Hippocampal CA3 thorny and a-thorny principal neuron models (Linaro et al in review)


This repository contains two populations of biophysically detailed models of murine hippocampal CA3 pyramidal neurons based on the two principal cell types that comprise this region. They are the result of a data-driven approach aimed at optimizing the model parameters by utilizing high-resolution morphological reconstructions and patch-clamp electrophysiology data together with a multi-objective optimization algorithm. The models quantitatively match the cell type-specific firing phenotypes and recapitulate the intrinsic population-level variability observed in the data. Additionally, the conductance values found by the optimization algorithm are consistent with differentially expressed ion channel genes in single-cell transcriptomic data for the two cell types. The models have further been employed to investigate the cell type-specific biophysical properties involved in the generation of complex-spiking output driven by synaptic input and to show that a-thorny bursting cells are capable of encoding more information in their firing output than their counterparts, thorny regular spiking neurons. Reference: Linaro D, Levy MJ, and Hunt, DL. Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons. (2022) PLOS Computational Biology

Model Type: Neuron or other electrically excitable cell

Region(s) or Organism(s): Hippocampus

Cell Type(s): Hippocampus CA3 pyramidal GLU cell

Currents: I Na,t; I Na,p; I K; I K,Ca; I Calcium; I h

Receptors: AMPA; NMDA

Model Concept(s): Excitability; Synaptic Integration; Bursting; Action Potentials; Detailed Neuronal Models; Information transfer; Parameter Fitting

Simulation Environment: NEURON

Implementer(s): Linaro, Daniele [daniele.linaro at unige.it]

References:

Linaro D, Levy MJ, Hunt DL. (). Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons PLoS Computational Biology.


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