How multiple conductances determine electrophysiological properties in a multicompartment model.
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Robust circuit rhythms in small circuits arise from variable circuit components and mechanismsExploiting mathematical models to illuminate electrophysiological variability between individualsComputational models in the age of large datasetsPopulation of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisationPotassium conductance dynamics confer robust spike-time precision in a neuromorphic model of the auditory brain stemDiverse levels of an inwardly rectifying potassium conductance generate heterogeneous neuronal behavior in a population of dorsal cochlear nucleus pyramidal neurons.Homeostasis of functional maps in active dendrites emerges in the absence of individual channelostasis.Correlations in ion channel mRNA in rhythmically active neurons.Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse modelsConductance ratios and cellular identity.Functional consequences of animal-to-animal variation in circuit parameters.Regression analysis for constraining free parameters in electrophysiological models of cardiac cells.Precise temperature compensation of phase in a rhythmic motor pattern.Hormonal modulation of sensorimotor integrationDeterminants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells.Quantifying the relative contributions of divisive and subtractive feedback to rhythm generationThe frequency preference of neurons and synapses in a recurrent oscillatory network.Using multi-compartment ensemble modeling as an investigative tool of spatially distributed biophysical balances: application to hippocampal oriens-lacunosum/moleculare (O-LM) cells.The effects of temperature on the stability of a neuronal oscillator.Non-linear developmental trajectory of electrical phenotype in rat substantia nigra pars compacta dopaminergic neurons.High prevalence of multistability of rest states and bursting in a database of a model neuron.Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment.Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology.Related neuropeptides use different balances of unitary mechanisms to modulate the cardiac neuromuscular system in the American lobster, Homarus americanus.Correlated conductance parameters in leech heart motor neurons contribute to motor pattern formationIntracellular and intercellular processes determine robustness of the circadian clock.Beyond faithful conduction: short-term dynamics, neuromodulation, and long-term regulation of spike propagation in the axon.Identifying crucial parameter correlations maintaining bursting activityVariability, compensation, and modulation in neurons and circuits.Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.Ionic Current Variability and Functional Stability in the Nervous SystemCoregulation of ion channel conductances preserves output in a computational model of a crustacean cardiac motor neuron.The stomatogastric nervous system as a model for studying sensorimotor interactions in real-time closed-loop conditions.Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes.Differential effects of conductances on the phase resetting curve of a bursting neuronal oscillator.Dopamine modulation of Ih improves temporal fidelity of spike propagation in an unmyelinated axonBluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience.Long-lasting changes in neural networks to compensate for altered nicotinic input.Feedback control of variability in the cycle period of a central pattern generatorNeuromodulation of neuronal circuits: back to the future
P2860
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P2860
How multiple conductances determine electrophysiological properties in a multicompartment model.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
2009年论文
@zh
2009年论文
@zh-cn
name
How multiple conductances dete ...... s in a multicompartment model.
@en
type
label
How multiple conductances dete ...... s in a multicompartment model.
@en
prefLabel
How multiple conductances dete ...... s in a multicompartment model.
@en
P2860
P1476
How multiple conductances dete ...... s in a multicompartment model.
@en
P2093
Adam L Taylor
Jean-Marc Goaillard
P2860
P304
P356
10.1523/JNEUROSCI.4438-08.2009
P407
P50
P577
2009-04-01T00:00:00Z