| Literature DB >> 35741612 |
Yanli Yang1, Yang Zhang1, Jie Xiang1, Bin Wang1, Dandan Li1, Xueting Cheng1, Tao Liu1, Xiaohong Cui1.
Abstract
The analysis of resting-state fMRI signals usually focuses on the low-frequency range/band (0.01-0.1 Hz), which does not cover all aspects of brain activity. Studies have shown that distinct frequency bands can capture unique fluctuations in brain activity, with high-frequency signals (>0.1 Hz) providing valuable information for the diagnosis of schizophrenia. We hypothesized that it is meaningful to study the dynamic reconfiguration of schizophrenia through different frequencies. Therefore, this study used resting-state functional magnetic resonance (RS-fMRI) data from 42 schizophrenia and 40 normal controls to investigate dynamic network reconfiguration in multiple frequency bands (0.01-0.25 Hz, 0.01-0.027 Hz, 0.027-0.073 Hz, 0.073-0.198 Hz, 0.198-0.25 Hz). Based on the time-varying dynamic network constructed for each frequency band, we compared the dynamic reconfiguration of schizophrenia and normal controls by calculating the recruitment and integration. The experimental results showed that the differences between schizophrenia and normal controls are observed in the full frequency, which is more significant in slow3. In addition, as visual network, attention network, and default mode network differ a lot from each other, they can show a high degree of connectivity, which indicates that the functional network of schizophrenia is affected by the abnormal brain state in these areas. These shreds of evidence provide a new perspective and promote the current understanding of the characteristics of dynamic brain networks in schizophrenia.Entities:
Keywords: dynamic reconfiguration; frequency-specific; multilayer network
Year: 2022 PMID: 35741612 PMCID: PMC9221032 DOI: 10.3390/brainsci12060727
Source DB: PubMed Journal: Brain Sci ISSN: 2076-3425