Relationship between MEG global dynamic functional network connectivity measures and symptoms in schizophrenia

SCHIZOPHRENIA RESEARCH

卷:209

Article

Sanfratello, L.¹  Houck, J. M.^1,2  Calhoun, V. D.^1,2 

[1] Mind Res Network, Albuquerque, NM USA

[2] Univ New Mexico, Albuquerque, NM 87131 USA

关键词: Magnetoencephalography;    Resting state;    Schizophrenia;    Functional connectivity;   

DOI  :  10.1016/j.schres.2019.05.007

来源: Elsevier

【 摘 要 】

An investigation of differences in dynamic functional network connectivity (dFNC) of healthy controls (HC) versus that of schizophrenia patients (SP) was completed, using eyes-open resting state MEG data. The MEG analysis utilized a source-space activity estimate (MNE/dSPM) whose result was the input to a group spatial independent component analysis (ICA), on which the networks of our MEG dFNC analysis were based. We have previously reported that our MEG dFNC revealed that SP change between brain meta-states (repeating patterns of network correlations which are allowed to overlap in time) significantly more often and to states which arc more different, relative to HC. Here, we extend our previous work to investigate the relationship between symptomology in SP and four meta-state metrics. We found a significant correlation between positive symptoms and the two meta-state metrics which showed significant differences between HC and SP. These two statistics quantified 1) how often individuals change state and 2) the total distance traveled within the state-space. We additionally found that a clustering of the meta-state metrics divides SP into groups which vary in symptomology. These results indicate specific relationships between symptomology and brain function for SP. (C) 2019 Elsevier B.V. All rights reserved.

【 授权许可】

Free