# braincharts

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## Pre-trained models, code, documentation, and supporting files for: 
### Charting Brain Growth and Aging at High Spatial Precision
In press at [eLife](elifesciences.org/articles/72904).

**Training the reference cohort** [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/fit_normative_models.ipynb)

**Fit pre-trained model to new (transfer) data** [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/predictive-clinical-neuroscience/braincharts/blob/master/scripts/apply_normative_models.ipynb)

**Abstract:** Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1,985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences.  These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision making. 

![](docs/elife_press_release_photo.jpg)

## **Interactive visualizations of evaluation metrics:**

[Heroku app for exploring explained variance](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. 

![](docs/eLife_interactive_viz.gif)

### **1. Full test set (including 10 randomized split halfs)**

Explained Variance [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_EVviz.ipynb)

MSLL [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_MSLLviz.ipynb)

Kurtosis [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_Kurtosisviz.ipynb)

Skew [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/10foldCV_Skewviz.ipynb)

### **2. mQC test set**

Explained Variance [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_EVviz.ipynb)

MSLL [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_MSLLviz.ipynb)

Kurtosis [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_Kurtosisviz.ipynb)

Skew [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/mQC_Skewviz.ipynb)

### **3. Patients test set**

Explained Variance [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_EVviz.ipynb)

MSLL [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_MSLLviz.ipynb)

Kurtosis [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_Kurtosisviz.ipynb)

Skew [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/patient_Skewviz.ipynb)

### **4. Transfer test set**

Explained Variance [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_EVviz.ipynb)

MSLL [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_MSLLviz.ipynb)

Kurtosis [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_Kurtosisviz.ipynb)

Skew [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saigerutherford/brainviz-app/blob/main/transfer_Skewviz.ipynb)