Inferring parameters of pyramidal neuron excitability in mouse models of Alzheimer’s disease using biophysical modeling and deep learning

Abstract excerpt

Alzheimer’s disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopathy exhibit altered intrinsic excitability properties. We introduce a novel parameter inference technique, deep hybrid modeling (DeepHM), that combines deep learning w...

Topics

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• Epilepsy
• Forecasting
• Ion Channel Gating
• Ion Channels
• Models, Neurological
• Models, Statistical
• Neural Networks, Computer
• Patch-Clamp Techniques

Identifiers and source

Literature Corpus work

a98a6925-79d4-5c6d-9dd6-2ad8414bc2f7

DOI

10.1101/2023.04.18.537149