Arsiero M, Lüscher HR, Lundstrom BN, Giugliano M. (2007). The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 27 [PubMed]
Aviel Y, Horn D, Abeles M. (2005). Memory capacity of balanced networks. Neural computation. 17 [PubMed]
Banerjee A. (2006). On the sensitive dependence on initial conditions of the dynamics of networks of spiking neurons. Journal of computational neuroscience. 20 [PubMed]
Brunel N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of computational neuroscience. 8 [PubMed]
Brunel N, Hakim V. (1999). Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural computation. 11 [PubMed]
Brunel N, Hansel D. (2006). How noise affects the synchronization properties of recurrent networks of inhibitory neurons. Neural computation. 18 [PubMed]
Brunel N, Wang XJ. (2001). Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. Journal of computational neuroscience. 11 [PubMed]
Burkitt AN, Meffin H, Grayden DB. (2004). Spike-timing-dependent plasticity: the relationship to rate-based learning for models with weight dynamics determined by a stable fixed point. Neural computation. 16 [PubMed]
Chover J, Haberly LB, Lytton WW. (2001). Alternating dominance of NMDA and AMPA for learning and recall: a computer model. Neuroreport. 12 [PubMed]
Curti E, Mongillo G, La Camera G, Amit DJ. (2004). Mean field and capacity in realistic networks of spiking neurons storing sparsely coded random memories. Neural computation. 16 [PubMed]
Durstewitz D. (2006). A few important points about dopamine's role in neural network dynamics. Pharmacopsychiatry. 39 Suppl 1 [PubMed]
Edin F, Macoveanu J, Olesen P, Tegnér J, Klingberg T. (2007). Stronger synaptic connectivity as a mechanism behind development of working memory-related brain activity during childhood. Journal of cognitive neuroscience. 19 [PubMed]
Feinerman O, Segal M, Moses E. (2007). Identification and dynamics of spontaneous burst initiation zones in unidimensional neuronal cultures. Journal of neurophysiology. 97 [PubMed]
Fransén E, Lansner A. (1998). A model of cortical associative memory based on a horizontal network of connected columns. Network (Bristol, England). 9 [PubMed]
Golomb D, Shedmi A, Curtu R, Ermentrout GB. (2006). Persistent synchronized bursting activity in cortical tissues with low magnesium concentration: a modeling study. Journal of neurophysiology. 95 [PubMed]
Gutkin BS, Laing CR, Colby CL, Chow CC, Ermentrout GB. (2001). Turning on and off with excitation: the role of spike-timing asynchrony and synchrony in sustained neural activity. Journal of computational neuroscience. 11 [PubMed]
Haeusler S, Maass W. (2007). A statistical analysis of information-processing properties of lamina-specific cortical microcircuit models. Cerebral cortex (New York, N.Y. : 1991). 17 [PubMed]
Izhikevich EM. (2006). Polychronization: computation with spikes. Neural computation. 18 [PubMed]
Jercog D et al. (2017). UP-DOWN cortical dynamics reflect state transitions in a bistable network. eLife. 6 [PubMed]
Joelving FC, Compte A, Constantinidis C. (2007). Temporal properties of posterior parietal neuron discharges during working memory and passive viewing. Journal of neurophysiology. 97 [PubMed]
Kumar A, Schrader S, Aertsen A, Rotter S. (2008). The high-conductance state of cortical networks. Neural computation. 20 [PubMed]
La Camera G, Rauch A, Lüscher HR, Senn W, Fusi S. (2004). Minimal models of adapted neuronal response to in vivo-like input currents. Neural computation. 16 [PubMed]
Latham PE, Nirenberg S. (2004). Computing and stability in cortical networks. Neural computation. 16 [PubMed]
Lerchner A et al. (2006). Response variability in balanced cortical networks. Neural computation. 18 [PubMed]
Litwin-Kumar A, Doiron B. (2012). Slow dynamics and high variability in balanced cortical networks with clustered connections. Nature neuroscience. 15 [PubMed]
Lundqvist M, Rehn M, Djurfeldt M, Lansner A. (2006). Attractor dynamics in a modular network model of neocortex. Network (Bristol, England). 17 [PubMed]
Ly C, Tranchina D. (2007). Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling. Neural computation. 19 [PubMed]
Maass W, Joshi P, Sontag ED. (2007). Computational aspects of feedback in neural circuits. PLoS computational biology. 3 [PubMed]
Macoveanu J, Klingberg T, Tegnér J. (2006). A biophysical model of multiple-item working memory: a computational and neuroimaging study. Neuroscience. 141 [PubMed]
Meffin H, Burkitt AN, Grayden DB. (2004). An analytical model for the "large, fluctuating synaptic conductance state" typical of neocortical neurons in vivo. Journal of computational neuroscience. 16 [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]
Mejías JF, Wang XJ. (2022). Mechanisms of distributed working memory in a large-scale network of macaque neocortex eLife. 11 [PubMed]
Miller P, Wang XJ. (2006). Stability of discrete memory states to stochastic fluctuations in neuronal systems. Chaos (Woodbury, N.Y.). 16 [PubMed]
Miyawaki Y, Okada M. (2004). A network model of perceptual suppression induced by transcranial magnetic stimulation. Neural computation. 16 [PubMed]
Mongillo G, Amit DJ. (2001). Oscillations and irregular emission in networks of linear spiking neurons. Journal of computational neuroscience. 11 [PubMed]
Morita K, Okada M, Aihara K. (2007). Selectivity and stability via dendritic nonlinearity. Neural computation. 19 [PubMed]
Muresan RC, Savin C. (2007). Resonance or integration? Self-sustained dynamics and excitability of neural microcircuits. Journal of neurophysiology. 97 [PubMed]
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]
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]
Renart A, Moreno-Bote R, Wang XJ, Parga N. (2007). Mean-driven and fluctuation-driven persistent activity in recurrent networks. Neural computation. 19 [PubMed]
Romani S, Amit DJ, Mongillo G. (2006). Mean-field analysis of selective persistent activity in presence of short-term synaptic depression. Journal of computational neuroscience. 20 [PubMed]
Ros E, Carrillo R, Ortigosa EM, Barbour B, Agís R. (2006). Event-driven simulation scheme for spiking neural networks using lookup tables to characterize neuronal dynamics. Neural computation. 18 [PubMed]
Rubin J, Terman D, Chow C. (2001). Localized bumps of activity sustained by inhibition in a two-layer thalamic network. Journal of computational neuroscience. 10 [PubMed]
Senn W, Fusi S. (2005). Learning only when necessary: better memories of correlated patterns in networks with bounded synapses. Neural computation. 17 [PubMed]
Shanahan M. (2008). A spiking neuron model of cortical broadcast and competition. Consciousness and cognition. 17 [PubMed]
Soula H, Beslon G, Mazet O. (2005). Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks Neural Comput. 18
Soula H, Chow CC. (2007). Stochastic dynamics of a finite-size spiking neural network. Neural computation. 19 [PubMed]
Sterratt DC, Graham B, Gillies A, Willshaw D. (2011). Principles of Computational Modelling in Neuroscience, Cambridge University Press.
Sussillo D, Abbott LF. (2009). Generating coherent patterns of activity from chaotic neural networks. Neuron. 63 [PubMed]
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]
Tomov P, Pena RF, Zaks MA, Roque AC. (2014). Sustained oscillations, irregular firing, and chaotic dynamics in hierarchical modular networks with mixtures of electrophysiological cell types. Frontiers in computational neuroscience. 8 [PubMed]
Vasilaki E, Giugliano M. (2014). Emergence of connectivity motifs in networks of model neurons with short- and long-term plastic synapses. PloS one. 9 [PubMed]
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]
Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W. (2011). Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science (New York, N.Y.). 334 [PubMed]
Wimmer K et al. (2015). Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT. Nature communications. 6 [PubMed]
Wong KF, Wang XJ. (2006). A recurrent network mechanism of time integration in perceptual decisions. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]
Zerlaut Y, Chemla S, Chavane F, Destexhe A. (2018). Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons. Journal of computational neuroscience. 44 [PubMed]
Zylbertal A, Kahan A, Ben-Shaul Y, Yarom Y, Wagner S. (2015). Prolonged Intracellular Na+ Dynamics Govern Electrical Activity in Accessory Olfactory Bulb Mitral Cells. PLoS biology. 13 [PubMed]