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Bohte SM, Mozer MC. (2007). Reducing the variability of neural responses: a computational theory of spike-timing-dependent plasticity. Neural computation. 19 [PubMed]

Clopath C, Büsing L, Vasilaki E, Gerstner W. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature neuroscience. 13 [PubMed]

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Dyhrfjeld-Johnsen J et al. (2007). Topological determinants of epileptogenesis in large-scale structural and functional models of the dentate gyrus derived from experimental data. Journal of neurophysiology. 97 [PubMed]

• Dentate gyrus (Morgan et al. 2007, 2008, Santhakumar et al. 2005, Dyhrfjeld-Johnsen et al. 2007) [Model]

Egger R et al. (2020). Cortical Output Is Gated by Horizontally Projecting Neurons in the Deep Layers Neuron. 105

• Sensory-evoked responses of L5 pyramidal tract neurons (Egger et al 2020) [Model]

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Esposito U, Giugliano M, van Rossum M, Vasilaki E. (2014). Measuring symmetry, asymmetry and randomness in neural network connectivity. PloS one. 9 [PubMed]

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Gal E et al. (2017). Rich cell-type-specific network topology in neocortical microcircuitry. Nature neuroscience. 20 [PubMed]

• The neocortical microcircuit collaboration portal (Markram et al. 2015) [Model]

Gilra A, Bhalla US. (2015). Bulbar microcircuit model predicts connectivity and roles of interneurons in odor coding. PloS one. 10 [PubMed]

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Golomb D et al. (2017). Mechanisms underlying a thalamocortical transformation during active tactile sensation PLoS Comput Biol. 13(6)

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Gourévitch B, Eggermont JJ. (2007). Evaluating information transfer between auditory cortical neurons. Journal of neurophysiology. 97 [PubMed]

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Hay E, Segev I. (2015). Dendritic Excitability and Gain Control in Recurrent Cortical Microcircuits. Cerebral cortex (New York, N.Y. : 1991). 25 [PubMed]

• Microcircuits of L5 thick tufted pyramidal cells (Hay & Segev 2015) [Model]
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Hooks BM et al. (2011). Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas. PLoS biology. 9 [PubMed]

• Laminar analysis of excitatory circuits in vibrissal motor and sensory cortex (Hooks et al. 2011) [Model]

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• Striatal GABAergic microcircuit, spatial scales of dynamics (Humphries et al, 2010) [Model]

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• Dynamical patterns underlying response properties of cortical circuits (Keane et al 2018) [Model]

Kerr CC et al. (2013). Cortical information flow in Parkinson's disease: a composite network/field model. Frontiers in computational neuroscience. 7 [PubMed]

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Kitano K, Fukai T. (2007). Variability v.s. synchronicity of neuronal activity in local cortical network models with different wiring topologies. Journal of computational neuroscience. 23 [PubMed]

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• GLMCC validation neural network model (Kobayashi et al. 2019) [Model]

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• Excitatory and inhibitory population activity (Bittner et al 2017) (Litwin-Kumar & Doiron 2017) [Model]

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• Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010) [Model]

Matsubara T, Torikai H. (2016). An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities. IEEE transactions on neural networks and learning systems. 27 [PubMed]

Mejias JF, Murray JD, Kennedy H, Wang XJ. (2016). Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex. Science advances. 2 [PubMed]

• Large-scale laminar model of macaque cortex (Mejias et al 2016) [Model]

Morgan RJ, Santhakumar V, Soltesz I. (2007). Modeling the dentate gyrus. Progress in brain research. 163 [PubMed]

• Dentate gyrus (Morgan et al. 2007, 2008, Santhakumar et al. 2005, Dyhrfjeld-Johnsen et al. 2007) [Model]

Morgan RJ, Soltesz I. (2008). Nonrandom connectivity of the epileptic dentate gyrus predicts a major role for neuronal hubs in seizures. Proceedings of the National Academy of Sciences of the United States of America. 105 [PubMed]

• Dentate gyrus (Morgan et al. 2007, 2008, Santhakumar et al. 2005, Dyhrfjeld-Johnsen et al. 2007) [Model]

Mäki-Marttunen T, Aćimović J, Ruohonen K, Linne ML. (2013). Structure-dynamics relationships in bursting neuronal networks revealed using a prediction framework. PloS one. 8 [PubMed]

• Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013) [Model]

Mäki-Marttunen T et al. (2018). A stepwise neuron model fitting procedure designed for recordings with high spatial resolution: Application to layer 5 pyramidal cells. Journal of neuroscience methods. 293 [PubMed]

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• NMDA spikes in basal dendrites of L5 pyramidal neurons (Polsky et al. 2009) [Model]

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• The neocortical microcircuit collaboration portal (Markram et al. 2015) [Model]

Reimann MW et al. (2017). Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function. Frontiers in computational neuroscience. 11 [PubMed]

• The neocortical microcircuit collaboration portal (Markram et al. 2015) [Model]

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• Functional balanced networks with synaptic plasticity (Sadeh et al, 2015) [Model]

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• Multi-area layer-resolved spiking network model of resting-state dynamics in macaque visual cortex [Model]

Schmidt M et al. (2018). A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas. PLoS computational biology. 14 [PubMed]

• Multi-area layer-resolved spiking network model of resting-state dynamics in macaque visual cortex [Model]

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• Modeling maintenance of Long-Term Potentiation in clustered synapses (Smolen 2015) [Model]

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• Method for deriving general HH neuron model`s spiking input-output relation (Soudry & Meir 2014) [Model]

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• Spontaneous weakly correlated excitation and inhibition (Tan et al. 2013) [Model]

Tikidji-Hamburyan RA, Martínez JJ, White JA, Canavier CC. (2015). Resonant Interneurons Can Increase Robustness of Gamma Oscillations. The Journal of neuroscience : the official journal of the Society for Neuroscience. 35 [PubMed]

• PIR gamma oscillations in network of resonators (Tikidji-Hamburyan et al. 2015) [Model]

Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. (2014). Connection-type-specific biases make uniform random network models consistent with cortical recordings. Journal of neurophysiology. 112 [PubMed]

Ursino M, Ricci G, Magosso E. (2020). Transfer Entropy as a Measure of Brain Connectivity: A Critical Analysis With the Help of Neural Mass Models Frontiers in computational neuroscience. 14 [PubMed]

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• Emergence of Connectivity Motifs in Networks of Model Neurons (Vasilaki, Giugliano 2014) [Model]

Vogels TP, Abbott LF. (2005). Signal propagation and logic gating in networks of integrate-and-fire neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience. 25 [PubMed]

• Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007) [Model]
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van Ooyen A et al. (2014). Independently outgrowing neurons and geometry-based synapse formation produce networks with realistic synaptic connectivity. PloS one. 9 [PubMed]

• NETMORPH: creates NNs with realistic neuron morphologies (Koene et al. 2009, van Ooyen et al. 2014) [Model]