Works matching IS 16625188 AND DT 2017 AND VI 11
Results: 33
Potential Mechanisms and Functions of Intermittent Neural Synchronization.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00044
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Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00041
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Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00037
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Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00035
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The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00036
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A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision Making.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00029
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Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00024
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Markovian Analysis of the Sequential Behavior of the Spontaneous Spinal Cord Dorsum Potentials Induced by Acute Nociceptive Stimulation in the Anesthetized Cat.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00032
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Forearm Flexor Muscles in Children with Cerebral Palsy Are Weak, Thin and Stiff.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00030
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A Computational Analysis of the Function of Three Inhibitory Cell Types in Contextual Visual Processing.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00028
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An Evaluation of the Accuracy of Classical Models for Computing the Membrane Potential and Extracellular Potential for Neurons.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00027
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Mechanisms of Winner-Take-All and Group Selection in Neuronal Spiking Networks.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00020
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Feature Detection in Visual Cortex during Different Functional States.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00021
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Analysis and Modeling of Subthreshold Neural Multi-Electrode Array Data by Statistical Field Theory.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00026
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Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00025
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Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00017
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Reward Based Motor Adaptation Mediated by Basal Ganglia.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00019
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Bifurcation Analysis on Phase-Amplitude Cross-Frequency Coupling in Neural Networks with Dynamic Synapses.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00018
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The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00013
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Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00014
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High Entrainment Constrains Synaptic Depression Levels of an In vivo Globular Bushy Cell Model.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00016
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Evaluation of a Neuromechanical Walking Control Model Using Disturbance Experiments.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00015
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Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00012
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A Dynamic Circuit Hypothesis for the Pathogenesis of Blepharospasm.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00011
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Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00010
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Contributions of EEG-fMRI to Assessing the Epileptogenicity of Focal Cortical Dysplasia.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00008
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Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00009
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Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00007
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Phase Difference between Model Cortical Areas Determines Level of Information Transfer.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00006
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Phasic Firing and Coincidence Detection by Subthreshold Negative Feedback: Divisive or Subtractive or, Better, Both.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00003
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Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00004
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Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00002
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A Phase-Locking Analysis of Neuronal Firing Rhythms with Transcranial Magneto-Acoustical Stimulation Based on the Hodgkin-Huxley Neuron Model.
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- Frontiers in Computational Neuroscience, 2017, v. 11, p. 1, doi. 10.3389/fncom.2017.00001
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