Discovering individual fingerprints in resting-state functional connectivity using deep neural networks.

"the code and sample data are publicly available at our github repository ( https://github com/bsplku/fingerprintfcdnn ). data s1 supporting information."

"the code and sample data are publicly available at our github repository ( https://github com/bsplku/fingerprintfcdnn ).; the code and sample results of fpfc are available at https://github com/bsplku/fingerprintfcdnn ."

"CONFLICT OF INTEREST STATEMENT The authors have no conflicts of interest regarding this study, including financial, consultant, institutional, or other relationships. The sponsors had no involvement in the study design, data collection, analysis or interpretation of the data, manuscript preparation, or the decision to submit for publication."

"FUNDING INFORMATION This work was supported by the National Research Foundation (NRF) grant, Ministry of Science and ICT (MSIT) of Korea (NRF‐2017R1E1A1A01077288, 2021M3E5D2A0102249311, No. RS‐2023‐00218987), and in part by the Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean Government (23ZS1100, Core Technology Research for Self‐Improving Integrated Artificial Intelligence System)."