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A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations.
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- Frontiers in Neuroinformatics, 2022, v. 16, p. 1, doi. 10.3389/fninf.2022.837549
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Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions.
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- Frontiers in Computational Neuroscience, 2017, p. 1, doi. 10.3389/fncom.2017.00079
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Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses.
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- Frontiers in Computational Neuroscience, 2014, v. 8, p. 1, doi. 10.3389/fncom.2014.00136
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A unified view on weakly correlated recurrent networks.
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- Frontiers in Computational Neuroscience, 2013, p. 1, doi. 10.3389/fncom.2013.00131
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A unified view on weakly correlated recurrent networks.
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- Frontiers in Computational Neuroscience, 2013, v. 7, p. 1, doi. 10.3389/fncom.2013.00131
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Dynamical Response Properties of Neocortical Neuron Ensembles: Multiplicative versus Additive Noise.
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- Journal of Neuroscience, 2009, v. 29, n. 4, p. 1006, doi. 10.1523/JNEUROSCI.3424-08.2009
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Firing-rate models for neurons with a broad repertoire of spiking behaviors.
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- 2013
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Effect of Alzheimer's disease on the dynamical and computational characteristics of recurrent neural networks.
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- 2013
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Dynamics and lifetime of persistent activity states in random networks of spiking neurons with strong synapses.
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- 2013
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Hybrid scheme for modeling LFPs from spiking cortical network models.
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- 2013
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Recurrence and external sources differentially shape network correlations.
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- 2013
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Taming the model zoo: a unified view on correlations in recurrent networks.
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- 2012
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Simplified model of the frequency dependence of the LFP's spatial reach.
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- 2012
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The ball and stick neuron model accounts both for microscopic and macroscopic power laws.
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- 2011
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Rate dynamics of the retina-LGN connection.
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- 2011
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Dynamics of self-sustained activity in random networks with strong synapses.
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- 2011
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Spatial reach of the local field potential is frequency dependent.
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- 2011
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Towards a unified theory of correlations in recurrent neural networks.
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- 2011
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Persistent localized activity in a two-population neural-field model with spatio-temporal external input.
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- 2011
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How local is the local field potential?
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- 2011
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Neurons hear their echo.
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- BMC Neuroscience, 2010, v. 11, p. 1, doi. 10.1186/1471-2202-11-S1-P47
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Decorrelation of low-frequency neural activity by inhibitory feedback.
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- BMC Neuroscience, 2010, v. 11, p. 1, doi. 10.1186/1471-2202-11-S1-O11
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Synchronization and rate dynamics in embedded synfire chains: effect of network heterogeneity and feedback.
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- BMC Neuroscience, 2009, v. 10, p. 1, doi. 10.1186/1471-2202-10-S1-P258
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Estimating the spatial range of local field potentials in a cortical population model.
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- BMC Neuroscience, 2009, v. 10, p. 1, doi. 10.1186/1471-2202-10-S1-P224
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Sequence learning, prediction, and replay in networks of spiking neurons.
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- PLoS Computational Biology, 2022, v. 18, n. 6, p. 1, doi. 10.1371/journal.pcbi.1010233
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Deterministic networks for probabilistic computing.
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- Scientific Reports, 2019, v. 9, n. 1, p. N.PAG, doi. 10.1038/s41598-019-54137-7
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The variability of tidewater-glacier calving: origin of event-size and interval distributions.
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- Journal of Glaciology, 2014, v. 60, n. 222, p. 622, doi. 10.3189/2014JoG13J215
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Power Laws from Linear Neuronal Cable Theory: Power Spectral Densities of the Soma Potential, Soma Membrane Current and Single-Neuron Contribution to the EEG.
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- PLoS Computational Biology, 2014, v. 10, n. 11, p. 1, doi. 10.1371/journal.pcbi.1003928
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The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics.
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- PLoS Computational Biology, 2014, v. 10, n. 1, p. 1, doi. 10.1371/journal.pcbi.1003428
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Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential.
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- PLoS Computational Biology, 2013, v. 9, n. 7, p. 1, doi. 10.1371/journal.pcbi.1003137
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- Article
Decorrelation of Neural-Network Activity by Inhibitory Feedback.
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- PLoS Computational Biology, 2012, v. 8, n. 8, p. 1, doi. 10.1371/journal.pcbi.1002596
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- Article
Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer's disease.
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- PLoS Computational Biology, 2020, v. 16, n. 8, p. 1, doi. 10.1371/journal.pcbi.1007790
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Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.
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- Cerebral Cortex, 2016, v. 26, n. 12, p. 4461, doi. 10.1093/cercor/bhw237
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Coherent noise enables probabilistic sequence replay in spiking neuronal networks.
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- PLoS Computational Biology, 2023, v. 19, n. 5, p. 1, doi. 10.1371/journal.pcbi.1010989
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Firing-rate models for neurons with a broad repertoire of spiking behaviors.
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- Journal of Computational Neuroscience, 2018, v. 45, n. 2, p. 103, doi. 10.1007/s10827-018-0693-9
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Firing-rate models capture essential response dynamics of LGN relay cells.
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- Journal of Computational Neuroscience, 2013, v. 35, n. 3, p. 359, doi. 10.1007/s10827-013-0456-6
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Dynamical Characteristics of Recurrent Neuronal Networks Are Robust Against Low Synaptic Weight Resolution.
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- Frontiers in Neuroscience, 2021, v. 15, p. 1, doi. 10.3389/fnins.2021.757790
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