Resilience and Brain Changes in Long-Term Ayahuasca Users: Insights From Psychometric and fMRI Pattern Recognition.

IF 3.5 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Lucas Rego Ramos, Orlando Fernandes, Tiago Arruda Sanchez
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引用次数: 0

Abstract

Background: Ayahuasca is an Amazonian psychedelic brew that contains dimethyltryptamine (DMT) and beta carbolines. Prolonged use has shown changes in cognitive-behavioral tasks, and in humans, there is evidence of changes in cortical thickness and an increase in neuroplasticity factors that could lead to modifications in functional neural circuits.

Purpose: To investigate the long-term effects of Ayahuasca usage through psychometric scales and fMRI data related to emotional processing using artificial intelligence tools.

Study type: Retrospective Cross-sectional, case-control study.

Subjects: 38 healthy male participants (19 long-term Ayahuasca users and 19 non-user controls).

Field strength/sequence: 1.5 Tesla; gradient-echo T2*-weighted echo-planar imaging sequence during an implicit emotion processing task.

Assessment: Participants completed standardized psychometric scales including the Ego Resilience Scale (ER89). During fMRI, participants performed a gender judgment task using faces with neutral or aversive (disgust/fear) expressions. Whole-brain fMRI data were analyzed using multivariate pattern recognition.

Statistical tests: Group comparisons of psychometric scores were performed using Student's t-tests or Mann-Whitney U tests based on normality. Multivariate pattern classification and regression were performed using machine learning algorithms: Multiple Kernel Learning (MKL), Support Vector Machine (SVM), and Gaussian Process Classification/Regression (GPC/GPR), with k-fold cross-validation and permutation testing (n = 100-1000) to assess model significance (α = 0.05).

Results: Ayahuasca users (mean = 43.89; SD = 5.64) showed significantly higher resilience scores compared to controls (mean = 39.05; SD = 5.34). The MKL classifier distinguished users from controls with 75% accuracy (p = 0.005). The GPR model significantly predicted individual resilience scores (r = 0.69).

Data conclusion: Long-term Ayahuasca use may be associated with altered emotional brain reactivity and increased psychological resilience. These findings support a neural patterns consistent with long-term adaptations of Ayahuasca detectable via fMRI and machine learning-based pattern analysis.

Evidence level: 4.

Technical efficacy: Stage 1.

长期死藤水使用者的恢复力和大脑变化:来自心理测量和功能磁共振成像模式识别的见解。
背景:死藤水是一种亚马逊地区的迷幻饮料,含有二甲基色胺(DMT)和-碳碱。长期使用大麻会改变认知行为任务,在人类中,有证据表明皮质厚度的变化和神经可塑性因素的增加可能导致功能性神经回路的改变。目的:利用人工智能工具,通过心理测量量表和与情绪处理相关的功能磁共振成像数据,探讨死藤水使用的长期影响。研究类型:回顾性横断面病例对照研究。受试者:38名健康男性参与者(19名长期死藤水使用者和19名非使用者对照)。场强/序列:1.5特斯拉;内隐情绪处理任务中的梯度-回波T2*加权回波平面成像序列。评估:参与者完成标准化心理测量量表,包括自我弹性量表(ER89)。在fMRI期间,参与者使用中性或厌恶(厌恶/恐惧)表情的面孔进行性别判断任务。全脑功能磁共振成像数据分析使用多元模式识别。统计检验:心理测量分数的组间比较采用基于正态性的学生t检验或Mann-Whitney U检验。采用多核学习(MKL)、支持向量机(SVM)和高斯过程分类/回归(GPC/GPR)等机器学习算法进行多元模式分类和回归,并采用k-fold交叉验证和置换检验(n = 100-1000)评估模型显著性(α = 0.05)。结果:死藤水服用者(平均43.89,SD = 5.64)的恢复力得分显著高于对照组(平均39.05,SD = 5.34)。MKL分类器区分用户和对照组的准确率为75% (p = 0.005)。GPR模型显著预测个体弹性得分(r = 0.69)。数据结论:长期使用死藤水可能与改变大脑的情绪反应和增加心理弹性有关。这些发现支持通过功能磁共振成像和基于机器学习的模式分析检测到的与死藤水长期适应一致的神经模式。证据等级:4。技术功效:第一阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.70
自引率
6.80%
发文量
494
审稿时长
2 months
期刊介绍: The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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