ReviewJournal of computational neuroscience1994
Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism.
Review in Journal of computational neuroscience, 1994. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 211 papers.
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Who cites it
211 citing papers in PubMed, 636 citations in OpenAlex.
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- A novel framework for expanding RNNs with biophysical detail to solve cognitive tasks.bioRxiv : the preprint server for biology · 2026Article
- Iso-orientation bias of layer 2/3 connections unifies spontaneous, visually and optogenetically driven V1 dynamics.Nature communications · 2026Article
- Studying Synchronization of Neural Oscillators through NMDA-AMPA Receptor interactions.Chaos, solitons, and fractals · 2026Article
- Approximate matrix exponential: a fast and accurate solver for Markov kinetic models of ion channels.Frontiers in computational neuroscience · 2026Article
- A subject-specific mechanistic model of affect links electroencephalography, cardiorespiratory feedback, and monoaminergic dynamics.Frontiers in computational neuroscience · 2026Article
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- Pre- and Post-synaptic Mechanisms of Neuronal Inhibition Assessed Through Biochemically Detailed Modeling of GABAThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- A simplified model of NMDA-receptor-mediated dynamics in leaky integrate-and-fire neurons.Journal of computational neuroscience · 2025Article
- Local homeostasis preserves global neural dynamics compensating for structural loss during human lifespan aging.Communications biology · 2025Article
- Intrinsic noise reveals the stability of a neuronal network.bioRxiv : the preprint server for biology · 2025Article
- Spatiotemporal calcium signaling patterns underlying opposing effects of histamine and TAS2R agonists in airway smooth muscle.American journal of physiology. Lung cellular and molecular physiology · 2025Article
- Burst firing optimizes invariant coding of natural communication signals by electrosensory neural populations.iScience · 2025Article
- Plasticity in inhibitory networks improves pattern separation in early olfactory processing.Communications biology · 2025Article
- Modelling the effect of allopregnanolone on the resolution of spike-wave discharges.Journal of computational neuroscience · 2025Article
- Is the Papez circuit the location of the elusive episodic memory engram?IBRO neuroscience reports · 2024Article
151 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Markov kinetic models were used to synthesize a complete description of synaptic transmission, including opening of voltage-dependent channels in the presynaptic terminal, release of neurotransmitter, gating of postsynaptic receptors, and activation of second-messenger systems. These kinetic schemes provide a more general framework for modeling ion channels than the Hodgkin-Huxley formalism, supporting a continuous spectrum of descriptions ranging from the very simple and computationally efficient to the highly complex and biophysically precise. Examples are given of simple kinetic schemes based on fits to experimental data that capture the essential properties of voltage-gated, synaptic and neuromodulatory currents. The Markov formalism allows the dynamics of ionic currents to be considered naturally in the larger context of biochemical signal transduction. This framework can facilitate the integration of a wide range of experimental data and promote consistent theoretical analysis of neural mechanisms from molecular interactions to network computations.
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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.