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Power spectral aspects of the default mode network in schizophrenia: an MEG study

机译:精神分裂症默认模式网络的功率谱方面:MEG研究

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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.
机译:背景精神分裂症的症状与自我监控功能的缺陷有关,这可能是默认模式网络(DMN)方面不规则的结果。精神分裂症的特征还可以在于静息状态下反映的大脑活动的功能异常。振荡分析提供了对静息大脑活动的重要理解。然而,尽管空间分辨率高,但由于其空间分辨率低,使用脑电图的常规方法受到了限制。这项研究的目的是使用脑磁图研究静息的大脑振荡和基于不同频带(例如theta,α,β和γ)中源空间的默认模式网络。此外,我们调查了这些休息和DMN活动是否可以将精神分裂症患者与正常对照区分开。为此,对20个患者和20个对照组的静止状态下每个频段的功率谱密度成像并在空间标准化的大脑模板上进行比较。结果DMN活性在Alpha波段的空间分布与以前的fMRI研究相似。在静止时激活扣带后皮质(PCC)和顶下外侧皮质,而在休息时而不是在任务期间停用内侧前额叶皮质(MPFC)。尽管MPFC和PCC区域显示出相反的激活模式,但是这两个区域在静止时具有显着的一致性。精神分裂症患者的DMN和PCC的静息活动增加,主要在θ和α谱带中。结论通过使用MEG识别主要在α带的DMN区域,我们发现精神分裂症患者的后扣带中的静息和DMN活动均增加。此外,精神分裂症患者在静止时的γ带中PCC和MPFC之间的相干性降低。

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