Inferring the Joint Distribution of Structural and Functional Connectivity in the Human Brain using UNIT-DDPM
Canamedi, V.
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AO_SCPLOWBSTRACTC_SCPLOWThe structural wiring of the brain is expected to produce a repertoire of functional networks, across time, context, individuals and vice versa. Therefore, a method to infer the joint distribution of structural and functional connectomes would be of immense value. However, existing approaches only provide deterministic snapshots of the structure-function relationship. Here we use an unpaired image translation method, UNIT-DDPM, that infers a joint distribution of structural and functional connectomes. Our approach allows estimates of variability of function for a given structure and vice versa. Furthermore, we found a significant improvement in prediction accuracy among individual brain networks, implicating a tighter coupling of structure and function than previously understood. Also, our approach has the ad-vantage of not relying on paired samples for training. This novel approach provides a means for identifying regions of consistent structure-function coupling.
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