Characterizing variability in resting-state functional magnetic resonance imaging (rsfMRI) metrics: A normative modeling framework

Alejandro Amador-Tejada, Ethan Danielli, Michael D. Noseworthy

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DOI: 10.1016/j.neuroimage.2026.122283
Published: 2026-11
Container: NeuroImage
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.neuroimage.2026.122283,
  title = {Characterizing variability in resting-state functional magnetic resonance imaging (rsfMRI) metrics: A normative modeling framework},
  author = {Alejandro Amador-Tejada and Ethan Danielli and Michael D. Noseworthy},
  year = {2026},
  journal = {NeuroImage},
  doi = {10.1016/j.neuroimage.2026.122283},
  url = {https://doi.org/10.1016/j.neuroimage.2026.122283}
}

RIS

TY  - JOUR
TI  - Characterizing variability in resting-state functional magnetic resonance imaging (rsfMRI) metrics: A normative modeling framework
AU  - Alejandro Amador-Tejada
AU  - Ethan Danielli
AU  - Michael D. Noseworthy
PY  - 2026
JO  - NeuroImage
DO  - 10.1016/j.neuroimage.2026.122283
UR  - https://doi.org/10.1016/j.neuroimage.2026.122283
ER  -

APA

Amador-Tejada, A., Danielli, E., & Noseworthy, M. D. (2026). Characterizing variability in resting-state functional magnetic resonance imaging (rsfMRI) metrics: A normative modeling framework. NeuroImage. https://doi.org/10.1016/j.neuroimage.2026.122283

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crossref · retrieved 2026-11-10T12:41:53.426Z