Data-driven mouse motor thalamus model reveals topography and spatial weight scaling govern spindle dynamics

We present a data-driven approach for reconstructing a detailed 3D anatomical model of the mouse motor thalamus, as described in our paper "Data-driven mouse motor thalamus model reveals topography and spatial weight scaling govern spindle dynamics".
Existing computational models often lack anatomical detail, limiting investigations into structure-function relationships. Our model integrates diverse data sources – publicly available datasets,anatomical descriptions, geometric constraints, and circuit-level findings – to generate a scaffold model capturing the topographical organization and structural boundaries of the thalamus.  

This project contains the code (written in Python and compiled using the Brain Scaffold Builder package [doc]) used to build the model, the associated anatomical data, the simulation outcomes, and scripts for replicating the manuscript's figures (including their corresponding Illustrator files). The data has been validated against experimental results and provides a valuable platform for testing circuit hypotheses and generating predictions about motor thalamic functions.

README.md provides a detailed overview of the different files and zip folders