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NBS-Predict: A prediction-based extension of the network-based statistic.
Emin Serin1, Andrew Zalesky2, Adu Matory3
1Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, Germany; Division of Mind and Brain Research, Department for Psychiatry, Charité-Universitätsmedizin Berlin, Charitéplatz 1, Berlin 10117, Germany.
Neuroimage
|October 5, 2021
Summary
NBS-Predict integrates machine learning with network-based statistics to identify brain connectivity biomarkers for precision medicine. This approach accurately predicts conditions like schizophrenia and intelligence scores from neuroimaging data.
Area of Science:
- Neuroscience
- Computational Biology
- Medical Informatics
Background:
- Graph models are crucial for studying brain connectivity across scales.
- Network-based statistic (NBS) analyzes brain graphs but lacks individual-level inference for precision medicine.
- Machine learning (ML) combined with NBS can enhance biomarker discovery.
Purpose of the Study:
- Introduce NBS-Predict, a novel approach combining ML and NBS.
- Evaluate NBS-Predict's performance on simulated and real neuroimaging data.
- Demonstrate NBS-Predict's utility in identifying generalizable neuroimaging biomarkers.
Main Methods:
- Developed NBS-Predict with a user-friendly graphical user interface (GUI).
- Integrated ML models with connected components within a cross-validation (CV) framework.
- Applied NBS-Predict to simulated data, schizophrenia rs-fMRI data, and Human Connectome Project data.
Main Results:
- NBS-Predict demonstrated good statistical power on simulated datasets.
- Achieved 90% accuracy in classifying schizophrenia using functional connectivity matrices, identifying affected subnetworks.
- Predicted general intelligence scores (r=0.2) and associated subnetworks from rs-fMRI data.
- Outperformed existing feature selection methods and connectome-based predictive modeling (CPM).
Conclusions:
- NBS-Predict is a powerful and convenient tool for identifying generalizable neuroimaging biomarkers.
- The method facilitates precision medicine by enabling individual-level predictions.
- NBS-Predict advances the analysis of brain connectivity for clinical and research applications.
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