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The aim of this study is to determine whether multiple sclerosis (MS) is associated with changes in global degree rank order disruption index (kD), a functional connectivity-based measure representing the overall distribution of nodal degree centrality, and its relationship between the clinical presentation of MS (global disability, cognitive and motor performance). The performance of kD will be assessed in comparison to established magnetic resonance imaging (MRI) biomarkers in MS (regional degree centrality, structural MRI with volumetry, diffusion-weighted imaging [DWI], lesion mapping) in order to assess the potential clinical utility of kD. To this end, a pre-existing dataset of 64 people with MS and 65 healthy control subjects will be evaluated in this secondary analysis.

The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects.

Supplemental material, JOP849814_supplemental_material for Cannabis-induced altered states of consciousness are associated with specific dynamic brain connectivity states by Yuliya Zaytseva, Jiří Horáček, Jaroslav Hlinka, Iveta Fajnerová, Renata Androvičová, Jaroslav Tintěra, Virginio Salvi, Marie Balíková, Tomáš Hložek, Filip Španiel and Tomáš Páleníček in Journal of Psychopharmacology