Connectivity in Amyotrophic Lateral Sclerosis (CoALS) is a pilot study that compared structural and functional brain networks in ALS patients to age-matched controls using graph measures.

By subdividing the brain regions into ‘nodes’ and finding their connections or ‘edges’ using structural measures like diffusion tensor imaging (DTI) or functional counterparts like fMRI, we are able to generate complex network representations of the brain. Graph measures can help parse out such complex brain networks using global and nodal measures.

Eight subjects with ALS underwent Diffusion tensor imaging (DTI) and Functional Magnetic Resonance Imaging (fMRI) as part of this study.  Age matched control data was obtained from online database. Functional MRI processing was done using CONN Toolbox in SPM12 and Diffusion MRI processing was performed by deterministic tractography using DSI Studio. 

Structural Measures using DTI: Network Density was found to be significantly higher in control subjects (mean = 0.078) compared to ALS patients (mean = 0.072), p = 0.047. No significant differences were noted for other network measures.

Functional Measures using fMRI: Global efficiency was found to be significantly higher in ALS subjects (mean = 0.51) compared to controls  (mean = 0.49) , p=0.01. No significant differences were noted for other measures.

The ‘network density’  indicates the potential connections between different nodes of a network. Lesser density in ALS patient indicates reduced structural connections in the network. Since these connections are representative of white matter tracts, it indicates degeneration of white matter tracts in ALS.The global efficiency of a network refers to the average of inverse distance between a node and all other nodes in the network which can be described as ‘interconnectedness’. Results indicates that brain networks in ALS patients have higher functional interconnectedness.  Overall, the graph network analysis of brain depicts structural network breakdown in ALS with an increased functional efficiency.