Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

中文翻译：

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使用内在功能连接对精神分裂症症状严重程度和超高风险的判别分析

过去的研究一直显示精神分裂症中大规模脑网络的功能性不连通性。在这项研究中，我们旨在进一步评估多变量模式分析 (MVPA) 是否可以产生患者症状的敏感预测因子，以及从全脑网络的内在功能连接中识别精神分裂症的超高风险 (UHR) 阶段。我们首先结合基于秩的特征选择和支持向量机方法来区分 43 名精神分裂症患者和 52 名健康对照。然后将构建的分类器应用于检查 18 个 UHR 个体的功能连接配置文件。分类器表明 MVPA 测量值与症状严重程度之间存在可靠的关系，在更严重的精神分裂症患者中具有更高的分类准确性。UHR 受试者的分类分数介于健康对照组和患者之间，表明脑功能异常处于中等水平。此外，在基线时具有类似精神分裂症的连接特征的 UHR 个体在随访中表现出更高的转化为全面疾病的比率。区分性大脑区域的空间图表明默认模式网络中功能连接性的增加，而精神分裂症中小脑、丘脑和视觉区域的功能连接性减少。这些发现可能在精神分裂症的早期诊断和干预中具有潜在的用途。在基线时具有类似精神分裂症的连接特征的 UHR 个体在随访中表现出更高的转化为全面疾病的比率。区分性大脑区域的空间图表明默认模式网络中功能连接性的增加，而精神分裂症中小脑、丘脑和视觉区域的功能连接性减少。这些发现可能在精神分裂症的早期诊断和干预中具有潜在的用途。在基线时具有类似精神分裂症的连接特征的 UHR 个体在随访中表现出更高的转化为全面疾病的比率。区分性大脑区域的空间图表明默认模式网络中功能连接性的增加，而精神分裂症中小脑、丘脑和视觉区域的功能连接性减少。这些发现可能在精神分裂症的早期诊断和干预中具有潜在的用途。