| name | fmri-mahalanobis-bures-whitening |
| description | De-individualizing fMRI signals via Mahalanobis whitening and Bures geometry — quantum-motivated dimensionality reduction for brain imaging |
| category | neuroscience |
| trigger_words | ["Mahalanobis","Bures distance","fMRI whitening","de-individualization","quantum geometry"] |
| arxiv_id | 2511.07313 |
De-Individualizing fMRI Signals via Mahalanobis Whitening and Bures Geometry
Summary
Uses Mahalanobis data whitening to distill meaningful information from fMRI signals. Interprets whitening as two-stage de-individualization motivated by Bures distance, connected to quantum mechanics. Potential for improving Alzheimer's diagnosis accuracy.
Core Methodology
- Category: q-bio.NC
- Authors: Aaron Jacobson, Tingting Dan, Martin Styner, Guorong Wu, Shahar Kovalsky, Caroline Moosmueller
- arXiv: 2511.07313
Key Concepts
- fMRI
- Mahalanobis whitening
- Bures distance
- quantum mechanics
- functional connectivity
- dimensionality reduction
- Alzheimer diagnosis
Activation Triggers
Mahalanobis, Bures distance, fMRI whitening, de-individualization, quantum geometry
