EAPSI: Developing a Predictive Model for Compulsive Behavior in Individuals with Obsessive Compulsive Disorder

诊断强迫症（OCD）最常用的方法是耶鲁-布朗量表（Yale-Brown scale），然而该量表只考虑可量化的时间和精力损失，同时也依赖于潜在的错误自我报告。此外，强迫症与其他焦虑症的显著区别在于其存在强迫行为。因此，目前诊断和治疗强迫症的方法不能用它们在治疗其他焦虑症方面的有效性来衡量。这项研究的重点是建立一个基于明斯基的心理社会的强迫行为预测模型。其目的是建立一个模型来预测个体表现出强迫行为的概率。这项研究在理解普遍焦虑和治疗由此产生的身体后果方面都有应用。该项目将在日本京都的京都府立医科大学进行，由Takashi Nakamae博士指导。这次合作提供了独特的数据，使人们能够对强迫行为有新的认识。通过将每个神经系统因子视为一个自动机，它对环境刺激有一定的反应概率并进入兴奋状态，就有可能观察到系统？年代的行为。通过持续应用这一概念，通过忧虑电路的扇区给出代理，设计了一种计算机算法，该算法表明可以使用阈值元胞自动机来预测执行的强迫次数。该模型的后续修订可能会考虑到游戏顺序的概率决定，以及利用已经执行的强迫数量的函数来确定每个代理对刺激做出反应的概率。一种成功的方法必须能够对强迫进行实证量化，但它有可能改善强迫症的治疗方法。此外，通过包含主题的变体？S的平均强迫次数，该模型可以定制，从而提供更个性化的治疗手段。最后，提出的研究对大脑绘图有启示；通过详细研究强迫症的本质，科学家们可能能够分离出焦虑回路的直接功能，这可能为我们了解脑细胞的功能提供线索。该奖项由美国国家科学基金会和日本科学促进会共同资助，隶属于东亚和太平洋暑期研究所项目，支持一名美国研究生进行暑期研究。

The most often used method of diagnosing Obsessive-Compulsive Disorder (OCD) is the Yale-Brown scale, however the scale only considers the quantifiable time and energy lost to compulsions, while also relying on potentially false self-reporting. Furthermore, OCD differs significantly from other anxiety disorders by the existence of compulsive behavior. Therefore, current means of diagnosing and treating OCD cannot be measured by their effectiveness in treating other anxiety disorders. This research is focused on developing a predictive model of compulsive behavior based upon Minsky's Society of Mind. The objective is to develop a model which would predict the probability of an individual performing compulsive behavior. The research has applications both in understanding pervasive anxiety, and in treating the physical consequences therein. This project will be conducted at Kyoto Prefectural University of Medicine in Kyoto, Japan under the mentorship of Dr. Takashi Nakamae. The collaboration provides access to unique data that will enable new insights into compulsive behavior.By considering each neurological agent as an automaton, which has a certain probability of reacting to an environmental stimulus and moving into an excited state, it is possible to observe the system?s behavior. By applying this concept continually, with agents given by the sectors of the worry circuit, a computer algorithm was designed which implied that the number of compulsions performed could be predicted using a threshold cellular automaton. Later revisions of the model may potentially take into consideration probabilistic determination of playing order, as well as utilizing a function of the number of compulsions already performed to determine the probability of each agent reacting to a stimulus. A successful method must be capable of empirically quantifying compulsivity, however it has the potential to improve the therapeutic treatment of OCD. Additionally, by including a variant for the subject?s average number of compulsions, the model may be customized and thus provide a more personal means of treatment. Finally, the proposed research has implications for brain mapping; by detailing the nature of compulsivity, scientists may be able to isolate the direct functions of the worry circuit which could give us clues into brain cell function.This award, under the East Asia and Pacific Summer Institutes program, supports summer research by a U.S. graduate student and is jointly funded by NSF and the Japan Society for the Promotion of Science.