This repository provides the source code and data associated with our manuscript "A hierarchy of time constants and reliable signal propagation in the marmoset cerebral cortex". It includes executable Jupyter notebooks and auxiliary Python functions necessary for reproducing all analyses, simulations, and figures presented in the manuscript.
The provided code was developed and tested with the following software versions:
- Python: 3.9.7
- SciPy: 1.7.1
- NumPy: 1.22.4
- pandas: 1.3.4
- statsmodels: 0.12.2
- NetworkX: 2.6.3
- NeuroDSP: 2.1.0
- FOOOF: 1.1.0
- seaborn: 0.13.2
- openpyxl: 3.0.9
- scikit-learn: 0.24.2
- joblib: 1.1.0
- matplotlib: 3.4.3
- The software has been thoroughly tested on Windows 11.
- No specialized or non-standard hardware is required.
No formal installation procedure is necessary. All necessary Python scripts and auxiliary functions are provided in this repository, along with executable Jupyter notebooks. Users are expected to directly run the notebooks provided.
- Not applicable, as installation is not required.
To reproduce the results presented in the manuscript, please execute the following self-contained Jupyter notebooks provided in the repository:
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Marmoset_Exp_Timescale_Model_Introcution.ipynb: Contains code and figures for the analysis of timescales based on marmoset ECoG experimental data. -
Method_Fitting_Hi.ipynb: Illustrates the procedure used to fit the composite gradient employed in the model, utilizing experimental data. -
Marmoset_Model_Timescale_Result.ipynb: Provides code and figures for all simulations and analyses of the timescale hierarchy in the multi-regional model of the marmoset cortex. -
Marmoset_Model_FC.ipynb: Includes code and figures for simulations and analyses related to functional connectivity in the multi-regional model of the marmoset cortex. -
Marmoset_Model_Signal_Prop.ipynb: Contains code and figures for simulations and analyses related to signal propagation within the multi-regional model of the marmoset cortex. -
Marmoset_Model_Delay.ipynb: Contains code and figures for simulations and analyses related to the multi-regional model of the marmoset cortex incorporating explicit axonal conduction delays. -
Marmoset_Exp_Timescale_Awake.ipynb: Contains code and figures for the analysis of timescales based on marmoset ECoG experimental data during the awake resting state.
The experimental data analyzed in these notebooks are sourced from:
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Brain/MINDS Marmoset Brain ECoG Auditory Dataset 01 (Komatsu, M., Ichinohe, N., DataID: 4924). Link to dataset
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Brain/MINDS Marmoset Optogenetics Dataset 01 (Komatsu, M., Sugano, E., Tomita, H., Fujii, N., DataID: 3718). Link to dataset
Both datasets are included under the Data directory. The simulated data generated from the model is located under Data/Marmoset_Model.
- Outputs of simulations, analyses, and figures are entirely contained within each provided Jupyter notebook.
- Most simulations and analyses should complete within a few minutes on a typical desktop computer.
- Longer runtimes may occur for notebooks involving parallel computations (
Marmoset_Model_FC.ipynbandMarmoset_Model_Signal_Prop.ipynb), with runtime dependent on the available number of computational threads.
- To apply this software framework to your own datasets, execute the corresponding self-contained Jupyter notebooks directly. Each notebook clearly documents the required input format and steps necessary for conducting the simulations and analyses.
- Notebooks are self-contained, and users can run them independently in any order.
- All figures and results shown in the manuscript can be fully reproduced using the notebooks provided in this repository.