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Neural Modeling and Error Recalibration
The chapter explores the process of modeling neurons in a simulation and the importance of recalibrating to correct accumulating errors. It delves into fitting data from individual neurons into a simulation, addressing errors, utilizing biophysical models, and comparing traditional models with deep learning approaches for handling large datasets of neural activities.