Brown Postdoctoral Training Program in Computational Psychiatry

了解精神障碍和推进精神治疗的目标需要基本的 不仅知道是什么环境、遗传和表观遗传因素导致了功能和功能障碍， 还有这些因素是如何改变电路级计算的，这些计算是行为的最接近的神经事件。 这一领域研究的出现有望将神经电路的核心计算与复杂性联系起来 人类行为，最终目标是开发全面的、多水平的跨诊断模型 神经精神障碍。因此，新兴的计算精神病学领域是 NIMH任务。尽管它很重要，但在这一领域进行培训的机会很少。 因此，拟议的培训计划寻求接受具有深厚领域背景的新近获得的博士 例如神经科学、工程学、应用数学和计算机科学，并为他们提供工具来 为计算精神病学这一新兴领域做出了重要贡献。拟议的培训计划 计算精神病学(TPCP)将在布朗大学进行，那里有临界质量的基础知识 主校区研究人员和精神病学和人类医学系的临床研究人员 进行这样的训练计划的行为。我们建议招募6名研究员(每年3名)参加TPCP，并 培训更有效率和效力的非临床研究人员的目标是能够与 提高临床研究人员对精神障碍和治疗的认识。该计划包含一个 学徒制模式，在这种模式下，研究员与计算领域的主要研究培训师合作，并 临床精神病学二级研究导师。在这种学徒制模式中，培训师与 这位研究员和一位二级临床精神病学导师正在进行以下领域的研究 神经成像、神经刺激和数字表型。这些研究领域尤其有利于 解决计算精神病学中的重要问题，无论这些问题是模型/理论驱动的还是数据驱动的。 拟议的教学计划将包括核心研讨会和个性化课程，包括 神经科学、计算机科学、工程学、应用数学或精神病学的伙伴选修课 精神错乱。所有研究员都参加了关于拨款撰写、负责任的研究行为以及严谨和 再现性。短期的最终产品是美国国立卫生研究院关于计算精神病学主题的拨款申请。 其长期目标是产生一批能够在计算领域开展研究的新学者 精神病学和培养这一新兴研究领域的下一代研究生。

The goal of understanding psychiatric disorders and advancing psychiatric treatments requires basic knowledge of not only what environmental, genetic and epigenetic factors underlie function and dysfunction, but also how these factors alter the circuit-level computations that are the proximal neural events to behavior. The advent of research in this area holds the promise of linking core computations of neural circuits to complex human behavior, with the ultimate goal of developing comprehensive, multilevel transdiagnostic models of neuropsychiatric disorders. Consequently, the emerging field of computational psychiatry is central to the NIMH mission. Despite its importance, there are very few opportunities to pursue training in this area. Consequently, the proposed training program seeks to take recent PhDs, with strong backgrounds in fields such as neuroscience, engineering, applied math, and computer science, and provide them with the tools to make important contributions to the nascent field of computational psychiatry. The proposed Training Program in Computational Psychiatry (TPCP) will take place at Brown University where there is a critical mass of basic researchers on the main campus and clinical researchers in the Department of Psychiatry and Human Behavior to conduct such a training program. We propose enrolling six fellows (3 per year) in the TPCP with the goal of training, more efficiently and effectively, nonclinical research fellows capable of collaborating with clinical researchers to advance knowledge of psychiatric disorders and treatments. The program embraces an apprenticeship model in which fellows work with a primary research trainer in a computational field and a secondary research mentor in clinical psychiatry. In this apprenticeship model, the trainer works closely with the fellow and a secondary clinical psychiatry mentor, who is conducting research in areas such as neuroimaging, neurostimulation, and digital phenotyping. These research areas are especially conducive to addressing important issues in computational psychiatry, whether they be model/theory-driven or data-driven. The proposed didactic program will include both core seminars and an individualized curriculum including fellow-selected courses in neuroscience, computer science, engineering, applied mathematics, or psychiatric disorders. All fellows attend core seminars on grant writing, responsible conduct of research, and rigor and reproducibility. The short-term final product is an NIH grant application on a computational psychiatry topic. The long-term goal is to produce a new cohort of academics who can conduct research in computational psychiatry and train the next generation of graduate students in this emerging field of inquiry.