RestLib: A library for rsFMRI analysis
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Contents |
People
- Javier Guaje
- Andrea Soddu (London Ontario)
- Christophe Phillips (Liege)
- Francisco Gómez
Summary
In the recent years, fMRI resting state activity has provided a set of powerful biomarkers for many pathological altered brain conditions such as, Alzheimer, Parkinson and disorders of consciousness, among others. These studies aim to establish changes in the resting state activity correlating with specific brain conditions. Usually, different dynamical aspects of the signal are exploited (functional connectivity, resting state network integrity or graph properties) to construct the corresponding biomarkers of the disease. Several efforts have been performed to mix individual subject information in group maps that capture the main common patterns of the studied populations. These maps provide valuable information about the studied condition. However, the use of this knowledge in clinical settings will require an individual subject resting state analysis. This is a challenging task, especially in severely affected brain conditions, because different patients can have quite specific noise sources. In this work, we propose an automated single subject resting state analysis tool that aims to isolate individual source noises and provide an individual characterization of multiple Resting State Networks at single subject level. The analysis performed by this tool will be used in the construction of diagnostic tool that operate at single subject level, but also as an input for group based analysis. We will test our approach in severely affected brain conditions such as disorder of consciousness and congenitally affected brains.
Method overview
Data sources
Results (Expected)
- Journal article. Complete library report.
