Resilience and Brain Changes in Long-Term Ayahuasca Users: Insights From Psychometric and fMRI Pattern Recognition
Arruda Sanchez, T., Fernandes Jr, O., Rego Ramos, L.
This case-control fMRI study (n=38 males) found that long-term ayahuasca users showed significantly higher psychological resilience scores and altered emotional brain reactivity patterns compared to controls. Machine learning algorithms achieved 75% accuracy in distinguishing users from non-users.
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.