Citation Relationships

Legends: Link to a Model Reference cited by multiple papers


Friedrich P, Vella M, Gulyás AI, Freund TF, Káli S (2014) A flexible, interactive software tool for fitting the parameters of neuronal models. Front Neuroinform 8:63 [PubMed]

   Software (called Optimizer) for fitting neuronal models (Friedrich et al. 2014)

References and models cited by this paper

References and models that cite this paper

Bahl A, Stemmler MB, Herz AV, Roth A (2012) Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data. J Neurosci Methods 210:22-34 [Journal] [PubMed]
   A set of reduced models of layer 5 pyramidal neurons (Bahl et al. 2012) [Model]
Bower JM, Beeman D (1998) The Book Of Genesis: Exploring Realistic Neural Models With The General Neural Simulation System
Brent RP (2002) Algorithms for Minimization Without Derivatives
Byrd RH, Lu P, Nocedal J, Zhu C (1995) A limited memory algorithm for bound constrained optimization Siam J Sci Comput 16:1190-1208
Cornelis H, Rodriguez AL, Coop AD, Bower JM (2012) Python as a federation tool for GENESIS 3.0. PLoS One 7:e29018 [Journal] [PubMed]
Davison AP, Brüderle D, Eppler J, Kremkow J, Muller E, Pecevski D, Perrinet L, Yger P (2008) PyNN: A Common Interface for Neuronal Network Simulators. Front Neuroinform 2:11 [Journal] [PubMed]
De Schutter E, Bower JM (1994) An active membrane model of the cerebellar Purkinje cell. I. Simulation of current clamps in slice. J Neurophysiol 71:375-400 [Journal] [PubMed]
   Cerebellar purkinje cell (De Schutter and Bower 1994) [Model]
De Schutter E, Bower JM (1994) An active membrane model of the cerebellar Purkinje cell II. Simulation of synaptic responses. J Neurophysiol 71:401-19 [Journal] [PubMed]
   Cerebellar purkinje cell (De Schutter and Bower 1994) [Model]
Druckmann S, Banitt Y, Gidon A, Schürmann F, Markram H, Segev I (2007) A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data. Front Neurosci 1:7-18 [Journal] [PubMed]
Druckmann S, Berger TK, Hill S, Schürmann F, Markram H, Segev I (2008) Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data. Biol Cybern 99:371-9 [Journal] [PubMed]
Eichner H, Borst A (2011) Hands-on parameter search for neural simulations by a MIDI-controller. PLoS One 6:e27013 [Journal] [PubMed]
Eppler JM, Helias M, Muller E, Diesmann M, Gewaltig MO (2008) PyNEST: A Convenient Interface to the NEST Simulator. Front Neuroinform 2:12 [Journal] [PubMed]
Garcia S, Guarino D, Jaillet F, Jennings T, Pröpper R, Rautenberg PL, Rodgers CC, Sobolev A, Wachtler T, Yger P, Davison AP (2014) Neo: an object model for handling electrophysiology data in multiple formats. Front Neuroinform 8:10 [Journal] [PubMed]
Gerstner W, Naud R (2009) Neuroscience. How good are neuron models? Science 326:379-80 [Journal] [PubMed]
Gleeson P, Crook S, Cannon RC, Hines ML, Billings GO, Farinella M, Morse TM, Davison AP, Ray S, Bhalla US, Barnes SR, Dimitrova YD, Silver RA (2010) NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS Comput Biol 6:e1000815 [Journal] [PubMed]
Goodman DF, Brette R (2009) The brian simulator. Front Neurosci 3:192-7 [Journal] [PubMed]
Gurkiewicz M, Korngreen A (2007) A numerical approach to ion channel modelling using whole-cell voltage-clamp recordings and a genetic algorithm. PLoS Comput Biol 3:e169 [Journal] [PubMed]
   Ion channel modeling with whole cell and a genetic algorithm (Gurkiewicz and Korngreen 2007) [Model]
Hendrickson EB, Edgerton JR, Jaeger D (2011) The use of automated parameter searches to improve ion channel kinetics for neural modeling. J Comput Neurosci 31:329-46 [Journal] [PubMed]
Huys QJ, Ahrens MB, Paninski L (2006) Efficient estimation of detailed single-neuron models. J Neurophysiol 96:872-90 [Journal] [PubMed]
   Efficient estimation of detailed single-neuron models (Huys et al. 2006) [Model]
Huys QJ, Paninski L (2009) Smoothing of, and parameter estimation from, noisy biophysical recordings. PLoS Comput Biol 5:e1000379 [Journal] [PubMed]
   Smoothing of, and parameter estimation from, noisy biophysical recordings (Huys & Paninski 2009) [Model]
Káli S, Freund TF (2005) Distinct properties of two major excitatory inputs to hippocampal pyramidal cells: a computational study. Eur J Neurosci 22:2027-48 [Journal] [PubMed]
Keren N, Peled N, Korngreen A (2005) Constraining compartmental models using multiple voltage recordings and genetic algorithms. J Neurophysiol 94:3730-42 [Journal] [PubMed]
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671-80 [Journal] [PubMed]
Naud R, Marcille N, Clopath C, Gerstner W (2008) Firing patterns in the adaptive exponential integrate-and-fire model. Biol Cybern 99:335-47 [Journal] [PubMed]
Nelder JA, Mead J (1965) A simplex algorithm for function minimization Computer J 7:308-313
Poirazi P, Brannon T, Mel BW (2003) Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell. Neuron 37:977-87 [PubMed]
   CA1 pyramidal neuron: as a 2-layer NN and subthreshold synaptic summation (Poirazi et al 2003) [Model]
Rossant C, Goodman DF, Platkiewicz J, Brette R (2010) Automatic fitting of spiking neuron models to electrophysiological recordings. Front Neuroinform 4:2 [Journal] [PubMed]
Svensson CM, Coombes S, Peirce JW (2012) Using evolutionary algorithms for fitting high-dimensional models to neuronal data. Neuroinformatics 10:199-218 [Journal] [PubMed]
Van Geit W, Achard P, De Schutter E (2007) Neurofitter: a parameter tuning package for a wide range of electrophysiological neuron models. Front Neuroinform 1:1 [Journal] [PubMed]
Van Geit W, De Schutter E, Achard P (2008) Automated neuron model optimization techniques: a review. Biol Cybern 99:241-51 [Journal] [PubMed]
Vanier MC, Bower JM (1999) A comparative survey of automated parameter-search methods for compartmental neural models. J Comput Neurosci 7:149-71 [PubMed]
Vavoulis DV, Straub VA, Aston JA, Feng J (2012) A self-organizing state-space-model approach for parameter estimation in hodgkin-huxley-type models of single neurons. PLoS Comput Biol 8:e1002401 [Journal] [PubMed]
J?drzejewski-Szmek Z, Abrahao KP, J?drzejewska-Szmek J, Lovinger DM, Blackwell KT (2018) Parameter Optimization Using Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES), an Approach to Investigate Differences in Channel Properties Between Neuron Subtypes. Front Neuroinform 12:47 [Journal] [PubMed]
   Parameter optimization using CMA-ES (Jedrzejewski-Szmek et al 2018) [Model]
Rumbell TH, Draguljic D, Yadav A, Hof PR, Luebke JI, Weaver CM (2016) Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons. J Comput Neurosci 41:65-90 [Journal] [PubMed]
   Rhesus Monkey Young and Aged L3 PFC Pyramidal Neurons (Rumbell et al. 2016) [Model]
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