spatial_dist: Calculate Euclidean distance of edges and vertices

In brainGraph: Graph Theory Analysis of Brain MRI Data

Calculate Euclidean distance of edges and vertices

Description

edge_spatial_dist calculates the Euclidean distance of an igraph graph object's edges. The distances are in mm and based on MNI space. These distances are NOT along the cortical surface, so can only be considered approximations, particularly concerning inter-hemispheric connections. The input graph must have atlas as a graph-level attribute.

vertex_spatial_dist calculates, for each vertex of a graph, the average Euclidean distance across all of that vertex's connections.

Usage

edge_spatial_dist(g)

vertex_spatial_dist(g)

Arguments

g	An igraph graph object

Value

edge_spatial_dist - a numeric vector with length equal to the edge count of the input graph, consisting of the Euclidean distance (in mm) of each edge

vertex_spatial_dist - a named numeric vector with length equal to the number of vertices, consisting of the average distance (in mm) for each vertex

Author(s)

Christopher G. Watson, [e-mail]

References

Alexander-Bloch, A.F. and Vertes, P.E. and Stidd, R. et al. (2013) The anatomical distance of functional connections predicts brain network topology in health and schizophrenia. Cerebral Cortex, 23, 127–138. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/cercor/bhr388")}

brainGraph documentation built on June 22, 2024, 7:36 p.m.