摘要:Background Symptoms of schizophrenia are related to deficits in self-monitoring function, which may be a consequence of irregularity in aspects of the default mode network (DMN). Schizophrenia can also be characterized by a functional abnormality of the brain activity that is reflected in the resting state. Oscillatory analysis provides an important understanding of resting brain activity. However, conventional methods using electroencephalography are restricted because of low spatial resolution, despite their excellent temporal resolution. The aim of this study was to investigate resting brain oscillation and the default mode network based on a source space in various frequency bands such as theta, alpha, beta, and gamma using magnetoencephalography. In addition, we investigated whether these resting and DMN activities could distinguish schizophrenia patients from normal controls. To do this, the power spectral density of each frequency band at rest was imaged and compared on a spatially normalized brain template in 20 patients and 20 controls. Results The spatial distribution of DMN activity in the alpha band was similar to that found in previous fMRI studies. The posterior cingulate cortex (PCC) and lateral inferior parietal cortex were activated at rest, while the medial prefrontal cortex (MPFC) was deactivated at rest rather than during the task. Although the MPFC and PCC regions exhibited contrasting activation patterns, these two regions were significantly coherent at rest. The DMN and resting activities of the PCC were increased in schizophrenia patients, predominantly in the theta and alpha bands. Conclusions By using MEG to identify the DMN regions, predominantly in the alpha band, we found that both resting and DMN activities were augmented in the posterior cingulate in schizophrenia patients. Furthermore, schizophrenia patients exhibited decreased coherence between the PCC and MPFC in the gamma band at rest.
关键词:Default mode network ; Magnetoencephalography ; Power spectral density ; Alpha ; Schizophrenia