Acker CD, Antic SD. (2009). Quantitative assessment of the distributions of membrane conductances involved in action potential backpropagation along basal dendrites. Journal of neurophysiology. 101 [PubMed]

• Excitability of PFC Basal Dendrites (Acker and Antic 2009) [Model]

Alvarez FP, Destexhe A. (2004). Simulating cortical network activity states constrained by intracellular recordings. Neurocomputing. 58

Blum Moyse L, Berry H. (2022). Modelling the modulation of cortical Up-Down state switching by astrocytes PLoS computational biology. 18 [PubMed]

• Modulation of cortical Up-Down state switching by astrocytes (Moyse & Berry, 2022) [Model]

Cai D, Rangan AV, McLaughlin DW. (2005). Architectural and synaptic mechanisms underlying coherent spontaneous activity in V1. Proceedings of the National Academy of Sciences of the United States of America. 102 [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]

Costa MS, Born J, Claussen JC, Martinetz T. (2016). Modeling the effect of sleep regulation on a neural mass model. Journal of computational neuroscience. 41 [PubMed]

• Neural mass model of the neocortex under sleep regulation (Costa et al 2016) [Model]

Destexhe A. (2009). Self-sustained asynchronous irregular states and Up-Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons. Journal of computational neuroscience. 27 [PubMed]

• Asynchronous irregular and up/down states in excitatory and inhibitory NNs (Destexhe 2009) [Model]

Destexhe A, Rudolph M, Paré D. (2003). The high-conductance state of neocortical neurons in vivo. Nature reviews. Neuroscience. 4 [PubMed]

Durstewitz D, Gabriel T. (2007). Dynamical basis of irregular spiking in NMDA-driven prefrontal cortex neurons. Cerebral cortex (New York, N.Y. : 1991). 17 [PubMed]

• Irregular spiking in NMDA-driven prefrontal cortex neurons (Durstewitz and Gabriel 2006) [Model]

French DA, Gruenstein EI. (2006). An integrate-and-fire model for synchronized bursting in a network of cultured cortical neurons. Journal of computational neuroscience. 21 [PubMed]

Fröhlich F, Bazhenov M, Timofeev I, Steriade M, Sejnowski TJ. (2006). Slow state transitions of sustained neural oscillations by activity-dependent modulation of intrinsic excitability. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]

Geisler C, Brunel N, Wang XJ. (2005). Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges. Journal of neurophysiology. 94 [PubMed]

Hayut I, Fanselow EE, Connors BW, Golomb D. (2011). LTS and FS inhibitory interneurons, short-term synaptic plasticity, and cortical circuit dynamics. PLoS computational biology. 7 [PubMed]

• Rate model of a cortical RS-FS-LTS network (Hayut et al. 2011) [Model]

Hill S, Tononi G. (2005). Modeling sleep and wakefulness in the thalamocortical system. Journal of neurophysiology. 93 [PubMed]

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]

Karameh FN, Dahleh MA, Brown EN, Massaquoi SG. (2006). Modeling the contribution of lamina 5 neuronal and network dynamics to low frequency EEG phenomena. Biological cybernetics. 95 [PubMed]

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

Komarov M et al. (2018). New class of reduced computationally efficient neuronal models for large-scale simulations of brain dynamics. Journal of computational neuroscience. 44 [PubMed]

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

• Thalamocortical sleep model (Fink et. al., 2024, and Krishnan et al., 2016) [Model]

Köndgen H et al. (2008). The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cerebral cortex (New York, N.Y. : 1991). 18 [PubMed]

• Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008) [Model]

Li G, Henriquez CS, Fröhlich F. (2017). Unified Thalamic Model Generates Multiple Distinct Oscillations with State-dependent Entrainment by Stimulation PLOS Computational Biology. 13(10)

• A unified thalamic model of multiple distinct oscillations (Li, Henriquez and Fröhlich 2017) [Model]

Pena RFO, Zaks MA, Roque AC. (2018). Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise : Spontaneous activity in networks with synaptic noise. Journal of computational neuroscience. 45 [PubMed]

• Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016) [Model]

Rakowski F, Karbowski J. (2017). Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost. PLoS computational biology. 13 [PubMed]

• Optimal synaptic assignment for locomotory behavior in C. elegans (Rakowski & Karbowski 2017) [Model]

Rangan AV, Cai D. (2007). Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks. Journal of computational neuroscience. 22 [PubMed]

Rangan AV, Cai D, McLaughlin DW. (2005). Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 102 [PubMed]

Schellenberger Costa M et al. (2016). A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation. PLoS computational biology. 12 [PubMed]

• Neural mass model of spindle generation in the isolated thalamus (Schellenberger Costa et al. 2016) [Model]
• Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016) [Model]

Soplata AE et al. (2023). Rapid thalamocortical network switching mediated by cortical synchronization underlies propofol-induced EEG signatures: a biophysical model. Journal of neurophysiology. 130 [PubMed]

• A biophysical model of thalamocortical network switching under propofol (Soplata et al., 2023) [Model]

Soplata AE et al. (2017). Thalamocortical control of propofol phase-amplitude coupling. PLoS computational biology. 13 [PubMed]

• Thalamocortical control of propofol phase-amplitude coupling (Soplata et al 2017) [Model]

Tabak J, Mascagni M, Bertram R. (2010). Mechanism for the universal pattern of activity in developing neuronal networks. Journal of neurophysiology. 103 [PubMed]

• Universal feature of developing networks (Tabak et al 2010) [Model]
• Universal feature of developing networks (Tabak et al 2010) (CellML) [Model]

Tabak J, O'Donovan MJ, Rinzel J. (2006). Differential control of active and silent phases in relaxation models of neuronal rhythms. Journal of computational neuroscience. 21 [PubMed]

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]

Taxidis J, Coombes S, Mason R, Owen MR. (2012). Modeling sharp wave-ripple complexes through a CA3-CA1 network model with chemical synapses. Hippocampus. 22 [PubMed]

• CRH modulates excitatory transmission and network physiology in hippocampus (Gunn et al. 2017) [Model]

Tomov P, Pena RF, Roque AC, Zaks MA. (2016). Mechanisms of Self-Sustained Oscillatory States in Hierarchical Modular Networks with Mixtures of Electrophysiological Cell Types. Frontiers in computational neuroscience. 10 [PubMed]

• Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016) [Model]

Weigenand A, Schellenberger Costa M, Ngo HV, Claussen JC, Martinetz T. (2014). Characterization of K-complexes and slow wave activity in a neural mass model. PLoS computational biology. 10 [PubMed]

• Neural mass model of the sleeping cortex (Weigenand et al 2014) [Model]
• Neural mass model of spindle generation in the isolated thalamus (Schellenberger Costa et al. 2016) [Model]
• Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016) [Model]
• Neural mass model of the neocortex under sleep regulation (Costa et al 2016) [Model]

Wilson MT et al. (2006). The K-complex and slow oscillation in terms of a mean-field cortical model. Journal of computational neuroscience. 21 [PubMed]

Winograd M, Destexhe A, Sanchez-Vives MV. (2008). Hyperpolarization-activated graded persistent activity in the prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America. 105 [PubMed]

• Hodgkin-Huxley model of persistent activity in prefrontal cortex neurons (Winograd et al. 2008) [Model]
• Hodgkin-Huxley model of persistent activity in PFC neurons (Winograd et al. 2008) (NEURON python) [Model]