Azouz R, Gray CM. (2008). Stimulus-selective spiking is driven by the relative timing of synchronous excitation and disinhibition in cat striate neurons in vivo. The European journal of neuroscience. 28 [PubMed]

Carracedo LM et al. (2013). A neocortical delta rhythm facilitates reciprocal interlaminar interactions via nested theta rhythms. The Journal of neuroscience : the official journal of the Society for Neuroscience. 33 [PubMed]

• Dynamic cortical interlaminar interactions (Carracedo et al. 2013) [Model]
• Electrodecrements in in vitro model of infantile spasms (Traub et al 2020) [Model]

Clopath C, Pedrosa V. (2017). The role of neuromodulators in cortical plasticity. A computational perspective. Front. Synaptic Neurosci.. 8

• A simple model of neuromodulatory state-dependent synaptic plasticity (Pedrosa and Clopath, 2016) [Model]

Delgado JY, Gómez-González JF, Desai NS. (2010). Pyramidal neuron conductance state gates spike-timing-dependent plasticity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 30 [PubMed]

• Pyramidal neuron conductances state and STDP (Delgado et al. 2010) [Model]

Diamond JS, Polsky A. (2011). Imperfect Space Clamp Permits Electrotonic Interactions between Inhibitory and Excitatory Synaptic Conductances, Distorting Voltage Clamp Recordings. PLoS ONE. 6(4)

• Interacting synaptic conductances during, distorting, voltage clamp (Poleg-Polsky and Diamond 2011) [Model]

Gilson M, Masquelier T, Hugues E. (2011). STDP allows fast rate-modulated coding with Poisson-like spike trains. PLoS computational biology. 7 [PubMed]

• STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011) [Model]

Gütig R, Sompolinsky H. (2009). Time-warp-invariant neuronal processing. PLoS biology. 7 [PubMed]

• Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009) [Model]

Jercog D et al. (2017). UP-DOWN cortical dynamics reflect state transitions in a bistable network. eLife. 6 [PubMed]

• Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017) [Model]

Keane A, Henderson JA, Gong P. (2018). Dynamical patterns underlying response properties of cortical circuits. Journal of the Royal Society, Interface. 15 [PubMed]

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

Kepecs A, Raghavachari S. (2007). Gating information by two-state membrane potential fluctuations. Journal of neurophysiology. 97 [PubMed]

Khalil R, Moftah MZ, Moustafa AA. (2017). The effects of dynamical synapses on firing rate activity: a spiking neural network model. The European journal of neuroscience. 46 [PubMed]

Krishnan GP et al. (2016). Cellular and neurochemical basis of sleep stages in the thalamocortical network. eLife. 5 [PubMed]

• Thalamocortical sleep model (Krishnan et al., 2016) [Model]

Lim S, Goldman MS. (2013). Balanced cortical microcircuitry for maintaining information in working memory. Nature neuroscience. 16 [PubMed]

• Model of working memory based on negative derivative feedback (Lim and Goldman, 2013) [Model]

Lim S, Goldman MS. (2014). Balanced cortical microcircuitry for spatial working memory based on corrective feedback control. The Journal of neuroscience : the official journal of the Society for Neuroscience. 34 [PubMed]

Markram H et al. (2015). Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 163 [PubMed]

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

Papoutsi A, Sidiropoulou K, Poirazi P. (2014). Dendritic nonlinearities reduce network size requirements and mediate ON and OFF states of persistent activity in a PFC microcircuit model. PLoS computational biology. 10 [PubMed]

• L5 PFC microcircuit used to study persistent activity (Papoutsi et al. 2014, 2013) [Model]

Pernelle G, Nicola W, Clopath C. (2018). Gap junction plasticity as a mechanism to regulate network-wide oscillations. PLoS computational biology. 14 [PubMed]

• Gap junction plasticity as a mechanism to regulate network-wide oscillations (Pernelle et al 2018) [Model]

Polsky A, Mel B, Schiller J. (2009). Encoding and decoding bursts by NMDA spikes in basal dendrites of layer 5 pyramidal neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience. 29 [PubMed]

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

Pospischil M, Piwkowska Z, Rudolph M, Bal T, Destexhe A. (2007). Calculating event-triggered average synaptic conductances from the membrane potential. Journal of neurophysiology. 97 [PubMed]

• Code to calc. spike-trig. ave (STA) conduct. from Vm (Pospischil et al. 2007, Rudolph et al. 2007) [Model]

Rudolph M, Pospischil M, Timofeev I, Destexhe A. (2007). Inhibition determines membrane potential dynamics and controls action potential generation in awake and sleeping cat cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 27 [PubMed]

• Code to calc. spike-trig. ave (STA) conduct. from Vm (Pospischil et al. 2007, Rudolph et al. 2007) [Model]

Shu Y, Duque A, Yu Y, Haider B, McCormick DA. (2007). Properties of action-potential initiation in neocortical pyramidal cells: evidence from whole cell axon recordings. Journal of neurophysiology. 97 [PubMed]

• Intracortical synaptic potential modulation by presynaptic somatic potential (Shu et al. 2006, 2007) [Model]

Tan AY, Andoni S, Priebe NJ. (2013). A spontaneous state of weakly correlated synaptic excitation and inhibition in visual cortex. Neuroscience. 247 [PubMed]

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

Yu Y, Migliore M, Hines ML, Shepherd GM. (2014). Sparse coding and lateral inhibition arising from balanced and unbalanced dendrodendritic excitation and inhibition. The Journal of neuroscience : the official journal of the Society for Neuroscience. 34 [PubMed]