Spectral graph model for fMRI: A biophysical, connectivity-based generative model for the analysis of frequency-resolved resting-state fMRI
Ashish Raj, Benjamin S. Sipes, Parul Verma, Daniel H. Mathalon, Bharat Biswal, Srikantan Nagarajan · 2024
Read Spectral graph model for fMRI: A biophysical, connectivity-based generative model for the analysis of frequency-resolved resting-state fMRI by Ashish Raj, Benjamin S. Sipes, Parul Verma, Daniel H. Mathalon, Bharat Biswal, Srikantan Nagarajan (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12315728.txt.
Description
Ashish Raj and five co-authors build a physics-based model of resting brain scans, in a 2024 paper. Resting scans are a main tool for mapping how brain regions work together. Most studies just track which regions rise and fall in step, throwing away the rich timing detail in the signal. Such step-tracking also lacks roots in the brain's actual wiring and physics.
The new model starts from the wiring map itself. It grows signals the way the wired brain might, then splits them by rhythm speed using math borrowed from graph theory. That split lets slow and fast rhythms each tell their own story about brain order. The authors say the model can sharpen studies of brain disease, where rhythm mix may shift before plain step-tracking notices. It also gives each scan result a grounding in body structure that pure statistics cannot.
Catalog record
| CREATOR | Ashish Raj, Benjamin S. Sipes, Parul Verma, Daniel H. Mathalon, Bharat Biswal, Srikantan Nagarajan |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 78 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |