ArticlePatterns (New York, N.Y.)2023
A universal workflow for creation, validation, and generalization of detailed neuronal models.
Article in Patterns (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- An in silico framework for dissecting the mechanistic origins of in vivo recorded neuronal activity.PLoS computational biology · 2026Article
- eFEL: electrophysiology feature extraction library.Bioinformatics (Oxford, England) · 2026Article
- Modeling and simulation of neocortical micro- and mesocircuitry (Part II, Physiology and experimentation).eLife · 2026Article
- Morphological details contribute to neuronal response variability within the same cell type.Frontiers in cellular neuroscience · 2026Article
- How to train your neuron: developing a detailed, up-to-date, multipurpose model of hippocampal CA1 pyramidal cells.Frontiers in computational neuroscience · 2026Article
- Article
- Higher-order interactions in neuronal function: From genes to ionic currents in biophysical models.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Biophysical modeling of thalamic reticular nucleus subpopulations and their differential contribution to spindle dynamics.iScience · 2025Article
- Article
- Article
- A multiscale electro-metabolic model of a rat neocortical circuit reveals the impact of ageing on central cortical layers.PLoS computational biology · 2025Article
- What makes human cortical pyramidal neurons functionally complex.bioRxiv : the preprint server for biology · 2024Article
- Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- Controlling morpho-electrophysiological variability of neurons with detailed biophysical models.iScience · 2023Article
- A universal workflow for creation, validation, and generalization of detailed neuronal models.Patterns (New York, N.Y.) · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Detailed single-neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools focus on a limited set of specific features characteristic of a single neuron. Here, we present a generalized automated workflow for the creation of robust electrical models and illustrate its performance by building cell models for the rat somatosensory cortex. Each model is based on a 3D morphological reconstruction and a set of ionic mechanisms. We use an evolutionary algorithm to optimize neuronal parameters to match the electrophysiological features extracted from experimental data. Then we validate the optimized models against additional stimuli and assess their generalizability on a population of similar morphologies. Compared to the state-of-the-art canonical models, our models show 5-fold improved generalizability. This versatile approach can be used to build robust models of any neuronal type.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.