Serotonergic psychedelics have been suggested to mirror certain aspects of psychosis, and, more generally, elicit a state of consciousness underpinned by increased entropy of on-going neural activity. We investigated the hypothesis that language produced under the effects of lysergic acid diethylamide (LSD) should exhibit increased entropy and reduced semantic coherence. Computational analysis of interviews conducted at two different time points after 75 μg of intravenous LSD verified this prediction. Non-semantic analysis of speech organization revealed increased verbosity and a reduced lexicon, changes that are more similar to those observed during manic psychoses than in schizophrenia, which was confirmed by direct comparison with reference samples. Importantly, features related to language organization allowed machine learning classifiers to identify speech under LSD with accuracy comparable to that obtained by examining semantic content. These results constitute a quantitative and objective characterization of disorganized natural speech as a landmark feature of the psychedelic state.

5-羟色胺能迷幻药被认为可以反映精神病的某些方面，更普遍地说，会引发一种意识状态，这种意识状态是由正在进行的神经活动的熵增加所支撑的。我们研究了在麦角酸二乙胺 (LSD) 的作用下产生的语言应该表现出增加的熵和降低的语义连贯性的假设。在静脉注射 75 微克 LSD 后，在两个不同时间点进行的访谈计算分析证实了这一预测。言语组织的非语义分析显示冗长增加和词汇减少，这些变化与躁狂精神病期间观察到的变化比精神分裂症期间观察到的变化更相似，这通过与参考样本的直接比较得到证实。重要的，与语言组织相关的特征允许机器学习分类器识别 LSD 下的语音，准确度与通过检查语义内容获得的准确度相当。这些结果构成了作为迷幻状态标志性特征的杂乱无章的自然语言的定量和客观表征。