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在生物物理详细的神经模型中估计参数的方法和考虑与基于模拟的推理推理

Nicholas Tolley1, Pedro L C Rodrigues2, Alexandre Gramfort3

  • 1Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America.

PLoS computational biology
|February 26, 2024
PubMed
概括

基于模拟的推理 (SBI) 现在估计了复杂的神经模型中的参数,克服了对时间序列数据的无概率贝叶斯推理的挑战. 这种方法可以更好地了解健康和疾病中的神经动态.

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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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