Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Psychology, Stockholm University, Stockholm, Sweden; Center for Dependency Disorders, Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden.
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden; Center for Aging and Demographic Research, Umeå University, Umeå, Sweden.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2018 Dec;3(12):1003-1012. doi: 10.1016/j.bpsc.2018.04.010. Epub 2018 May 9.
Psychopathic traits vary dimensionally in the population and are associated with multiple negative outcomes. The impaired integration theory (IIT) proposes that psychopathic traits are associated with abnormal neural network topology, such that disturbed integration of neural networks results in a self-perpetuating impairment in rapid integration and learning from multiple components of information. The IIT is based on findings from male offenders presenting high scores on all psychopathic traits. The present study investigated whether IIT predictions of topology abnormalities were associated with psychopathic traits, measured dimensionally, in young adult women with subsyndromal scores.
Seventy-three women, with an average age of 25 years, were assessed using the Psychopathy Checklist-Revised and completed resting-state magnetic resonance imaging. Preprocessed time series from 90 anatomical regions were extracted to form connectivity matrices and used to calculate network topology based on graph theory. Correlations between total psychopathy and factor scores with both the raw connectivity matrix and global and local graph theory measures were computed.
Total psychopathy scores and behavioral factor scores were related to connectivity between several pairs of regions, primarily limbic/paralimbic. Psychopathic traits were not associated with global topology measures. Topology abnormalities, robust across network formation thresholds, were found in nodes of the default mode network and in hubs connecting several resting-state networks.
IIT predictions of abnormal topology of hubs and default mode network nodes with dimensionally measured psychopathic traits were confirmed in a sample of young women. Regional abnormalities, accompanied by preserved global topology, may underlie context-specific abnormal information processing and integration.
人群中的精神病态特征具有维度性，与多种负面结果相关。受损整合理论（IIT）提出，精神病态特征与神经网络拓扑的异常有关，即神经网络的整合受到干扰，导致从信息的多个组成部分快速整合和学习的自我维持障碍。IIT 基于所有精神病态特征得分较高的男性罪犯的研究结果。本研究调查了 IIT 对拓扑异常的预测是否与亚综合征得分的年轻成年女性的精神病态特征维度相关。
73 名女性，平均年龄 25 岁，使用《精神病态检查表修订版》进行评估，并完成静息态磁共振成像。从 90 个解剖区域提取预处理时间序列，以形成连接矩阵，并使用基于图论的方法计算网络拓扑。计算总精神病态和因子得分与原始连接矩阵以及全局和局部图论测量值之间的相关性。
总精神病态评分和行为因子评分与几个区域之间的连接有关，主要是边缘/边缘系统。精神病态特征与全局拓扑测量值无关。在默认模式网络的节点和连接几个静息状态网络的枢纽中发现了拓扑异常，这些异常在网络形成阈值下是稳健的。
在年轻女性样本中，IIT 对维度测量的精神病态特征的异常拓扑的预测得到了确认。伴有全局拓扑保留的区域异常可能是特定于上下文的异常信息处理和整合的基础。
