in vitro model of infantile spasms (Traub et al 2020)
104.  Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014)
105.  Emergence of Connectivity Motifs in Networks of Model Neurons (Vasilaki, Giugliano 2014)
106.  Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011)
107.  Emergence of spatiotemporal sequences in spiking neuronal networks (Spreizer et al 2019)
108.  Engaging distinct oscillatory neocortical circuits (Vierling-Claassen et al. 2010)
109.  Entrainment and divisive inhibition in a neocortical neural mass model (Papasavvas et al 2020)
110.  Event-related simulation of neural processing in complex visual scenes (Mihalas et al. 2011)
111.  Excitability of PFC Basal Dendrites (Acker and Antic 2009)
112.  Extraction and classification of three cortical neuron types (Mensi et al. 2012)
113.  Firing neocortical layer V pyramidal neuron (Reetz et al. 2014; Stadler et al. 2014)
114.  Fitting predictive coding to the neurophysiological data (Spratling 2019)
115.  Four cortical interneuron subtypes (Kubota et al. 2011)
116.  Fronto-parietal visuospatial WM model with HH cells (Edin et al 2007)
117.  Functional consequences of cortical circuit abnormalities on gamma in schizophrenia (Spencer 2009)
118.  Hierarchical network model of perceptual decision making (Wimmer et al 2015)
119.  High dimensional dynamics and low dimensional readouts in neural microcircuits (Haeusler et al 2006)
120.  Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008)
121.  Human L2/3 pyramidal cells with low Cm values (Eyal et al. 2016)
122.  Huntington`s disease model (Gambazzi et al. 2010)
123.  Hyperconnectivity, slow synapses in PFC mental retardation and autism model (Testa-Silva et al 2011)
124.  I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
125.  Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010)
126.  Information-processing in lamina-specific cortical microcircuits (Haeusler and Maass 2006)
127.  Inhibition and glial-K+ interaction leads to diverse seizure transition modes (Ho & Truccolo 2016)
128.  Inhibition of bAPs and Ca2+ spikes in a multi-compartment pyramidal neuron model (Wilmes et al 2016)
129.  Inhibitory control by an integral feedback signal in prefrontal cortex (Miller and Wang 2006)
130.  Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011)
131.  Investigation of different targets in deep brain stimulation for Parkinson`s (Pirini et al. 2009)
132.  Irregular spiking in NMDA-driven prefrontal cortex neurons (Durstewitz and Gabriel 2006)
133.  Kernel method to calculate LFPs from networks of point neurons (Telenczuk et al 2020)
134.  Knox implementation of Destexhe 1998 spike and wave oscillation model (Knox et al 2018)
135.  L5 cortical neurons with recreated synaptic inputs in vitro correlation transfer (Linaro et al 2019)
136.  L5 PFC microcircuit used to study persistent activity (Papoutsi et al. 2014, 2013)
137.  L5 pyr. cell spiking control by oscillatory inhibition in distal apical dendrites (Li et al 2013)
138.  L5 pyramidal neuron myelination increases analog-digital facilitation extent (Zbili & Debanne 2020)
139.  L5b PC model constrained for BAC firing and perisomatic current step firing (Hay et al., 2011)
140.  Large cortex model with map-based neurons (Rulkov et al 2004)
141.  Large scale neocortical model for PGENESIS (Crone et al 2019)
142.  Large-scale laminar model of macaque cortex (Mejias et al 2016)
143.  Large-scale model of neocortical slice in vitro exhibiting persistent gamma (Tomsett et al. 2014)
144.  Layer V pyramidal cell functions and schizophrenia genetics (Mäki-Marttunen et al 2019)
145.  Layer V pyramidal cell model with reduced morphology (Mäki-Marttunen et al 2018)
146.  LFP signature of monosynaptic thalamocortical connection (Hagen et al 2017)
147.  Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
148.  Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009)
149.  Mechanisms for stable, robust, and adaptive development of orientation maps (Stevens et al. 2013)
150.  Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015)
151.  Mice Somatosensory L2/3 Pyramidal cells (Iascone et al 2020)
152.  Microcircuits of L5 thick tufted pyramidal cells (Hay & Segev 2015)
153.  Mirror Neuron (Antunes et al 2017)
154.  Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)
155.  Motor cortex microcircuit simulation based on brain activity mapping (Chadderdon et al. 2014)
156.  Multi-area layer-resolved spiking network model of resting-state dynamics in macaque visual cortex
157.  Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)
158.  Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)
159.  Network topologies for producing limited sustained activation (Kaiser and Hilgetag 2010)
160.  Neural mass model of the neocortex under sleep regulation (Costa et al 2016)
161.  Neural mass model of the sleeping cortex (Weigenand et al 2014)
162.  Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016)
163.  NN activity impact on neocortical pyr. neurons integrative properties in vivo (Destexhe & Pare 1999)
164.  NN for proto-object based contour integration and figure-ground segregation (Hu & Niebur 2017)
165.  Orientation preference in L23 V1 pyramidal neurons (Park et al 2019)
166.  Orientation selectivity in inhibition-dominated recurrent networks (Sadeh and Rotter, 2015)
167.  Persistent synchronized bursting activity in cortical tissues (Golomb et al 2005)
168.  Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010)
169.  Pipette and membrane patch geometry effects on GABAa currents patch-clamp exps (Moroni et al. 2011)
170.  Polychronization: Computation With Spikes (Izhikevich 2005)
171.  Prefrontal–striatal Parkinsons comp. model of multicue category learning (Moustafa and Gluck 2011)
172.  Preserving axosomatic spiking features despite diverse dendritic morphology (Hay et al., 2013)
173.  Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012)
174.  Reducing variability in motor cortex activity by GABA (Hoshino et al. 2019)
175.  Reinforcement learning of targeted movement (Chadderdon et al. 2012)
176.  Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
177.  Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)
178.  Reward modulated STDP (Legenstein et al. 2008)
179.  Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012)
180.  SCZ-associated variant effects on L5 pyr cell NN activity and delta osc. (Maki-Marttunen et al 2018)
181.  Selective control of cortical axonal spikes by a slowly inactivating K+ current (Shu et al. 2007)
182.  Sensory-evoked responses of L5 pyramidal tract neurons (Egger et al 2020)
183.  Shaping NMDA spikes by timed synaptic inhibition on L5PC (Doron et al. 2017)
184.  Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
185.  Spike propagation in dendrites with stochastic ion channels (Diba et al. 2006)
186.  Spontaneous weakly correlated excitation and inhibition (Tan et al. 2013)
187.  Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999)
188.  State and location dependence of action potential metabolic cost (Hallermann et al., 2012)
189.  Stochastic layer V pyramidal neuron: interpulse interval coding and noise (Singh & Levy 2017)
190.  Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)
191.  Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
192.  Systematic integration of data into multi-scale models of mouse primary V1 (Billeh et al 2020)
193.  Temporal integration by stochastic recurrent network (Okamoto et al. 2007)
194.  The origin of different spike and wave-like events (Hall et al 2017)
195.  The role of glutamate in neuronal ion homeostasis: spreading depolarization (Hubel et al 2017)
196.  Theoretical principles of DBS induced synaptic suppression (Farokhniaee & McIntyre 2019)
197.  Theory of sequence memory in neocortex (Hawkins & Ahmad 2016)
198.  Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019)
199.  Two populations of excitatory neurons in the superficial retrosplenial cortex (Brennan et al 2020)
200.  Unbalanced peptidergic inhibition in superficial cortex underlies seizure activity (Hall et al 2015)
201.  V1 and AL spiking neural network for visual contrast response in mouse (Meijer et al. 2020)
202.  Visual physiology of the layer 4 cortical circuit in silico (Arkhipov et al 2018)

Re-display model names with descriptions