Andreou Christina, Leicht Gregor, Nolte Guido, Polomac Nenad, Moritz Steffen, Karow Anne, Hanganu-Opatz Ileana L, Engel Andreas K, Mulert Christoph
Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Schizophr Res. 2015 Feb;161(2-3):299-307. doi: 10.1016/j.schres.2014.12.018. Epub 2014 Dec 29.
Disturbed functional connectivity is assumed to underlie neurocognitive deficits in patients with schizophrenia. As neurocognitive deficits are already present in the high-risk state, identification of the neural networks involved in this core feature of schizophrenia is essential to our understanding of the disorder. Resting-state studies enable such investigations, while at the same time avoiding the known confounder of impaired task performance in patients. The aim of the present study was to investigate EEG resting-state connectivity in high-risk individuals (HR) compared to first episode patients with schizophrenia (SZ) and to healthy controls (HC), and its association with cognitive deficits.
64-channel resting-state EEG recordings (eyes closed) were obtained for 28 HR, 19 stable SZ, and 23 HC, matched for age, education, and parental education. The imaginary coherence-based multivariate interaction measure (MIM) was used as a measure of connectivity across 80 cortical regions and six frequency bands. Mean connectivity at each region was compared across groups using the non-parametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients.
SZ displayed increased theta-band resting-state MIM connectivity across midline, sensorimotor, orbitofrontal regions and the left temporoparietal junction. HR displayed intermediate theta-band connectivity patterns that did not differ from either SZ or HC. Mean theta-band connectivity within the above network partially mediated verbal memory deficits in SZ and HR.
Aberrant theta-band connectivity may represent a trait characteristic of schizophrenia associated with neurocognitive deficits. As such, it might constitute a promising target for novel treatment applications.
功能连接紊乱被认为是精神分裂症患者神经认知缺陷的基础。由于神经认知缺陷在高危状态下就已存在，识别参与精神分裂症这一核心特征的神经网络对于我们理解该疾病至关重要。静息态研究能够进行此类调查，同时避免了患者任务表现受损这一已知混杂因素。本研究的目的是调查高危个体（HR）与首发精神分裂症患者（SZ）及健康对照（HC）相比的脑电图静息态连接性，及其与认知缺陷的关联。
对28名HR、19名稳定期SZ和23名HC进行了64导静息态脑电图记录（闭眼），三组在年龄、教育程度和父母教育程度方面相匹配。基于虚数相干的多变量交互测量（MIM）被用作80个皮质区域和六个频段连接性的测量指标。使用非参数随机化方法比较各组每个区域的平均连接性。此外，应用基于网络的统计方法来识别患者中受影响的网络。
SZ在中线、感觉运动、眶额区域和左侧颞顶叶交界处显示出θ频段静息态MIM连接性增加。HR显示出中间的θ频段连接模式，与SZ或HC均无差异。上述网络内的平均θ频段连接性部分介导了SZ和HR的言语记忆缺陷。
异常的θ频段连接性可能代表与神经认知缺陷相关的精神分裂症的一种特质特征。因此，它可能构成新型治疗应用的一个有前景的靶点。
