Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.
Fiche du document
5 juin 2018
- doi: 10.1038/s41467-018-04614-w
- issn: 2041-1723
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41467-018-04614-w
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/29872218
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/2041-1723
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_78334C1102128
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
Sujets proches
Cerebrum Mind Relations--Foreign countries Relations (Canon law)Citer ce document
G. Rosenthal et al., « Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes. », Serveur académique Lausannois, ID : 10.1038/s41467-018-04614-w
Métriques
Partage / Export
Résumé
Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.