Functional connectome fingerprinting across the lifespan. (St-Onge F. et al., 2023)

Citation :
St-Onge, F., Javanray, M., Pichet Binette, A., Strikwerda-Brown, C., Remz, J., Spreng, R. N., Shafiei, G., Misic, B., Vachon-Presseau, É., & Villeneuve, S. (2023). Functional connectome fingerprinting across the lifespan. Network neuroscience (Cambridge, Mass.)7(3), 1206–1227. https://doi.org/10.1162/netn_a_00320

Full text : Here

Functional connectome fingerprinting across the lifespan.

St-Onge F, Javanray M, Pichet Binette A, Strikwerda-Brown C, Remz J, Spreng RN, Shafiei G, Misic B, Vachon-Presseau E, Villeneuve S.

published in Network Neurosciences, October 2023.

ABSTRACT :
Systematic changes have been observed in the functional architecture of the human brain with advancing age. However, functional connectivity (FC) is also a powerful feature to detect unique “connectome fingerprints,” allowing identification of individuals among their peers. Although fingerprinting has been robustly observed in samples of young adults, the reliability of this approach has not been demonstrated across the lifespan. We applied the fingerprinting framework to the Cambridge Centre for Ageing and Neuroscience cohort (n = 483 aged 18 to 89 years). We found that individuals are “fingerprintable” (i.e., identifiable) across independent functional MRI scans throughout the lifespan. We observed a U-shape distribution in the strength of “self-identifiability” (within-individual correlation across modalities), and “others-identifiability” (between-individual correlation across modalities), with a decrease from early adulthood into middle age, before improving in older age. FC edges contributing to self-identifiability were not restricted to specific brain networks and were different between individuals across the lifespan sample. Self-identifiability was additionally associated with regional brain volume. These findings indicate that individual participant-level identification is preserved across the lifespan despite the fact that its components are changing nonlinearly.