Structural brain network analysis in schizophrenia using minimum spanning tree

Abstract

Schizophrenia is a mental disorder in which functional and structural brain networks are disrupted. Classical network analysis has been used by many researchers to quantify brain networks and to study the network changes in schizophrenia, but unfortunately metrics used in this classical method highly depend on the networks' density and weight; the comparisons made by this method are biased. The minimum spanning tree (MST) is an alternative method to solve this problem, but its usefulness in studying the schizophrenic brain network has not been examined yet. In the present study, we quantified structural brain networks using MST metrics to conduct group analysis between age and sex matched schizophrenic patients and healthy controls. Many MST metrics including Kappa, gamma, max, Betweenness centrality (BC), leaf number, and diameter were found to have significantly changed between two groups that implied a disruption in the whole brain integrity. This was unlike the brain segregation, which was not altered in the schizophrenia group. These results have consistency with Classical network analysis works and demonstrate the MST potential as a powerful method to be used in researches, studying schizophrenic brain connectome.

Random topology organization and decreased visual processing of internet addiction: Evidence from a minimum spanning tree analysis

“…These results imply that the brain of IA participants developed for randomization. MaxDeg, MaxBC, and K are all indexes showing the existence of high‐degree nodes or hubs (Anjomshoa et al, ). These indexes’ values were higher in the IA group, suggesting some brain regions have a greater cognitive burden than comparable regions, which may ultimately be a risk factor for crucial node overloaded.…”

Quantitative and Qualitative Comparison of EEG-Based Neural Network Organization in Two Schizophrenia Groups Differing in the Duration of Illness and Disease Burden: Graph Analysis With Application of the Minimum Spanning Tree

“…For each patient, 25 visual artifact-free and eyes closed (inspected by a clinical neurophysiologist) epochs of 4096 samples (8 seconds) were selected. The selected epoch has a band-pass filtered into the frequencies: delta (0.5-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-12 Hz), beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), and gamma (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45). Because of the fact that different frequency ranges in alpha band are involved in different cognitive processes, 14 the alpha band was divided into 2 frequency bands.…”

“…27,33 Furthermore, earlier schizophrenia studies using MST for diffusion tensor imaging (DTI) showed decreased centrality (low number of central hubs in the network) in several brain regions for the groups with psychotic disorders, 24 as well as differences in network organization between healthy controls and patients. 34…”

“…27,33 Furthermore, earlier schizophrenia studies using MST for diffusion tensor imaging (DTI) showed decreased centrality (low number of central hubs in the network) in several brain regions for the groups with psychotic disorders, 24 as well as differences in network organization between healthy controls and patients. 34 Even though there are many neuroimaging studies in schizophrenia that investigate disconnectivity, both, in structural and functional aspects, we cannot clearly determine how the influence of mental illness burden affects the organization of neural networks. Especially, there is a lack of EEG-based papers referring to this problem.…”

A comparative study of verbal fluency in patients with paranoid schizophrenia first grade relatives and healthy controls

“…Rich evidence on specific cognitive dysfunction, not only as epiphenomenon due to therapy but core feature of the disease is currently been collected 1 . These cognitive changes have been discussed in association with neurodevelopmental theory and changes in brain circles, engaged in cognition, particularly these, related to prefrontal cortex and its networks to cortical and subcortical structures 2,3 .…”