We introduce a deep learning approach to derive functional fingerprint of the brain that can identify individuals. By investigating the features extracted by our model, we noticed that they mostly resemble the existing resting state networks, and three networks (default mode, attention, and frontopariental control networks) contribute the most to individual discriminability.
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