serval:BIB_78334C110212
Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.
10.1038/s41467-018-04614-w
000434125100006
29872218
Rosenthal
G.
author
Váša
F.
author
Griffa
A.
author
Hagmann
P.
author
Amico
E.
author
Goñi
J.
author
Avidan
G.
author
Sporns
O.
author
article
2018-06-05
Nature communications
2041-1723
2041-1723
journal
9
1
2178
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.
Brain/diagnostic imaging
Brain/physiology
Computer Simulation
Connectome/methods
Diffusion Tensor Imaging/methods
Humans
Image Processing, Computer-Assisted
Models, Neurological
Nerve Net/diagnostic imaging
Nerve Net/physiology
Rotation
eng
60_published
true
peer-reviewed
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: epublish
University of Lausanne
mailto:serval_help@unil.ch
http://www.unil.ch/serval
http://serval.unil.ch/disclaimer
https://serval.unil.ch/notice/serval:BIB_78334C110212