A stochastic model of hippocampal synaptic plasticity with geometrical readout of enzyme dynamics
A stochastic model of hippocampal synaptic plasticity with geometrical readout of enzyme dynamics
复制标题
基于酶动力学几何读数的海马突触可塑性随机模型
DOI：
10.1101/2021.03.30.437703
复制
发表时间：
2022-05
期刊：
影响因子：
7.7
通讯作者：
Yuri Elias Rodrigues;C. Tigaret;H. Marie;Cian O’Donnell;R. Veltz
中科院分区：
文献类型：
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作者：
Yuri Elias Rodrigues;C. Tigaret;H. Marie;Cian O’Donnell;R. Veltz
发现突触可塑性的规律是理解大脑学习的重要一步。现有的可塑性模型要么是1）自上而下和可解释的，但不够灵活，无法解释实验数据，要么是2）自下而上和生物现实，但过于复杂，难以解释，难以拟合数据。为了避免这些方法的缺点，我们提出了一个新的可塑性规则的基础上的几何读出机制，灵活地映射突触酶动力学预测可塑性的结果。我们将此读数应用于海马突触可塑性诱导的多时间尺度模型，该模型包括电动力学，钙，CaMKII和钙调神经磷酸酶，以及固有噪声源的准确表示。使用一组模型参数，我们证明了这种可塑性规则的鲁棒性，通过复制9个已发表的体外实验，涵盖各种尖峰定时和频率依赖性可塑性诱导方案，动物年龄和实验条件。我们的模型还预测，在体内一样的尖峰时间不规则性强烈形状可塑性的结果。这种几何读出建模方法可以很容易地应用到其他兴奋性或抑制性突触，以发现其突触可塑性规则。
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.