From Matrices to Knowledge: Using Semantic Networks to Annotate the Connectome.

ABSTRACT: The connectome is regarded as the key to brain function in health and disease. Structural and functional neuroimaging enables us to measure brain connectivity in the living human brain. The field of connectomics describes the connectome as a mathematical graph with its connection strengths being represented by connectivity matrices. Graph theory algorithms are used to assess the integrity of the graph as a whole and to reveal brain network biomarkers for brain diseases; however, the faulty wiring of single connections or subnetworks as the structural correlate for neurological or mental diseases remains elusive. We describe a novel approach to represent the knowledge of human brain connectivity by a semantic network - a formalism frequently used in knowledge management to describe the sema

SUBMITTER: Kopetzky SJ 

PROVIDER: S-EPMC6292998 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature