Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons
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Timothy H. Rumbell | Christina M. Weaver | P. Hof | J. Luebke | Danel Draguljic | C. M. Weaver | A. Yadav
[1] Jennifer I Luebke,et al. Area‐Specific Features of Pyramidal Neurons—a Comparative Study in Mouse and Rhesus Monkey , 2016, Cerebral cortex.
[2] J. Payandeh,et al. The hitchhiker’s guide to the voltage-gated sodium channel galaxy , 2016, The Journal of general physiology.
[3] Eve Marder,et al. Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment. , 2014, Journal of neurophysiology.
[4] Frances K. Skinner,et al. Using Multi-Compartment Ensemble Modeling As an Investigative Tool of Spatially Distributed Biophysical Balances: Application to Hippocampal Oriens-Lacunosum/Moleculare (O-LM) Cells , 2014, PloS one.
[5] Hao Huang,et al. Estimating parameters and predicting membrane voltages with conductance-based neuron models , 2014, Biological Cybernetics.
[6] Szabolcs Káli,et al. A flexible, interactive software tool for fitting the parameters of neuronal models , 2014, Front. Neuroinform..
[7] A. Korngreen,et al. A Quantitative Description of Dendritic Conductances and Its Application to Dendritic Excitation in Layer 5 Pyramidal Neurons , 2014, The Journal of Neuroscience.
[8] Viola Priesemann,et al. Local active information storage as a tool to understand distributed neural information processing , 2013, Front. Neuroinform..
[9] Timothy H. Rumbell,et al. Functional consequences of age-related morphologic changes in pyramidal neurons of the rhesus monkey prefrontal cortex , 2013, BMC Neuroscience.
[10] A. Prinz,et al. Multi-objective evolutionary algorithms for analysis of conductance correlations involved in recovery of bursting after neuromodulator deprivation in lobster stomatogastric neuron models , 2013, BMC Neuroscience.
[11] Henry Markram,et al. Preserving axosomatic spiking features despite diverse dendritic morphology. , 2013, Journal of neurophysiology.
[12] Patrick R Hof,et al. Influence of Highly Distinctive Structural Properties on the Excitability of Pyramidal Neurons in Monkey Visual and Prefrontal Cortices , 2012, The Journal of Neuroscience.
[13] Arnd Roth,et al. Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data , 2012, Journal of Neuroscience Methods.
[14] Y. Jan,et al. Voltage‐gated potassium channels and the diversity of electrical signalling , 2012, The Journal of physiology.
[15] Michele Pace,et al. Global parameter estimation of an Hodgkin-Huxley formalism using membrane voltage recordings: Application to neuro-mimetic analog integrated circuits , 2012, Neurocomputing.
[16] W. Gerstner,et al. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. , 2012, Journal of neurophysiology.
[17] H. Abarbanel,et al. Dynamical estimation of neuron and network properties II: path integral Monte Carlo methods , 2012, Biological Cybernetics.
[18] Jean-Marc Goaillard,et al. Ca2+/cAMP-Sensitive Covariation of IA and IH Voltage Dependences Tunes Rebound Firing in Dopaminergic Neurons , 2012, The Journal of Neuroscience.
[19] Mark Kostuk,et al. Dynamical estimation of neuron and network properties I: variational methods , 2011, Biological Cybernetics.
[20] Thomas K. Berger,et al. Effective Stimuli for Constructing Reliable Neuron Models , 2011, PLoS Comput. Biol..
[21] Henry Markram,et al. Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties , 2011, PLoS Comput. Biol..
[22] Dieter Jaeger,et al. The use of automated parameter searches to improve ion channel kinetics for neural modeling , 2011, Journal of Computational Neuroscience.
[23] P. Hof,et al. Age-related morphologic changes alter robustness of neuronal function , 2010, BMC Neuroscience.
[24] Dieter Jaeger,et al. The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites , 2010, Journal of Computational Neuroscience.
[25] Jerome Sacks,et al. Choosing the Sample Size of a Computer Experiment: A Practical Guide , 2009, Technometrics.
[26] Alfredo Rodriguez,et al. Three-dimensional neuron tracing by voxel scooping , 2009, Journal of Neuroscience Methods.
[27] Patrick J Coskren,et al. The electrotonic structure of pyramidal neurons contributing to prefrontal cortical circuits in macaque monkeys is significantly altered in aging. , 2009, Cerebral cortex.
[28] Astrid A. Prinz,et al. Computational intelligence in modeling of biological neurons: A case study of an invertebrate pacemaker neuron , 2009, 2009 International Joint Conference on Neural Networks.
[29] Liam Paninski,et al. Smoothing of, and Parameter Estimation from, Noisy Biophysical Recordings , 2009, PLoS Comput. Biol..
[30] Henry Markram,et al. Minimal Hodgkin–Huxley type models for different classes of cortical and thalamic neurons , 2008, Biological Cybernetics.
[31] Erik De Schutter,et al. Automated neuron model optimization techniques: a review , 2008, Biological Cybernetics.
[32] Thomas K. Berger,et al. Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data , 2008, Biological Cybernetics.
[33] Erik De Schutter,et al. Frontiers in Computational Neuroscience Calcium, Synaptic Plasticity and Intrinsic Homeostasis in Purkinje Neuron Models Materials and Methods Original Pc Model , 2022 .
[34] Cengiz Günay,et al. Channel Density Distributions Explain Spiking Variability in the Globus Pallidus: A Combined Physiology and Computer Simulation Database Approach , 2008, The Journal of Neuroscience.
[35] J. Luebke,et al. Why are pyramidal cell firing rates increased with aging, and what can we do about it? , 2008, BMC Neuroscience.
[36] Douglas B. Ehlenberger,et al. Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images , 2008, PloS one.
[37] Susan L. Wearne,et al. Neuronal Firing Sensitivity to Morphologic and Active Membrane Parameters , 2007, PLoS Comput. Biol..
[38] Werner Van Geit,et al. Neurofitter: A Parameter Tuning Package for a Wide Range of Electrophysiological Neuron Models , 2007, Frontiers Neuroinformatics.
[39] Henry Markram,et al. A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Neuron Models by Experimental Data , 2007, Front. Neurosci..
[40] Erik De Schutter,et al. Neurofitter: a parameter tuning package for a wide range of electrophysiological neuron models , 2007, BMC Neuroscience.
[41] Joshua D. Knowles,et al. Multiobjective Optimization in Bioinformatics and Computational Biology , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[42] Liam Paninski,et al. Efficient estimation of detailed single-neuron models. , 2006, Journal of neurophysiology.
[43] E. Marder,et al. Variability, compensation and homeostasis in neuron and network function , 2006, Nature Reviews Neuroscience.
[44] Erik De Schutter,et al. Complex Parameter Landscape for a Complex Neuron Model , 2006, PLoS Comput. Biol..
[45] Ronald L Calabrese,et al. Creation and reduction of a morphologically detailed model of a leech heart interneuron. , 2006, Journal of neurophysiology.
[46] Susan L. Wearne,et al. The role of action potential shape and parameter constraints in optimization of compartment models , 2006, Neurocomputing.
[47] E. Marder,et al. Variable channel expression in identified single and electrically coupled neurons in different animals , 2006, Nature Neuroscience.
[48] Michael L. Hines,et al. The NEURON Book , 2006 .
[49] R. Storn,et al. Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .
[50] Noam Peled,et al. Constraining compartmental models using multiple voltage recordings and genetic algorithms. , 2005, Journal of neurophysiology.
[51] B. Bean,et al. Robustness of Burst Firing in Dissociated Purkinje Neurons with Acute or Long-Term Reductions in Sodium Conductance , 2005, The Journal of Neuroscience.
[52] Yu-Ming Chang,et al. Increased action potential firing rates of layer 2/3 pyramidal cells in the prefrontal cortex are significantly related to cognitive performance in aged monkeys. , 2005, Cerebral cortex.
[53] Eve Marder,et al. Alternative to hand-tuning conductance-based models: construction and analysis of databases of model neurons. , 2003, Journal of neurophysiology.
[54] R. Traub,et al. Fast rhythmic bursting can be induced in layer 2/3 cortical neurons by enhancing persistent Na+ conductance or by blocking BK channels. , 2003, Journal of neurophysiology.
[55] I. Jolliffe. Principal Component Analysis , 2005 .
[56] E. Marder,et al. Global Structure, Robustness, and Modulation of Neuronal Models , 2001, The Journal of Neuroscience.
[57] Alain Destexhe,et al. Simplified models of neocortical pyramidal cells preserving somatodendritic voltage attenuation , 2001, Neurocomputing.
[58] R. Maex,et al. Introduction to Equation Solving and Parameter Fitting , 2000 .
[59] Erik De Schutter,et al. Introduction to Equation Solving and Parameter Fitting , 2000 .
[60] R. E. Burke,et al. Comparison of Alternative Designs for Reducing Complex Neurons to Equivalent Cables , 2000, Journal of Computational Neuroscience.
[61] James M. Bower,et al. A Comparative Survey of Automated Parameter-Search Methods for Compartmental Neural Models , 1999, Journal of Computational Neuroscience.
[62] P. Jonas,et al. Functional differences in Na+ channel gating between fast‐spiking interneurones and principal neurones of rat hippocampus , 1997, The Journal of physiology.
[63] T. J. Mitchell,et al. Exploratory designs for computational experiments , 1995 .
[64] R. Traub,et al. A branching dendritic model of a rodent CA3 pyramidal neurone. , 1994, The Journal of physiology.
[65] T. Sejnowski,et al. Reduced compartmental models of neocortical pyramidal cells , 1993, Journal of Neuroscience Methods.
[66] M. E. Johnson,et al. Minimax and maximin distance designs , 1990 .
[67] D. Wolfe,et al. Nonparametric Statistical Methods. , 1974 .
[68] Eve Marder,et al. Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model , 2014, Neuron.
[69] Nicholas T. Carnevale,et al. Introducing The Neuroscience Gateway , 2013, IWSG.
[70] Carlos A. Coello Coello,et al. Multi-objective Optimization Using Differential Evolution: A Survey of the State-of-the-Art , 2008 .
[71] Kenneth V. Price,et al. Eliminating Drift Bias from the Differential Evolution Algorithm , 2008 .
[72] K. Zielinski,et al. Stopping Criteria for Differential Evolution in Constrained Single-Objective Optimization , 2008 .
[73] R. Storn,et al. Differential Evolution , 2004 .
[74] A. E. Eiben,et al. Introduction to Evolutionary Computing , 2003, Natural Computing Series.