ArticleJournal of computational neuroscience2009
Parametric and non-parametric modeling of short-term synaptic plasticity. Part II: Experimental study.
Article in Journal of computational neuroscience, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 32 citations in OpenAlex.
- Short-term depression and long-term plasticity together tune sensitive range of synaptic plasticity.PLoS computational biology · 2020Article
- A Glutamatergic Spine Model to Enable Multi-Scale Modeling of Nonlinear Calcium Dynamics.Frontiers in computational neuroscience · 2018Article
- Hippocampal closed-loop modeling and implications for seizure stimulation design.Journal of neural engineering · 2015Article
- Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling.Journal of neuroscience methods · 2015Article
- Model-based asessment of an in-vivo predictive relationship from CA1 to CA3 in the rodent hippocampus.Journal of computational neuroscience · 2015Article
- System identification of point-process neural systems using probability based Volterra kernels.Journal of neuroscience methods · 2015Article
- Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.Frontiers in computational neuroscience · 2015Article
- Extraction and restoration of hippocampal spatial memories with non-linear dynamical modeling.Frontiers in systems neuroscience · 2014Article
- A comparison between direct and indirect measurements of neurotransmitter vesicle release dynamics: a computational study.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2014Article
- Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions.Journal of computational neuroscience · 2013Article
- A nonlinear model for hippocampal cognitive prosthesis: memory facilitation by hippocampal ensemble stimulation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2012Article
- A hippocampal cognitive prosthesis: multi-input, multi-output nonlinear modeling and VLSI implementation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2012Article
- Nonlinear dynamic modeling of neuron action potential threshold during synaptically driven broadband intracellular activity.IEEE transactions on bio-medical engineering · 2012Article
- Nonlinear dynamic modeling of synaptically driven single hippocampal neuron intracellular activity.IEEE transactions on bio-medical engineering · 2011Article
- The Neurobiological Basis of Cognition: Identification by Multi-Input, Multioutput Nonlinear Dynamic Modeling: A method is proposed for measuring and modeling human long-term memory formation by mathematical analysis and computer simulation of nerve-cell dynamics.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2010Article
- A method for decoding the neurophysiological spike-response transform.Journal of neuroscience methods · 2009Article
- Nonlinear modeling of neural population dynamics for hippocampal prostheses.Neural networks : the official journal of the International Neural Network Society · 2009Article
- Wiener-Volterra characterization of neurons in primary auditory cortex using poisson-distributed impulse train inputs.Journal of neurophysiology · 2009Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
This paper presents a synergistic parametric and non-parametric modeling study of short-term plasticity (STP) in the Schaffer collateral to hippocampal CA1 pyramidal neuron (SC) synapse. Parametric models in the form of sets of differential and algebraic equations have been proposed on the basis of the current understanding of biological mechanisms active within the system. Non-parametric Poisson-Volterra models are obtained herein from broadband experimental input-output data. The non-parametric model is shown to provide better prediction of the experimental output than a parametric model with a single set of facilitation/depression (FD) process. The parametric model is then validated in terms of its input-output transformational properties using the non-parametric model since the latter constitutes a canonical and more complete representation of the synaptic nonlinear dynamics. Furthermore, discrepancies between the experimentally-derived non-parametric model and the equivalent non-parametric model of the parametric model suggest the presence of multiple FD processes in the SC synapses. Inclusion of an additional set of FD process in the parametric model makes it replicate better the characteristics of the experimentally-derived non-parametric model. This improved parametric model in turn provides the requisite biological interpretability that the non-parametric model lacks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.