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Tuckwell HC (1988) Introduction To Theoretical Neurobiology: Vol 1, Linear Cable Theory And Dendritic Structure

References and models cited by this paper

References and models that cite this paper

Arsiero M, Lüscher HR, Lundstrom BN, Giugliano M (2007) The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex. J Neurosci 27:3274-84 [Journal] [PubMed]

   Input Fluctuations effects on f-I curves (Arsiero et al. 2007) [Model]

Aviel Y, Horn D, Abeles M (2005) Memory capacity of balanced networks. Neural Comput 17:691-713 [Journal] [PubMed]

Berends M, Maex R, De Schutter E (2005) The effect of NMDA receptors on gain modulation. Neural Comput 17:2531-47 [Journal] [PubMed]

Brette R, Gerstner W (2005) Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. J Neurophysiol 94:3637-42 [Journal] [PubMed]

   Adaptive exponential integrate-and-fire model (Brette & Gerstner 2005) [Model]

Brunel N, Hansel D (2006) How noise affects the synchronization properties of recurrent networks of inhibitory neurons. Neural Comput 18:1066-110 [Journal] [PubMed]

Brunel N, Wang XJ (2001) Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. J Comput Neurosci 11:63-85 [PubMed]

Cavallari S, Panzeri S, Mazzoni A (2014) Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks. Front Neural Circuits 8:12 [Journal] [PubMed]

   I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014) [Model]

Christodoulou C, Bugmann G, Clarkson T (2002) A Spiking Neuron Model: Applications and Learning. Neural Networks 15:891-908

Cox SJ (2004) Estimating the location and time course of synaptic input from multi-site potential recordings. J Comput Neurosci 17:225-43 [Journal] [PubMed]

Delord B, Baraduc P, Costalat R, Burnod Y, Guigon E (2000) A model study of cellular short-term memory produced by slowly inactivating potassium conductances. J Comput Neurosci 8:251-73 [PubMed]

Dicke U, Dau T (2005) A functional point-neuron model simulating cochlear nucleus ideal onset responses. J Comput Neurosci 19:239-53 [Journal] [PubMed]

Diesmann M, Gewaltig MO, Aertsen A (1999) Stable propagation of synchronous spiking in cortical neural networks. Nature 402:529-33 [Journal] [PubMed]

   Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999) [Model]

Doiron B, Oswald AM, Maler L (2007) Interval coding. II. Dendrite-dependent mechanisms. J Neurophysiol 97:2744-57 [Journal] [PubMed]

Gabbiani F, Cox SJ (2010) Mathematics for Neuroscientists :1-486 [Journal]

   Mathematics for Neuroscientists (Gabbiani and Cox 2010) [Model]

Goldwyn JH, Shea-Brown E (2011) The what and where of adding channel noise to the Hodgkin-Huxley equations. PLoS Comput Biol 7:e1002247 [Journal] [PubMed]

   Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) (pylab) [Model]
   Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) [Model]

Guerrero-Rivera R, Morrison A, Diesmann M, Pearce TC (2006) Programmable logic construction kits for hyper-real-time neuronal modeling. Neural Comput 18:2651-79 [Journal] [PubMed]

Hansel D, van Vreeswijk C (2002) How noise contributes to contrast invariance of orientation tuning in cat visual cortex. J Neurosci 22:5118-28 [PubMed]

Jolivet R, Gerstner W (2004) Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival. J Physiol Paris 98:442-51 [Journal] [PubMed]

Jolivet R, Kobayashi R, Rauch A, Naud R, Shinomoto S, Gerstner W (2008) A benchmark test for a quantitative assessment of simple neuron models. J Neurosci Methods 169:417-24 [Journal] [PubMed]

   Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) [Model]

Jolivet R, Rauch A, Lüscher HR, Gerstner W (2006) Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J Comput Neurosci 21:35-49 [Journal] [PubMed]

   Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) [Model]

Köndgen H, Geisler C, Fusi S, Wang XJ, Lüscher HR, Giugliano M (2008) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18:2086-97 [Journal] [PubMed]

   Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008) [Model]

Kumar A, Schrader S, Aertsen A, Rotter S (2008) The high-conductance state of cortical networks. Neural Comput 20:1-43 [Journal] [PubMed]

La Camera G, Rauch A, Lüscher HR, Senn W, Fusi S (2004) Minimal models of adapted neuronal response to in vivo-like input currents. Neural Comput 16:2101-24 [Journal] [PubMed]

Lánský P, Greenwood PE (2005) Optimal signal estimation in neuronal models. Neural Comput 17:2240-57 [Journal] [PubMed]

Lánský P, Rodriguez R, Sacerdote L (2004) Mean instantaneous firing frequency is always higher than the firing rate. Neural Comput 16:477-89 [PubMed]

Lansky P, Sanda P, He J (2006) The parameters of the stochastic leaky integrate-and-fire neuronal model. J Comput Neurosci 21:211-23 [Journal] [PubMed]

Lindner B, Longtin A (2006) Comment on "Characterization of subthreshold voltage fluctuations in neuronal membranes," by M. Rudolph and A. Destexhe. Neural Comput 18:1896-931 [Journal] [PubMed]

Loebel A, Tsodyks M (2002) Computation by ensemble synchronization in recurrent networks with synaptic depression. J Comput Neurosci 13:111-24 [PubMed]

Ly C, Tranchina D (2007) Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling. Neural Comput 19:2032-92 [Journal] [PubMed]

Marpeau F, Barua A, Josic K (2009) A finite volume method for stochastic integrate-and-fire models. J Comput Neurosci 26:445-57 [Journal] [PubMed]

   A finite volume method for stochastic integrate-and-fire models (Marpeau et al. 2009) [Model]

Masquelier T (2018) STDP Allows Close-to-Optimal Spatiotemporal Spike Pattern Detection by Single Coincidence Detector Neurons. Neuroscience 389:133-140 [Journal] [PubMed]

   Optimal spatiotemporal spike pattern detection by STDP (Masquelier 2017) [Model]

Meffin H, Burkitt AN, Grayden DB (2004) An analytical model for the "large, fluctuating synaptic conductance state" typical of neocortical neurons in vivo. J Comput Neurosci 16:159-75 [Journal] [PubMed]

Michalikova M, Remme MW, Kempter R (2017) Spikelets in Pyramidal Neurons: Action Potentials Initiated in the Axon Initial Segment That Do Not Activate the Soma. PLoS Comput Biol 13:e1005237 [Journal] [PubMed]

   Spikelet generation and AP initiation in a L5 neocortical pyr neuron (Michalikova et al. 2017) Fig 1 [Model]
   Spikelet generation and AP initiation in a simplified pyr neuron (Michalikova et al. 2017) Fig 3 [Model]

Migliore M, Lansky P (1999) Long-term potentiation and depression induced by a stochastic conditioning of a model synapse. Biophys J 77:1234-43 [Journal] [PubMed]

   Stochastic LTP/LTD conditioning of a synapse (Migliore and Lansky 1999) [Model]

Miller P, Wang XJ (2006) Stability of discrete memory states to stochastic fluctuations in neuronal systems. Chaos 16:026109 [Journal] [PubMed]

Morrison A, Straube S, Plesser HE, Diesmann M (2007) Exact subthreshold integration with continuous spike times in discrete-time neural network simulations. Neural Comput 19:47-79 [Journal] [PubMed]

Munro E, Kopell N (2012) Subthreshold somatic voltage in neocortical pyramidal cells can control whether spikes propagate from the axonal plexus to axon terminals: a model study. J Neurophysiol 107:2833-52 [Journal] [PubMed]

   Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012) [Model]

Olypher AV, Lánský P, Fenton AA (2002) Properties of the extra-positional signal in hippocampal place cell discharge derived from the overdispersion in location-specific firing. Neuroscience 111:553-66 [PubMed]

Pilly PK, Grossberg S (2013) Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells PLOS One 8(4):e60599 [Journal] [PubMed]

   Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013) [Model]

Ramirez-Mahaluf JP, Roxin A, Mayberg HS, Compte A (2017) A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics. Cereb Cortex 27:660-679 [Journal] [PubMed]

   MDD: the role of glutamate dysfunction on Cingulo-Frontal NN dynamics (Ramirez-Mahaluf et al 2017) [Model]

Renart A, Song P, Wang XJ (2003) Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks. Neuron 38:473-85 [PubMed]

Romani S, Amit DJ, Mongillo G (2006) Mean-field analysis of selective persistent activity in presence of short-term synaptic depression. J Comput Neurosci 20:201-17 [Journal] [PubMed]

Rudolph M, Destexhe A (2003) Characterization of subthreshold voltage fluctuations in neuronal membranes. Neural Comput 15:2577-618 [Journal] [PubMed]

Rudolph M, Destexhe A (2004) Inferring network activity from synaptic noise. J Physiol Paris 98:452-66 [Journal] [PubMed]

Song P, Wang XJ (2005) Angular path integration by moving "hill of activity": a spiking neuron model without recurrent excitation of the head-direction system. J Neurosci 25:1002-14 [Journal] [PubMed]

Stemme A, Deco G, Busch A (2007) The neuronal dynamics underlying cognitive flexibility in set shifting tasks. J Comput Neurosci 23:313-31 [Journal] [PubMed]

Stewart RD, Bair W (2009) Spiking neural network simulation: numerical integration with the Parker-Sochacki method. J Comput Neurosci 27:115-33 [Journal] [PubMed]

   Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009) [Model]

Teka W, Marinov TM, Santamaria F (2014) Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model. PLoS Comput Biol 10:e1003526 [Journal] [PubMed]

   Fractional leaky integrate-and-fire model (Teka et al. 2014) [Model]

Tsodyks M, Uziel A, Markram H (2000) Synchrony generation in recurrent networks with frequency-dependent synapses. J Neurosci 20:RC50 [PubMed]

Urakubo H, Aihara T, Kuroda S, Watanabe M, Kondo S (2004) Spatial localization of synapses required for supralinear summation of action potentials and EPSPs. J Comput Neurosci 16:251-65 [Journal] [PubMed]

Van Rossum MC (2001) The transient precision of integrate and fire neurons: effect of background activity and noise. J Comput Neurosci 10:303-11 [Journal] [PubMed]

Wang K, Riera J, Enjieu-Kadji H, Kawashima R (2013) The role of extracellular conductivity profiles in compartmental models for neurons: particulars for layer 5 pyramidal cells. Neural Comput 25:1807-52 [Journal] [PubMed]

   Modeling conductivity profiles in the deep neocortical pyramidal neuron (Wang K et al. 2013) [Model]

Weigenand A, Schellenberger Costa M, Ngo HV, Claussen JC, Martinetz T (2014) Characterization of K-complexes and slow wave activity in a neural mass model. PLoS Comput Biol 10:e1003923 [Journal] [PubMed]

   Neural mass model of spindle generation in the isolated thalamus (Schellenberger Costa et al. 2016) [Model]
   Neural mass model of the sleeping cortex (Weigenand et al 2014) [Model]
   Neural mass model of the neocortex under sleep regulation (Costa et al 2016) [Model]
   Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016) [Model]

Woo B, Shin D, Yang D, Choi J (2005) Reduced model and simulation of neuron with passive dendritic cable: an eigenfunction expansion approach. J Comput Neurosci 19:379-97 [Journal] [PubMed]

Zhang X, Carney LH (2005) Response properties of an integrate-and-fire model that receives subthreshold inputs. Neural Comput 17:2571-601 [Journal] [PubMed]

   Response properties of an integrate and fire model (Zhang and Carney 2005) [Model]

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