ArticleBiological cybernetics2016
Nonlinear statistical data assimilation for HVC[Formula: see text] neurons in the avian song system.
Article in Biological cybernetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Single shot detection of alterations across multiple ionic currents from assimilation of cell membrane dynamics.Scientific reports · 2024Article
- Model of the HVC neural network as a song motor in zebra finch.Frontiers in computational neuroscience · 2024Article
- Optimal control methods for nonlinear parameter estimation in biophysical neuron models.PLoS computational biology · 2022Article
- A data-assimilation approach to predict population dynamics during epithelial-mesenchymal transition.Biophysical journal · 2022Article
- Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation.Infectious Disease Modelling · 2021Article
- WalkingeLife · 2020Article
- Cell Fate Forecasting: A Data-Assimilation Approach to Predict Epithelial-Mesenchymal Transition.Biophysical journal · 2020Article
- Exploring the molecular basis of neuronal excitability in a vocal learner.BMC genomics · 2019Article
- Special Issue from the 2017 International Conference on Mathematical Neuroscience.Journal of mathematical neuroscience · 2019Article
- Data Assimilation Methods for Neuronal State and Parameter Estimation.Journal of mathematical neuroscience · 2018Review
- Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus.PLoS computational biology · 2017Article
- Model of the songbird nucleus HVC as a network of central pattern generators.Journal of neurophysiology · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
With the goal of building a model of the HVC nucleus in the avian song system, we discuss in detail a model of HVC[Formula: see text] projection neurons comprised of a somatic compartment with fast Na[Formula: see text] and K[Formula: see text] currents and a dendritic compartment with slower Ca[Formula: see text] dynamics. We show this model qualitatively exhibits many observed electrophysiological behaviors. We then show in numerical procedures how one can design and analyze feasible laboratory experiments that allow the estimation of all of the many parameters and unmeasured dynamical variables, given observations of the somatic voltage [Formula: see text] alone. A key to this procedure is to initially estimate the slow dynamics associated with Ca, blocking the fast Na and K variations, and then with the Ca parameters fixed estimate the fast Na and K dynamics. This separation of time scales provides a numerically robust method for completing the full neuron model, and the efficacy of the method is tested by prediction when observations are complete. The simulation provides a framework for the slice preparation experiments and illustrates the use of data assimilation methods for the design of those experiments.
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