Aggressive behaviours associated with MDMA and psychedelics: a narrative review.

Objective: Monoamine neurotransmitters play a role in aggression, especially when altered by illicit substances. However, some literature suggests that not all illicit substances may lead to aggression, notably psychedelics. This narrative review investigates the associations between serotonergic psychedelics and MDMA on aggressive behaviour.

AI in Surgical Curriculum Design and Unintended Outcomes for Technical Competencies in Simulation Training.

Importance: To better elucidate the role of artificial intelligence (AI) in surgical skills training requires investigations in the potential existence of a hidden curriculum.

Objective: To assess the pedagogical value of AI-selected technical competencies and their extended effects in surgical simulation training.

Design, Setting, And Participants: This cohort study was a follow-up of a randomized clinical trial conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre at the Montreal Neurological Institute, McGill University, Montreal, Canada.

Psilocybin for treatment-resistant depression without psychedelic effects: study protocol for a 4-week, double-blind, proof-of-concept randomised controlled trial.

Background: Randomised controlled trials (RCTs) of psilocybin have reported large antidepressant effects in adults with major depressive disorder and treatment-resistant depression (TRD). Given psilocybin's psychedelic effects, all published studies have included psychological support. These effects depend on serotonin 2A (5-HT2A) receptor activation, which can be blocked by 5-HT2A receptor antagonists like ketanserin or risperidone.

Performance in a Simulated Virtual Reality Anterior Cervical Discectomy and Fusion Task: Disc Residual, Rate of Removal, and Efficiency Analyses.

Background And Objectives: Anterior cervical discectomy and fusion (ACDF) is among the most common spine procedures. The Sim-Ortho virtual reality simulator platform contains a validated ACDF simulated task for performance assessment. This study aims to develop a methodology to extract three-dimensional data and reconstruct and quantitate specific simulated disc tissues to generate novel metrics to analyze performance metrics of skilled and less skilled participants.

Serotonergic psychedelics for depression: What do we know about neurobiological mechanisms of action?

Introduction: Current treatment options for major depressive disorder (MDD) have limited efficacy and are associated with adverse effects. Recent studies investigating the antidepressant effect of serotonergic psychedelics-also known as classic psychedelics-have promising preliminary results with large effect sizes. In this context, we conducted a review of the putative neurobiological underpinnings of the mechanism of antidepressant action of these drugs.

Therapeutic uses of psychedelics for eating disorders and body dysmorphic disorder.

Background: Clinical use of psychedelics has gained considerable attention, with promising benefits across a range of mental disorders. Current pharmacological and psychotherapeutic treatments for body dysmorphic disorder (BDD) and eating disorders (EDs) have limited efficacy. As such, other treatment options such as psychedelic-assisted therapies are being explored in these clinical groups.

A Critical Appraisal of Evidence on the Efficacy and Safety of Serotonergic Psychedelic Drugs as Emerging Antidepressants: Mind the Evidence Gap.

Purpose/background: There has been resurgence of interest in the therapeutic use of serotonergic ("classic") psychedelics in major depressive disorder (MDD) and end-of-life distress. This commentary offers a critical appraisal of current evidence for antidepressant effects of classic psychedelics from contemporary clinical trials and highlights pitfalls that should be addressed before clinical translation.

Methods/procedures: A narrative review was conducted to identify clinical trials of serotonergic psychedelics for the treatment of MDD and end-of-life distress.

Artificial Neural Network Approach to Competency-Based Training Using a Virtual Reality Neurosurgical Simulation.

Background: The methodology of assessment and training of surgical skills is evolving to deal with the emergence of competency-based training. Artificial neural networks (ANNs), a branch of artificial intelligence, can use newly generated metrics not only for assessment performance but also to quantitate individual metric importance and provide new insights into surgical expertise.

Objective: To outline the educational utility of using an ANN in the assessment and quantitation of surgical expertise.

Nondominant Hand Skills Spatial and Psychomotor Analysis During a Complex Virtual Reality Neurosurgical Task-A Case Series Study.

Background: Virtual reality surgical simulators provide detailed psychomotor performance data, allowing qualitative and quantitative assessment of hand function. The nondominant hand plays an essential role in neurosurgery in exposing the operative area, assisting the dominant hand to optimize task execution, and hemostasis. Outlining expert-level nondominant hand skills may be critical to understand surgical expertise and aid learner training.

Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation.

In procedural-based medicine, the technical ability can be a critical determinant of patient outcomes. Psychomotor performance occurs in real-time, hence a continuous assessment is necessary to provide action-oriented feedback and error avoidance guidance. We outline a deep learning application, the Intelligent Continuous Expertise Monitoring System (ICEMS), to assess surgical bimanual performance at 0.

Effect of Artificial Intelligence Tutoring vs Expert Instruction on Learning Simulated Surgical Skills Among Medical Students: A Randomized Clinical Trial.

Importance: To better understand the emerging role of artificial intelligence (AI) in surgical training, efficacy of AI tutoring systems, such as the Virtual Operative Assistant (VOA), must be tested and compared with conventional approaches.

Objective: To determine how VOA and remote expert instruction compare in learners' skill acquisition, affective, and cognitive outcomes during surgical simulation training.

Design, Setting, And Participants: This instructor-blinded randomized clinical trial included medical students (undergraduate years 0-2) from 4 institutions in Canada during a single simulation training at McGill Neurosurgical Simulation and Artificial Intelligence Learning Centre, Montreal, Canada.

Assessment of learning curves on a simulated neurosurgical task using metrics selected by artificial intelligence.

Objective: Understanding the variation of learning curves of experts and trainees for a given surgical procedure is important in implementing formative learning paradigms to accelerate mastery. The study objectives were to use artificial intelligence (AI)-derived metrics to determine the learning curves of participants in 4 groups with different expertise levels who performed a series of identical virtual reality (VR) subpial resection tasks and to identify learning curve differences among the 4 groups.

Methods: A total of 50 individuals participated, 14 neurosurgeons, 4 neurosurgical fellows and 10 senior residents (seniors), 10 junior residents (juniors), and 12 medical students.

Utilizing a multilayer perceptron artificial neural network to assess a virtual reality surgical procedure.

Background: Virtual reality surgical simulators are a safe and efficient technology for the assessment and training of surgical skills. Simulators allow trainees to improve specific surgical techniques in risk-free environments. Recently, machine learning has been coupled to simulators to classify performance.

Virtual Reality Anterior Cervical Discectomy and Fusion Simulation on the Novel Sim-Ortho Platform: Validation Studies.

Background: Virtual reality spine simulators are emerging as potential educational tools to assess and train surgical procedures in safe environments. Analysis of validity is important in determining the educational utility of these systems.

Objective: To assess face, content, and construct validity of a C4-C5 anterior cervical discectomy and fusion simulation on the Sim-Ortho virtual reality platform, developed by OSSimTechTM (Montreal, Canada) and the AO Foundation (Davos, Switzerland).

The Virtual Operative Assistant: An explainable artificial intelligence tool for simulation-based training in surgery and medicine.

Simulation-based training is increasingly being used for assessment and training of psychomotor skills involved in medicine. The application of artificial intelligence and machine learning technologies has provided new methodologies to utilize large amounts of data for educational purposes. A significant criticism of the use of artificial intelligence in education has been a lack of transparency in the algorithms' decision-making processes.

Artificial Neural Networks to Assess Virtual Reality Anterior Cervical Discectomy Performance.

Background: Virtual reality surgical simulators provide a safe environment for trainees to practice specific surgical scenarios and allow for self-guided learning. Artificial intelligence technology, including artificial neural networks, offers the potential to manipulate large datasets from simulators to gain insight into the importance of specific performance metrics during simulated operative tasks.

Objective: To distinguish performance in a virtual reality-simulated anterior cervical discectomy scenario, uncover novel performance metrics, and gain insight into the relative importance of each metric using artificial neural networks.

Artificial Intelligence Distinguishes Surgical Training Levels in a Virtual Reality Spinal Task.

Background: With the emergence of competency-based training, the current evaluation scheme of surgical skills is evolving to include newer methods of assessment and training. Artificial intelligence through machine learning algorithms can utilize extensive data sets to analyze operator performance. This study aimed to address 3 questions: (1) Can artificial intelligence uncover novel metrics of surgical performance? (2) Can support vector machine algorithms be trained to differentiate "senior" and "junior" participants who are executing a virtual reality hemilaminectomy? (3) Can other algorithms achieve a good classification performance?

Methods: Participants from 4 Canadian universities were divided into 2 groups according to their training level (senior and junior) and were asked to perform a virtual reality hemilaminectomy.

Machine Learning Identification of Surgical and Operative Factors Associated With Surgical Expertise in Virtual Reality Simulation.

Importance: Despite advances in the assessment of technical skills in surgery, a clear understanding of the composites of technical expertise is lacking. Surgical simulation allows for the quantitation of psychomotor skills, generating data sets that can be analyzed using machine learning algorithms.

Objective: To identify surgical and operative factors selected by a machine learning algorithm to accurately classify participants by level of expertise in a virtual reality surgical procedure.

Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

Objective: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analyzed with machine learning algorithms. These advancements may increase the understanding, assessment and training of psychomotor performance. Consequently, the application of machine learning techniques to evaluate performance on virtual reality simulators has led to an increase in the volume and complexity of publications which bridge the fields of computer science, medicine, and education.

Is Virtual Reality Surgical Performance Influenced by Force Feedback Device Utilized?

Objective: The study objectives were to assess if surgical performance and subjective assessment of a virtual reality simulator platform was influenced by changing force feedback devices.

Design: Participants used the NeuroVR (formerly NeuroTouch) simulator to perform 5 practice scenarios and a realistic scenario involving subpial resection of a virtual reality brain tumor with simulated bleeding. The influence of force feedback was assessed by utilizing the Omni and Entact haptic systems.