ArticleeLife2023
A stochastic model of hippocampal synaptic plasticity with geometrical readout of enzyme dynamics.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Spike-based alignment learning solves the weight transport problem.Nature communications · 2026Article
- Article
- A generalized mathematical framework for the calcium control hypothesis describes weight-dependent synaptic plasticity.Journal of computational neuroscience · 2025Article
- Synaptic plasticity rules driving representational shifting in the hippocampus.Nature neuroscience · 2025Article
- Overcoming the limitations of motion sensor models by considering dendritic computations.Scientific reports · 2025Article
- The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis.PLoS computational biology · 2025Article
- Asymmetric Voltage Attenuation in Dendrites Can Enable Hierarchical Heterosynaptic Plasticity.eNeuro · 2023Article
- State-of-the-art image and video quality assessment with a metric based on an intrinsically non-linear neural summation model.Frontiers in neuroscience · 2023Article
- Dendritic spine morphology regulates calcium-dependent synaptic weight change.The Journal of general physiology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
Discovering the rules of synaptic plasticity is an important step for understanding brain learning. Existing plasticity models are either (1) top-down and interpretable, but not flexible enough to account for experimental data, or (2) bottom-up and biologically realistic, but too intricate to interpret and hard to fit to data. To avoid the shortcomings of these approaches, we present a new plasticity rule based on a geometrical readout mechanism that flexibly maps synaptic enzyme dynamics to predict plasticity outcomes. We apply this readout to a multi-timescale model of hippocampal synaptic plasticity induction that includes electrical dynamics, calcium, CaMKII and calcineurin, and accurate representation of intrinsic noise sources. Using a single set of model parameters, we demonstrate the robustness of this plasticity rule by reproducing nine published ex vivo experiments covering various spike-timing and frequency-dependent plasticity induction protocols, animal ages, and experimental conditions. Our model also predicts that in vivo-like spike timing irregularity strongly shapes plasticity outcome. This geometrical readout modelling approach can be readily applied to other excitatory or inhibitory synapses to discover their synaptic plasticity rules.
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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 Socratic graph.