Abeles M, Hayon G, Lehmann D. (2004). Modeling compositionality by dynamic binding of synfire chains. Journal of computational neuroscience. 17 [PubMed]
Ang KK, Quek C. (2005). RSPOP: rough set-based pseudo outer-product fuzzy rule identification algorithm. Neural computation. 17 [PubMed]
Aoki T, Aoyagi T. (2007). Synchrony-induced switching behavior of spike pattern attractors created by spike-timing-dependent plasticity. Neural computation. 19 [PubMed]
Aviel Y, Horn D, Abeles M. (2005). Memory capacity of balanced networks. Neural computation. 17 [PubMed]
Azouz R. (2005). Dynamic spatiotemporal synaptic integration in cortical neurons: neuronal gain, revisited. Journal of neurophysiology. 94 [PubMed]
Bono J, Clopath C. (2017). Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level. Nature communications. 8 [PubMed]
Braitenberg V. (2001). Brain size and number of neurons: an exercise in synthetic neuroanatomy. Journal of computational neuroscience. 10 [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]
Bugmann G, Christodoulou C, Clarkson T. (). A Spiking Neuron Model: Applications and Learning. Neural Networks. 15
Burwick T. (2007). Oscillatory neural networks with self-organized segmentation of overlapping patterns. Neural computation. 19 [PubMed]
Carnevale NT, Tsai KY, Brown TH. (1994). Hebbian learning is jointly controlled by electrotonic and input structure Network. 5
Carvalho TP, Buonomano DV. (2009). Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions. Neuron. 61 [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]
Cortes JM, Torres JJ, Marro J, Garrido PL, Kappen HJ. (2006). Effects of fast presynaptic noise in attractor neural networks. Neural computation. 18 [PubMed]
De Schutter E. (1997). A new functional role for cerebellar long-term depression. Progress in brain research. 114 [PubMed]
De Schutter E, Smolen P. (1998). Calcium dynamics in large neuronal models Methods In Neuronal Modeling: From Ions To Networks.
Deneve S. (2008). Bayesian spiking neurons II: learning. Neural computation. 20 [PubMed]
Durstewitz D, Seamans JK, Sejnowski TJ. (2000). Dopamine-mediated stabilization of delay-period activity in a network model of prefrontal cortex. Journal of neurophysiology. 83 [PubMed]
Edelstein SJ, Schaad O, Henry E, Bertrand D, Changeux JP. (1996). A kinetic mechanism for nicotinic acetylcholine receptors based on multiple allosteric transitions. Biological cybernetics. 75 [PubMed]
Eliasmith C. (2005). A unified approach to building and controlling spiking attractor networks. Neural computation. 17 [PubMed]
Fiori S. (2005). Nonlinear complex-valued extensions of Hebbian learning: an essay. Neural computation. 17 [PubMed]
Frank MJ. (2005). Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism. Journal of cognitive neuroscience. 17 [PubMed]
Frank MJ. (2006). Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making. Neural networks : the official journal of the International Neural Network Society. 19 [PubMed]
Galan RF, Weidert M, Menzel R, Herz AVM , Galizia CG. (2005). Sensory Memory for Odors Is Encoded in Spontaneous Correlated Activity Between Olfactory Glomeruli Neural Comput. 18
García-Sanchez M, Huerta R. (2003). Design parameters of the fan-out phase of sensory systems. Journal of computational neuroscience. 15 [PubMed]
Gerkin RC, Lau PM, Nauen DW, Wang YT, Bi GQ. (2007). Modular competition driven by NMDA receptor subtypes in spike-timing-dependent plasticity. Journal of neurophysiology. 97 [PubMed]
Gerstner W, Kistler WM. (2002). Mathematical formulations of Hebbian learning. Biological cybernetics. 87 [PubMed]
Graham BP, Saudargiene A, Cobb S. (2014). Spine head calcium as a measure of summed postsynaptic activity for driving synaptic plasticity. Neural computation. 26 [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]
Hansel D, Mato G. (2003). Asynchronous states and the emergence of synchrony in large networks of interacting excitatory and inhibitory neurons. Neural computation. 15 [PubMed]
Haykin S, Chen Z. (2005). The cocktail party problem. Neural computation. 17 [PubMed]
Karmarkar UR, Najarian MT, Buonomano DV. (2002). Mechanisms and significance of spike-timing dependent plasticity. Biological cybernetics. 87 [PubMed]
King PD, Zylberberg J, DeWeese MR. (2013). Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. The Journal of neuroscience : the official journal of the Society for Neuroscience. 33 [PubMed]
Komarov M, Bazhenov M. (2016). Linking dynamics of the inhibitory network to the input structure. Journal of computational neuroscience. 41 [PubMed]
Kopell N, Borgers C, Pervouchine D, Tort AB, Malerba P. (2010). Gamma and theta rhythms in biophysical models of hippocampal circuits Hippocampal Microcircuits: A Computational Modeller`s Resource Book. Ch. 15..
Legenstein R, Maass W. (2011). Branch-specific plasticity enables self-organization of nonlinear computation in single neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience. 31 [PubMed]
London M, Schreibman A, Häusser M, Larkum ME, Segev I. (2002). The information efficacy of a synapse. Nature neuroscience. 5 [PubMed]
Manita S, Ross WN. (2010). IP(3) mobilization and diffusion determine the timing window of Ca(2+) release by synaptic stimulation and a spike in rat CA1 pyramidal cells. Hippocampus. 20 [PubMed]
Matsumoto N, Okada M, Sugase-Miyamoto Y, Yamane S. (2005). Neuronal mechanisms encoding global-to-fine information in inferior-temporal cortex. Journal of computational neuroscience. 18 [PubMed]
Mazza M, de Pinho M, Piqueira JR, Roque AC. (2004). A dynamical model of fast cortical reorganization. Journal of computational neuroscience. 16 [PubMed]
Miller P, Wang XJ. (2006). Stability of discrete memory states to stochastic fluctuations in neuronal systems. Chaos (Woodbury, N.Y.). 16 [PubMed]
Mo CH, Gu M, Koch C. (2004). A learning rule for local synaptic interactions between excitation and shunting inhibition. Neural computation. 16 [PubMed]
Molter C, Salihoglu U, Bersini H. (2007). The road to chaos by time-asymmetric Hebbian learning in recurrent neural networks. Neural computation. 19 [PubMed]
Morrison A, Mehring C, Geisel T, Aertsen AD, Diesmann M. (2005). Advancing the boundaries of high-connectivity network simulation with distributed computing. Neural computation. 17 [PubMed]
Neville KR, Lytton WW. (1999). Potentiation of Ca2+ influx through NMDA channels by action potentials: a computer model. Neuroreport. 10 [PubMed]
Noack R, Manjesh C, Ruszinko M, Siegelmann H, Kozma R. (2017). Resting state neural networks and energy metabolism 2017 International Joint Conference on Neural Networks (IJCNN).
Olypher AV, Klement D, Fenton AA. (2006). Cognitive disorganization in hippocampus: a physiological model of the disorganization in psychosis. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]
Porr B, Wörgötter F. (2006). Strongly improved stability and faster convergence of temporal sequence learning by using input correlations only. Neural computation. 18 [PubMed]
Porr B, Wörgötter F. (2007). Learning with "relevance": using a third factor to stabilize Hebbian learning. Neural computation. 19 [PubMed]
Rao RP. (2004). Bayesian computation in recurrent neural circuits. Neural computation. 16 [PubMed]
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]
Renart A, Moreno-Bote R, Wang XJ, Parga N. (2007). Mean-driven and fluctuation-driven persistent activity in recurrent networks. Neural computation. 19 [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]
Rusakov DA, Richter-Levin G, Stewart MG, Bliss TV. (1997). Reduction in spine density associated with long-term potentiation in the dentate gyrus suggests a spine fusion-and-branching model of potentiation. Hippocampus. 7 [PubMed]
Saudargiene A, Porr B, Wörgötter F. (2004). How the shape of pre- and postsynaptic signals can influence STDP: a biophysical model. Neural computation. 16 [PubMed]
Schulz R, Reggia JA. (2004). Temporally asymmetric learning supports sequence processing in multi-winner self-organizing maps. Neural computation. 16 [PubMed]
Sejnowski TJ, Destexhe A. (2000). Why do we sleep? Brain research. 886 [PubMed]
Seung HS, Lee DD, Reis BY, Tank DW. (2000). The autapse: a simple illustration of short-term analog memory storage by tuned synaptic feedback. Journal of computational neuroscience. 9 [PubMed]
Shirke AM, Malinow R. (1997). Mechanisms of potentiation by calcium-calmodulin kinase II of postsynaptic sensitivity in rat hippocampal CA1 neurons. Journal of neurophysiology. 78 [PubMed]
Softky W. (1994). Sub-millisecond coincidence detection in active dendritic trees. Neuroscience. 58 [PubMed]
Softky WR, Koch C. (1993). The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. The Journal of neuroscience : the official journal of the Society for Neuroscience. 13 [PubMed]
Spreizer S, Aertsen A, Kumar A. (2019). From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks. PLoS computational biology. 15 [PubMed]
Sterratt DC, Graham B, Gillies A, Willshaw D. (2011). Principles of Computational Modelling in Neuroscience, Cambridge University Press.
Stuart GJ, Häusser M. (2001). Dendritic coincidence detection of EPSPs and action potentials. Nature neuroscience. 4 [PubMed]
Tamosiunaite M, Porr B, Wörgötter F. (2007). Self-influencing synaptic plasticity: recurrent changes of synaptic weights can lead to specific functional properties. Journal of computational neuroscience. 23 [PubMed]
Tikidji-Hamburyan RA, El-Ghazawi TA, Triplett JW. (2016). Novel Models of Visual Topographic Map Alignment in the Superior Colliculus. PLoS computational biology. 12 [PubMed]
Toyoizumi T, Pfister JP, Aihara K, Gerstner W. (2007). Optimality model of unsupervised spike-timing-dependent plasticity: synaptic memory and weight distribution. Neural computation. 19 [PubMed]
Troyer TW, Doupe AJ. (2000). An associational model of birdsong sensorimotor learning I. Efference copy and the learning of song syllables. Journal of neurophysiology. 84 [PubMed]
Troyer TW, Doupe AJ. (2000). An associational model of birdsong sensorimotor learning II. Temporal hierarchies and the learning of song sequence. Journal of neurophysiology. 84 [PubMed]
Tsigankov DN, Koulakov AA. (2006). A unifying model for activity-dependent and activity-independent mechanisms predicts complete structure of topographic maps in ephrin-A deficient mice. Journal of computational neuroscience. 21 [PubMed]
Urakubo H, Aihara T, Kuroda S, Watanabe M, Kondo S. (2004). Spatial localization of synapses required for supralinear summation of action potentials and EPSPs. Journal of computational neuroscience. 16 [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]
Wennekers T, Ay N. (2005). Finite state automata resulting from temporal information maximization and a temporal learning rule. Neural computation. 17 [PubMed]
Willshaw DJ, Steuber V. (1999). Adaptive leaky integrator models of cerebellar Purkinje cells can learn the clustering of temporal patterns Neurocomputing. 26
Wilson HR, Cowan JD. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophysical journal. 12 [PubMed]
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]
Wörgötter F, Porr B. (2005). Temporal sequence learning, prediction, and control: a review of different models and their relation to biological mechanisms. Neural computation. 17 [PubMed]
Yoshioka M. (2002). Spike-timing-dependent learning rule to encode spatiotemporal patterns in a network of spiking neurons. Physical review. E, Statistical, nonlinear, and soft matter physics. 65 [PubMed]
Yu X, Shouval HZ, Knierim JJ. (2008). A biophysical model of synaptic plasticity and metaplasticity can account for the dynamics of the backward shift of hippocampal place fields. Journal of neurophysiology. 100 [PubMed]
Zachariou M, Alexander SP, Coombes S, Christodoulou C. (2013). A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition. PloS one. 8 [PubMed]