https://github.com/predictive-clinical-neuroscience/braincharts
Tip revision: c017a3e0beca4a62982ebf6563a19fa5c0b7284c authored by Andre Marquand on 10 December 2024, 14:42:02 UTC
Added FA models
Added FA models
Tip revision: c017a3e
README.md
# PCNtoolkit braincharts
[](https://gitter.im/predictive-clinical-neuroscience/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) [](https://pcntoolkit.readthedocs.io/en/latest/?badge=latest) [](https://doi.org/10.5281/zenodo.5207839)
## Pre-trained models, code, documentation, and supporting files for:
### 1.) Charting Brain Growth and Aging at High Spatial Precision
In press at [eLife](https://elifesciences.org/articles/72904).
### 2.) Evidence for Embracing Normative Modeling
In press at [eLife](https://elifesciences.org/articles/85082).
**Training the reference cohort (cortical thickness and subcortical volume)** [](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/fit_normative_models_ct.ipynb)
**Fit pre-trained model (cortical thickness and subcortical volume) to new (transfer) data** [](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/apply_normative_models_ct.ipynb)
**Fit pre-trained model (surface area) to new (transfer) data** [](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/apply_normative_models_sa.ipynb)
**Fit pre-trained model (resting-state functional connectivity - Yeo17 brain networks) to new (transfer) data** [](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/apply_normative_models_yeo17.ipynb)

## **Interactive visualizations of evaluation metrics:**
[Heroku app for exploring explained variance - temporarily offline due to Heroku policy changes](https://brainviz-app.herokuapp.com/).
Click on the 'open in colab' button below to launch the interactive visualization and explore the evaluation metrics yourself. There is a separate visualization for each test set and evaluation metric.

### **1. Full test set (including 10 randomized split halfs)**
Explained Variance [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_EVviz.ipynb)
MSLL [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_MSLLviz.ipynb)
Kurtosis [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_Kurtosisviz.ipynb)
Skew [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_Skewviz.ipynb)
### **2. mQC test set**
Explained Variance [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_EVviz.ipynb)
MSLL [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_MSLLviz.ipynb)
Kurtosis [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_Kurtosisviz.ipynb)
Skew [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_Skewviz.ipynb)
### **3. Patients test set**
Explained Variance [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_EVviz.ipynb)
MSLL [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_MSLLviz.ipynb)
Kurtosis [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_Kurtosisviz.ipynb)
Skew [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_Skewviz.ipynb)
### **4. Transfer test set**
Explained Variance [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_EVviz.ipynb)
MSLL [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_MSLLviz.ipynb)
Kurtosis [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_Kurtosisviz.ipynb)
Skew [](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_Skewviz.ipynb)