Publication Type | Preprint |
Authors | Jamison K, Gu Z, Wang Q, Tozlu C, Sabuncu M, Kuceyeski A |
Journal | bioRxiv |
Date Published | 10/08/2024 |
ISSN | 2692-8205 |
Abstract | Brain connectivity can be estimated in many ways, depending on modality and processing strategy. Here we present the Krakencoder, a joint connectome mapping tool that simultaneously, bidirectionally translates between structural (SC) and functional connectivity (FC), and across different atlases and processing choices via a common latent representation. These mappings demonstrate unprecedented accuracy and individual-level identifiability; the mapping between SC and FC has identifiability 42-54% higher than existing models. The Krakencoder combines all connectome flavors via a shared low-dimensional latent space. This "fusion" representation i) better reflects familial relatedness, ii) preserves age- and sex-relevant information and iii) enhances cognition-relevant information. The Krakencoder can be applied without retraining to new, out-of-age-distribution data while still preserving inter-individual differences in the connectome predictions and familial relationships in the latent representations. The Krakencoder is a significant leap forward in capturing the relationship between multi-modal brain connectomes in an individualized, behaviorally- and demographically-relevant way. |
DOI | 10.1101/2024.04.12.589274 |
PubMed ID | 38659856 |
PubMed Central ID | PMC11042193 |