A Neuroinformatics Framework for Evaluating Functional Connectivity Metrics in Small-Sample Resting-State fMRI: An Age-Stratified Autism Study.

Haghighat H.

Open source

DOI
10.1007/s12021-026-09816-y
Published
2026-09-15
Container
Neuroinformatics
Publisher
Not recorded
Open access
no

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BibTeX

@article{allodium:10.1007/s12021-026-09816-y,
  title = {A Neuroinformatics Framework for Evaluating Functional Connectivity Metrics in Small-Sample Resting-State fMRI: An Age-Stratified Autism Study.},
  author = {Haghighat H.},
  year = {2026},
  journal = {Neuroinformatics},
  doi = {10.1007/s12021-026-09816-y},
  url = {https://doi.org/10.1007/s12021-026-09816-y}
}

RIS

TY  - JOUR
TI  - A Neuroinformatics Framework for Evaluating Functional Connectivity Metrics in Small-Sample Resting-State fMRI: An Age-Stratified Autism Study.
AU  - Haghighat H.
PY  - 2026
JO  - Neuroinformatics
DO  - 10.1007/s12021-026-09816-y
UR  - https://doi.org/10.1007/s12021-026-09816-y
ER  - 

APA

H., H. (2026). A Neuroinformatics Framework for Evaluating Functional Connectivity Metrics in Small-Sample Resting-State fMRI: An Age-Stratified Autism Study.. Neuroinformatics. https://doi.org/10.1007/s12021-026-09816-y

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