Suppr超能文献

皮质厚度与振荡相位重置:精神分裂症中突显网络功能障碍的一种潜在机制。

Cortical thickness and oscillatory phase resetting: a proposed mechanism of salience network dysfunction in schizophrenia.

作者信息

Palaniyappan L, Doege K, Mallikarjun P, Liddle E, Francis-Liddle P

机构信息

Division of Psychiatry, University of Nottingham, Queen's Medical Centre, Nottingham, United Kingdom.

出版信息

Psychiatriki. 2012 Apr-Jun;23(2):117-29.

Abstract

Schizophrenia is characterised by both electrophysiological abnormalities and consistent changes in the structure of cortical grey matter. But the relationship between these two observations is largely unknown. Structural changes reported in schizophrenia include reduced grey matter volume, thickness and surface area in several cortical regions, but most frequently in the insula and anterior cingulate cortex. These two regions together constitute an intrinsic brain circuit known as the "Salience Network", which has a key role in stimulus processing. During stimulus processing tasks, evoked activity is noted using electroencephalography (EEG). Phase resetting of ongoing oscillations contributes to this evoked activity. Neuronal oscillations play a crucial role in cerebral recruitment during cognitive tasks, and influencing the oscillatory phase can modulate cortical excitability and the transition between various cognitive states. At a network level, such a transition or switch is thought to be enabled by the Salience Network. In this study, we investigated the relationship between the cortical thickness in the Salience Network (measured using MRI) and the degree of phase resetting observed during an oddball task (measured using EEG) in 18 medicated male patients in a clinically stable phase of schizophrenia and 20 age and gender matched healthy controls. We obtained a measure of partial phase resetting after a stimulus is presented, and a second measure representing mean evoked activity, using the methods proposed by Martinez-Montes. Using MRI analysis, we have firstly shown that there is a significant loss of cortical thickness of regions that constitute the Salience Network in patients with schizophrenia. EEG analysis revealed that in healthy controls, the expected relationship between phase resetting and evoked electrical activity is observed, but in patients with schizophrenia the theta phase resetting is a weak predictor of the activity evoked by attending to a target stimulus, though the difference between the groups did not reach statistical significance in the present sample. Furthermore, in patients with schizophrenia the reduced thickness in the Salience Network is associated with the inefficient phase resetting of theta oscillations. Our findings suggest that the grey matter reduction seen in the Salience Network in patients with schizophrenia has substantial functional consequences. In particular, the structural defect of the insula that is seen in schizophrenia is likely to be associated with less efficient recruitment of brain circuits for processing information. This implies a possible mechanism by which disruptions in the intrinsic Salience Network can result in a general disturbance in salience detection seen in schizophrenia.

摘要

精神分裂症的特征在于电生理异常以及皮质灰质结构的持续变化。但这两种观察结果之间的关系在很大程度上尚不清楚。精神分裂症中报道的结构变化包括几个皮质区域的灰质体积、厚度和表面积减少,但最常见于脑岛和前扣带回皮质。这两个区域共同构成一个被称为“突显网络”的内在脑回路,其在刺激处理中起关键作用。在刺激处理任务期间,使用脑电图(EEG)记录诱发活动。正在进行的振荡的相位重置有助于这种诱发活动。神经元振荡在认知任务期间的大脑募集过程中起关键作用,并且影响振荡相位可以调节皮质兴奋性以及各种认知状态之间的转换。在网络层面,这种转换或切换被认为是由突显网络实现的。在本研究中,我们调查了18名处于精神分裂症临床稳定期的服药男性患者和20名年龄及性别匹配的健康对照者中,突显网络中的皮质厚度(使用MRI测量)与在奇偶数任务期间观察到的相位重置程度(使用EEG测量)之间的关系。我们使用Martinez - Montes提出的方法,在呈现刺激后获得了部分相位重置的测量值,以及代表平均诱发活动的第二个测量值。通过MRI分析,我们首先表明精神分裂症患者中构成突显网络的区域存在明显的皮质厚度损失。EEG分析显示,在健康对照者中,观察到了相位重置与诱发电活动之间的预期关系,但在精神分裂症患者中,θ相位重置是关注目标刺激所诱发活动的一个较弱预测指标,尽管在本样本中两组之间的差异未达到统计学显著性。此外,在精神分裂症患者中,突显网络中厚度的减少与θ振荡的低效相位重置有关。我们的研究结果表明,精神分裂症患者突显网络中所见的灰质减少具有重大的功能后果。特别是,精神分裂症中所见的脑岛结构缺陷可能与处理信息的脑回路募集效率较低有关。这暗示了一种可能的机制,通过该机制,内在突显网络的破坏可导致精神分裂症中所见的突显检测普遍紊乱。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验