Departamento de Física, Universidad de Buenos Aires and Instituto de Física de Buenos Aires (IFIBA - CONICET), Pabellón I, Ciudad Universitaria (1428), CABA, Buenos Aires, Argentina.
Fundación Para La Lucha Contra Las Enfermedades Neurológicas de La Infancia (FLENI), Montañeses 2325, C1428 CABA, Buenos Aires, Argentina.
Psychopharmacology (Berl). 2022 Sep;239(9):2841-2852. doi: 10.1007/s00213-022-06170-0. Epub 2022 Jun 9.
Serotonergic psychedelics are being studied as novel treatments for mental health disorders and as facilitators of improved well-being, mental function, and creativity. Recent studies have found mixed results concerning the effects of low doses of psychedelics ("microdosing") on these domains. However, microdosing is generally investigated using instruments designed to assess larger doses of psychedelics, which might lack sensitivity and specificity for this purpose.
Determine whether unconstrained speech contains signatures capable of identifying the acute effects of psilocybin microdoses.
Natural speech under psilocybin microdoses (0.5 g of psilocybin mushrooms) was acquired from thirty-four healthy adult volunteers (11 females: 32.09 ± 3.53 years; 23 males: 30.87 ± 4.64 years) following a double-blind and placebo-controlled experimental design with two measurement weeks per participant. On Wednesdays and Fridays of each week, participants consumed either the active dose (psilocybin) or the placebo (edible mushrooms). Features of interest were defined based on variables known to be affected by higher doses: verbosity, semantic variability, and sentiment scores. Machine learning models were used to discriminate between conditions. Classifiers were trained and tested using stratified cross-validation to compute the AUC and p-values.
Except for semantic variability, these metrics presented significant differences between a typical active microdose and the inactive placebo condition. Machine learning classifiers were capable of distinguishing between conditions with high accuracy (AUC [Formula: see text] 0.8).
These results constitute first evidence that low doses of serotonergic psychedelics can be identified from unconstrained natural speech, with potential for widely applicable, affordable, and ecologically valid monitoring of microdosing schedules.
血清素能迷幻剂正被研究作为治疗精神健康障碍的新型治疗方法，以及作为改善幸福感、心理功能和创造力的辅助手段。最近的研究发现，低剂量迷幻剂（“微剂量”）对这些领域的影响结果喜忧参半。然而，微剂量通常使用设计用于评估更大剂量迷幻剂的仪器进行研究，这可能缺乏针对该目的的敏感性和特异性。
确定不受限制的言语是否包含可识别迷幻剂微剂量急性效应的特征。
从 34 名健康成年志愿者（11 名女性：32.09±3.53 岁；23 名男性：30.87±4.64 岁）中获取了在双盲和安慰剂对照实验设计下服用 0.5 克迷幻蘑菇（迷幻蘑菇）后的微剂量下的自然言语（迷幻剂）或安慰剂（食用蘑菇）。根据已知受更高剂量影响的变量，定义了感兴趣的特征：啰嗦、语义变异性和情绪得分。使用机器学习模型来区分条件。使用分层交叉验证来训练和测试分类器，以计算 AUC 和 p 值。
除语义变异性外，这些指标在典型的主动微剂量和非活性安慰剂条件之间存在显著差异。机器学习分类器能够以高准确度区分条件（AUC[公式：见正文]0.8）。
这些结果首次证明，低剂量的血清素能迷幻剂可以从不受限制的自然言语中识别出来，具有广泛适用、经济实惠且生态有效的微剂量方案监测的潜力。
