Eguchi A, Neymotin SA, Stringer SM. (2014). Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity Frontiers in neural circuits. 8 [PubMed]

• Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014) [Model]

Esposito U, Giugliano M, Vasilaki E. (2014). Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity. Frontiers in computational neuroscience. 8 [PubMed]

• Adaptation of Short-Term Plasticity parameters (Esposito et al. 2015) [Model]

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]
• Layer V pyramidal cell model with reduced morphology (Mäki-Marttunen et al 2018) [Model]

Helmstaedter M, Sakmann B, Feldmeyer D. (2009). The relation between dendritic geometry, electrical excitability, and axonal projections of L2/3 interneurons in rat barrel cortex. Cerebral cortex (New York, N.Y. : 1991). 19 [PubMed]

• Axonal Projection and Interneuron Types (Helmstaedter et al. 2008) [Model]

Helmstaedter M, Staiger JF, Sakmann B, Feldmeyer D. (2008). Efficient recruitment of layer 2/3 interneurons by layer 4 input in single columns of rat somatosensory cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 28 [PubMed]

• Axonal Projection and Interneuron Types (Helmstaedter et al. 2008) [Model]

Hilgetag CC, Kaiser M. (2010). Optimal hierarchical modular topologies for producing limited sustained activation of neural networks Front. Neuroinform.. 4(8)

• Network topologies for producing limited sustained activation (Kaiser and Hilgetag 2010) [Model]

Hong S, Ratté S, Prescott SA, De Schutter E. (2012). Single neuron firing properties impact correlation-based population coding. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

• A model for how correlation depends on the neuronal excitability type (Hong et al. 2012) [Model]

Nandy AS, Nassi JJ, Reynolds JH. (2017). Laminar Organization of Attentional Modulation in Macaque Visual Area V4. Neuron. 93 [PubMed]

Neymotin SA, Lee H, Park E, Fenton AA, Lytton WW. (2011). Emergence of physiological oscillation frequencies in a computer model of neocortex. Frontiers in computational neuroscience. 5 [PubMed]

• Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011) [Model]

Potjans TC, Diesmann M. (2014). The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. Cerebral cortex (New York, N.Y. : 1991). 24 [PubMed]

• A full-scale cortical microcircuit spiking network model (Shimoura et al 2018) [Model]

Puigbò JY et al. (2018). Cholinergic Behavior State-Dependent Mechanisms of Neocortical Gain Control: a Neurocomputational Study. Molecular neurobiology. 55 [PubMed]

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]