Structural Connectome Fingerprinting
Date:
- Best graphical abstract award
Introduction:
Connectome fingerprinting, the process of identification and characterization of individuals from their brain activity data, has recently garnered significant attention. It has been shown that functional magnetic resonance imaging (fMRI) recordings of individuals carry unique information that not only acts as an identifier but can also reflect cognitive abilities such as fluid intelligence. Although substantial research regarding fingerprinting has been conducted using fMRI, the extant literature using white-matter tractography does not adequately leverage structural connectivity for the purpose of fingerprinting.
Aims:
The objective of this research is to explore advantages of exploiting structural connectivity fingerprints in the identification of individuals and behavior prediction.
Methods:
The openly available data from the human connectome project was used to collect anatomical information (i.e. cortical thickness and curvature), and functional and structural connectivity of 1000 subjects as fingerprints of behavioral characteristics. For 42 subjects, the fingerprints were used to identify the retest subjects in a pool of all 1000 subjects.
Results:
Our findings show that a high resolution structural connectivity fingerprint has the highest identification capability while explaining the behavioral characteristics.
Conclusions:
We showed that the new method of structural fingerprinting provided a significantly better measure for individual identification. Additionally, it was shown that identification by itself does not necessarily make a fingerprinting measure informative as an interpretable predictor of cognition/behavior, as features like curvature perform well for the identification task. Thus, the interpretability of behavior from the proposed fingerprinting measure displays the practicality of the new method.