Combined statistical-biophysical modeling links ion channel genes to physiology of cortical neuron types.

ABSTRACT: Neural cell types have classically been characterized by their anatomy and electrophysiology. More recently, single-cell transcriptomics has enabled an increasingly fine genetically defined taxonomy of cortical cell types, but the link between the gene expression of individual cell types and their physiological and anatomical properties remains poorly understood. Here, we develop a hybrid modeling approach to bridge this gap. Our approach combines statistical and mechanistic models to predict cells' electrophysiological activity from their gene expression pattern. To this end, we fit biophysical Hodgkin-Huxley-based models for a wide variety of cortical cell types using simulation-based inference, while overcoming the challenge posed by the mismatch between the mathematical model and the d

SUBMITTER: Bernaerts Y 

PROVIDER: S-EPMC11722265 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature