首页> 美国卫生研究院文献>Frontiers in Human Neuroscience >Combination of Resting State fMRI DTI and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA
【2h】

Combination of Resting State fMRI DTI and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA

机译:结合静息状态fMRIDTI和sMRI数据通过N-way MCCA + jICA区分精神分裂症

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called “mCCA + jICA” as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.
机译:多模态脑成像数据已显示出在回答科学上有趣的和临床相关的问题上越来越有用。每种大脑成像技术都提供了关于大脑功能或结构的不同视图,而多峰融合利用了每种成像技术的优势,并且可能发现隐藏的关系,这些关系可以合并来自单独的神经成像研究的发现。但是,当前大多数方法都集中于成对融合,并且在N向数据融合和检查多种数据类型之间的关系方面的工作还很少。我们最近开发了一种称为“ mCCA + jICA”的方法,它是一种新颖的多路融合方法,能够研究多种模式之间共享或不同的疾病风险因素,以及各种模式之间的完全对应。在本文中,我们将这种模型应用于静息状态fMRI(低频波动幅度,ALFF),灰质(GM)密度和DTI(分数各向异性,FA)数据,以阐明精神分裂症患者的潜在异常情况(SZs,n = 35)相对于健康对照(HCs,n = 28)。在SZs中识别了模态常见和模态唯一异常区域,然后将其成功分类为七个模态组合,显示了mCCA + jICA模型及其结果的广泛适用性的潜力。此外,一对GM-DTI成分与正负综合症量表(PANSS)的正症状子量表显着相关,表明默认模型网络中的GM密度变化以及前丘脑辐射中的白质破坏与阳性PANSS增加。研究结果表明,额叶的DTI各向异性变化可能与额叶前额叶皮层和颞上回的相应功能/结构变化有关,这些变化被认为在SZ的临床表达中起作用。

著录项

相似文献

  • 外文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号