diff --git a/_projects/federated-learning.md b/_projects/federated-learning.md
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+++ b/_projects/federated-learning.md
@@ -0,0 +1,22 @@
+---
+title: Benchmarking federated learning approaches against siloed and mega-analysis regimes
+# subtitle:
+status: active
+image: img/projects/fl_overview.png
+layout: project
+people:
+ - Michelle
+ - Nikhil
+---
+
+Although neuroimaging is seeing a growing number of datasets, the international adoption of strong data privacy frameworks ([Marelli & Testa, 2018](https://doi.org/10.1126/science.aar5419)) has led to many of these datasets remaining in so-called “silos”. When data cannot readily be shared, it becomes imperative to develop distributed data processing tools and federated analysis methods to enable large-scale multi-site studies.
+
+In this project, we compare a simple federated analysis setup (i.e. sharing only fitted model parameters) with two traditional experimental setups:
+- Siloed analysis (no sharing of data or model parameters)
+- Mega-analysis (sharing data)
+
+We evaluate the performance of machine learning (ML) models on several neuroimaging datasets of Parkinson’s (PD) and Alzheimer’s disease (AD) on two common prediction tasks in neurodegenerative diseases: 1) brain age and 2) cognitive decline. We hypothesize that model performance improves as we go from siloed to federated to mega-analysis setups.
+
+
+
+
diff --git a/_projects/nipoppy.md b/_projects/nipoppy.md
index 1093de7c4ad..987e1f67752 100644
--- a/_projects/nipoppy.md
+++ b/_projects/nipoppy.md
@@ -1,15 +1,19 @@
---
title: "Nipoppy: A framework for the reproducible organization and processing neuroimaging-clinical datasets"
subtitle: A Neurobagel complement project
-image: img/other/nipoppy_overview.png
+image: img/projects/nipoppy_protocol.png
status: active
layout: project
-repository: https://github.com/neurodatascience/nipoppy/tree/main
-documentation: https://www.neurobagel.org/documentation/Nipoppy/overview/
+repository: https://github.com/nipoppy/nipoppy/tree/main
+documentation: https://nipoppy.readthedocs.io/en/latest
people:
- Michelle
- Nikhil
+ - Mathieu
- Brent
+ - Mohammad
+ - Jacob
+ - Julia
- Remi
- Vincent
- Ines
@@ -21,24 +25,25 @@ Nipoppy is a lightweight framework for standardized organization and processing
The framework consists of the following:
-1. A **data organization specification** for both imaging and non-imaging data
-
- - Whenever possible, we follow the [Brain Imaging Data Structure (BIDS) standard](https://bids.neuroimaging.io/)
- - We provide additional specifications for cases not (yet) covered by BIDS, such as phenotypic data and imaging derivatives
-
-
-
-
-
-2. A **standardized workflow process (i.e., protocol)** covering the following:
+1. A **standardized workflow process (i.e., protocol)** covering the following:
- Curation and organization of MRI and tabular data
- E.g., conversion of DICOM data to BIDS
- Standardized processing of imaging data using existing or custom pipelines
- - E.g., fMRIPrep, MRIQC
+ - E.g., [fMRIPrep](https://fmriprep.org/en/stable/), [MRIQC](https://mriqc.readthedocs.io/en/stable/)
- The [Boutiques framework](https://boutiques.github.io/) is used to flexibly execute and add new pipelines
- Tracking of availability status for raw and processed data
- We also develop an interactive [dashboard](https://digest.neurobagel.org/) for easy visualization of tracker results
- Extraction of imaging-derived phenotypes (IDPs) into files ready for downstream analysis
-3. A [software package](https://github.com/neurodatascience/nipoppy/tree/main) with tools to help work within the framework
+
+2. A **data organization specification** for both imaging and non-imaging data
+
+ - Whenever possible, we follow the [Brain Imaging Data Structure (BIDS) standard](https://bids.neuroimaging.io/)
+ - We provide additional specifications for cases not (yet) covered by BIDS, such as phenotypic data and imaging derivatives
+
+
+
+
+
+3. A [software package](https://github.com/nipoppy/nipoppy/tree/main) with tools to help work within the framework
Nipoppy can also provide metadata to [Neurobagel](https://www.neurobagel.org/documentation/) tools to allow for data harmonization and federated search of participants across multiple studies.
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