Group of Cognitive Systems Modeling, Biophysical Section. Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo 11400, Uruguay.
Schizophr Res. 2011 Sep;131(1-3):157-64. doi: 10.1016/j.schres.2011.04.026. Epub 2011 Jun 2.
Several psychiatric and neurological conditions affect the semantic organization and content of a patient's speech. Specifically, the discourse of patients with schizophrenia is frequently characterized as lacking coherence. The evaluation of disturbances in discourse is often used in diagnosis and in assessing treatment efficacy, and is an important factor in prognosis. Measuring these deviations, such as "loss of meaning" and incoherence, is difficult and requires substantial human effort. Computational procedures can be employed to characterize the nature of the anomalies in discourse. We present a set of new tools derived from network theory and information science that may assist in empirical and clinical studies of communication patterns in patients, and provide the foundation for future automatic procedures. First we review information science and complex network approaches to measuring semantic coherence, and then we introduce a representation of discourse that allows for the computation of measures of disorganization. Finally we apply these tools to speech transcriptions from patients and a healthy participant, illustrating the implications and potential of this novel framework.
几种精神和神经病症会影响患者言语的语义组织和内容。具体来说，精神分裂症患者的话语通常表现出缺乏连贯性。话语障碍的评估通常用于诊断和评估治疗效果，也是预后的一个重要因素。衡量这些偏差，如“失去意义”和不连贯，是困难的，需要大量的人力。可以使用计算程序来描述话语异常的性质。我们提出了一组来自网络理论和信息科学的新工具，这些工具可能有助于对患者沟通模式的实证和临床研究，并为未来的自动程序提供基础。首先，我们回顾了信息科学和复杂网络方法来测量语义连贯性，然后我们引入了一种话语表示，允许计算组织混乱的度量。最后，我们将这些工具应用于患者和健康参与者的语音转录，说明了这个新框架的意义和潜力。
