Brain fingerprints along the language hierarchy

• Published in: Frontiers in human neuroscience Vol. 16; p. 982905
• Main Authors: Zhang, Juan, Zhuang, Liping, Jiang, Jiahao, Yang, Menghan, Li, Shijie, Tang, Xiangrong, Ma, Yingbo, Liu, Lanfang, Ding, Guosheng
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 15-09-2022; Frontiers Media S.A
• Subjects: Accuracy; Brain; brain fingerprint; Brain mapping; fMRI; functional connectivity; Functional magnetic resonance imaging; Human Neuroscience; individual identification; Language; language hierarchy; Medical imaging; Neural networks; Neuroimaging; Semantics
• ISSN: 1662-5161; 1662-5161
• DOI: 10.3389/fnhum.2022.982905

Recent studies have shown that the brain functional connectome constitutes a unique fingerprint that allows the identification of individuals from a group. However, what information encoded in the brain that makes us unique remains elusive. Here, we addressed this issue by examining how individual identifiability changed along the language hierarchy. Subjects underwent fMRI scanning during rest and when listening to short stories played backward, scrambled at the sentence level, and played forward. Identification for individuals was performed between two scan sessions for each task as well as between the rest and task sessions. We found that individual identifiability tends to increase along the language hierarchy: the more complex the task is, the better subjects can be distinguished from each other based on their whole-brain functional connectivity profiles. A similar principle is found at the functional network level: compared to the low-order network (the auditory network), the high-order network is more individualized (the frontoparietal network). Moreover, in both cases, the increase in individual identifiability is accompanied by the increase in inter-subject variability of functional connectivities. These findings advance the understanding of the source of brain individualization and have potential implications for developing robust connectivity-based biomarkers.