McGill University School of Medicine, Montreal, QC, Canada.
Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
Mol Psychiatry. 2023 Jun;28(6):2189-2196. doi: 10.1038/s41380-023-02114-y. Epub 2023 Jun 6.
Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. There has been significant progress in the development of tasks and how to model them, presenting an opportunity to incorporate computational psychiatry methodologies into large- scale research projects or into clinical practice. In this viewpoint, we explore some of the barriers to incorporation of computational psychiatry tasks and models into wider mainstream research directions. These barriers include the time required for participants to complete tasks, test-retest reliability, limited ecological validity, as well as practical concerns, such as lack of computational expertise and the expense and large sample sizes traditionally required to validate tasks and models. We then discuss solutions, such as the redesigning of tasks with a view toward feasibility, and the integration of tasks into more ecologically valid and standardized game platforms that can be more easily disseminated. Finally, we provide an example of how one task, the conditioned hallucinations task, might be translated into such a game. It is our hope that interest in the creation of more accessible and feasible computational tasks will help computational methods make more positive impacts on research as well as, eventually, clinical practice.
计算精神病学是一个旨在开发人类大脑信息处理的正式模型的领域，以及这种处理的改变如何导致临床现象。在任务的开发和建模方面已经取得了重大进展，为将计算精神病学方法纳入大规模研究项目或临床实践提供了机会。在这个观点中，我们探讨了将计算精神病学任务和模型纳入更广泛的主流研究方向的一些障碍。这些障碍包括参与者完成任务所需的时间、测试-重测可靠性、有限的生态有效性，以及实际问题，如缺乏计算专业知识以及传统上验证任务和模型所需的费用和大样本量。然后，我们讨论了解决方案，例如重新设计任务以提高可行性，并将任务集成到更具生态有效性和标准化的游戏平台中，以便更轻松地传播。最后，我们提供了一个示例，说明如何将一个任务，即条件性幻觉任务，转化为这样的游戏。我们希望对创建更易于访问和可行的计算任务的兴趣将有助于计算方法对研究，最终对临床实践产生更积极的影响。
