Muscinelli SP, Gerstner W, Schwalger T. (2019). How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. PLoS computational biology. 15 [PubMed]

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References and models cited by this paper

Bair W, Koch C. (1996). Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey. Neural computation. 8 [PubMed]

Barkai N, Leibler S. (1997). Robustness in simple biochemical networks. Nature. 387 [PubMed]

Beiran M, Ostojic S. (2019). Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks. PLoS computational biology. 15 [PubMed]

Benda J, Herz AV. (2003). A universal model for spike-frequency adaptation. Neural computation. 15 [PubMed]

Berry MJ, Meister M. (1998). Refractoriness and neural precision. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]

Brette R, Guigon E. (2003). Reliability of spike timing is a general property of spiking model neurons. Neural computation. 15 [PubMed]

Brunel N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of computational neuroscience. 8 [PubMed]

Deco G, Jirsa VK, McIntosh AR. (2011). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature reviews. Neuroscience. 12 [PubMed]

Deco G, Rolls ET. (2005). Neurodynamics of biased competition and cooperation for attention: a model with spiking neurons. Journal of neurophysiology. 94 [PubMed]

Deger M, Schwalger T, Naud R, Gerstner W. (2014). Fluctuations and information filtering in coupled populations of spiking neurons with adaptation. Physical review. E, Statistical, nonlinear, and soft matter physics. 90 [PubMed]

Doose J, Doron G, Brecht M, Lindner B. (2016). Noisy Juxtacellular Stimulation In Vivo Leads to Reliable Spiking and Reveals High-Frequency Coding in Single Neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience. 36 [PubMed]

Dummer B, Wieland S, Lindner B. (2014). Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity. Frontiers in computational neuroscience. 8 [PubMed]

Fairhall AL, Lewen GD, Bialek W, de Ruyter Van Steveninck RR. (2001). Efficiency and ambiguity in an adaptive neural code. Nature. 412 [PubMed]

Fourcaud N, Brunel N. (2002). Dynamics of the firing probability of noisy integrate-and-fire neurons. Neural computation. 14 [PubMed]

Gerstner W. (2000). Population dynamics of spiking neurons: fast transients, asynchronous states, and locking. Neural computation. 12 [PubMed]

Jaeger H, Haas H. (2004). Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science (New York, N.Y.). 304 [PubMed]

Jeong H, Mason SP, Barabási AL, Oltvai ZN. (2001). Lethality and centrality in protein networks. Nature. 411 [PubMed]

Knight BW. (1972). Dynamics of encoding in a population of neurons. The Journal of general physiology. 59 [PubMed]

König P, Engel AK, Singer W. (1996). Integrator or coincidence detector? The role of the cortical neuron revisited. Trends in neurosciences. 19 [PubMed]

La Camera G et al. (2006). Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons. Journal of neurophysiology. 96 [PubMed]

Laje R, Buonomano DV. (2013). Robust timing and motor patterns by taming chaos in recurrent neural networks. Nature neuroscience. 16 [PubMed]

Lerchner A et al. (2006). Response variability in balanced cortical networks. Neural computation. 18 [PubMed]

Lundstrom BN, Higgs MH, Spain WJ, Fairhall AL. (2008). Fractional differentiation by neocortical pyramidal neurons. Nature neuroscience. 11 [PubMed]

Maass W, Natschläger T, Markram H. (2002). Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural computation. 14 [PubMed]

Mainen ZF, Sejnowski TJ. (1995). Reliability of spike timing in neocortical neurons. Science (New York, N.Y.). 268 [PubMed]

Mar DJ, Chow CC, Gerstner W, Adams RW, Collins JJ. (1999). Noise shaping in populations of coupled model neurons. Proceedings of the National Academy of Sciences of the United States of America. 96 [PubMed]

Mastrogiuseppe F, Ostojic S. (2018). Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks. Neuron. 99 [PubMed]

Mattia M, Del Giudice P. (2002). Population dynamics of interacting spiking neurons. Physical review. E, Statistical, nonlinear, and soft matter physics. 66 [PubMed]

McCormick DA, Williamson A. (1989). Convergence and divergence of neurotransmitter action in human cerebral cortex. Proceedings of the National Academy of Sciences of the United States of America. 86 [PubMed]

Melamed O, Gerstner W, Maass W, Tsodyks M, Markram H. (2004). Coding and learning of behavioral sequences. Trends in neurosciences. 27 [PubMed]

Naud R, Gerstner W. (2012). Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram. PLoS computational biology. 8 [PubMed]

Nicola W, Clopath C. (2017). Supervised learning in spiking neural networks with FORCE training. Nature communications. 8 [PubMed]

Ostojic S et al. (2015). Neuronal morphology generates high-frequency firing resonance. The Journal of neuroscience : the official journal of the Society for Neuroscience. 35 [PubMed]

Pastor-Satorras R, Vespignani A. (2001). Epidemic spreading in scale-free networks. Physical review letters. 86 [PubMed]

Pozzorini C, Naud R, Mensi S, Gerstner W. (2013). Temporal whitening by power-law adaptation in neocortical neurons. Nature neuroscience. 16 [PubMed]

Rajan K, Abbott LF. (2006). Eigenvalue spectra of random matrices for neural networks. Physical review letters. 97 [PubMed]

Rajan K, Abbott LF, Sompolinsky H. (2010). Stimulus-dependent suppression of chaos in recurrent neural networks. Physical review. E, Statistical, nonlinear, and soft matter physics. 82 [PubMed]

Richardson MJ, Brunel N, Hakim V. (2003). From subthreshold to firing-rate resonance. Journal of neurophysiology. 89 [PubMed]

Schaffer ES, Ostojic S, Abbott LF. (2013). A complex-valued firing-rate model that approximates the dynamics of spiking networks. PLoS computational biology. 9 [PubMed]

Schwalger T, Deger M, Gerstner W. (2017). Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size. PLoS computational biology. 13 [PubMed]

Schwalger T, Schimansky-Geier L. (2008). Interspike interval statistics of a leaky integrate-and-fire neuron driven by Gaussian noise with large correlation times. Physical review. E, Statistical, nonlinear, and soft matter physics. 77 [PubMed]

Setareh H, Deger M, Gerstner W. (2018). Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagation. PLoS computational biology. 14 [PubMed]

Sompolinsky H, Crisanti A, Sommers HJ. (1988). Chaos in random neural networks. Physical review letters. 61 [PubMed]

Stiefel KM, Gutkin BS, Sejnowski TJ. (2009). The effects of cholinergic neuromodulation on neuronal phase-response curves of modeled cortical neurons. Journal of computational neuroscience. 26 [PubMed]

Sussillo D, Abbott LF. (2009). Generating coherent patterns of activity from chaotic neural networks. Neuron. 63 [PubMed]

Wilson HR, Cowan JD. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophysical journal. 12 [PubMed]

van Vreeswijk C, Sompolinsky H. (1996). Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science (New York, N.Y.). 274 [PubMed]

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