Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints

Daouia I. Larabi, Martin Gell, Enrico Amico, Simon B. Eickhoff, Kaustubh R. Patil

Open source

DOI: 10.1162/imag.a.1444
Published: 2026
Container: Imaging Neuroscience
Publisher: MIT Press
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1162/imag.a.1444,
  title = {Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints},
  author = {Daouia I. Larabi and Martin Gell and Enrico Amico and Simon B. Eickhoff and Kaustubh R. Patil},
  year = {2026},
  journal = {Imaging Neuroscience},
  doi = {10.1162/imag.a.1444},
  url = {https://doi.org/10.1162/imag.a.1444}
}

RIS

TY  - JOUR
TI  - Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints
AU  - Daouia I. Larabi
AU  - Martin Gell
AU  - Enrico Amico
AU  - Simon B. Eickhoff
AU  - Kaustubh R. Patil
PY  - 2026
JO  - Imaging Neuroscience
DO  - 10.1162/imag.a.1444
UR  - https://doi.org/10.1162/imag.a.1444
ER  -

APA

Larabi, D. I., Gell, M., Amico, E., Eickhoff, S. B., & Patil, K. R. (2026). Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints. Imaging Neuroscience. https://doi.org/10.1162/imag.a.1444

Source records

crossref · retrieved 2026-11-10T19:48:15.261Z