Psychobiology of Suicidal Behavior in Borderline Personality Disorder

这一相互竞争的继续方案扩展和深化了一项富有成效的纵向研究计划 303例有前瞻性自杀倾向的边缘型人格障碍患者的自杀行为 被确定为严重自杀未遂的高风险。我们在2017-22年度的研究重点是从 自杀行为的人际体验，整合三个时间尺度：自杀的自然主义预测 多年来的行为；几天后自杀念头的预测；以及对决定的实验性询问 在几分钟内完成处理。综上所述，我们的研究结果表明，自杀念头的出现 人与人之间的冲突是由内化的精神病理学催化的，而向自杀行为的转变 是通过在决策中外化精神病理学和神经行为改变来促进的。在基础上建设 在这项工作中，我们建议(1)检查导致失代偿的人际特征和特定方面 在几年的时间范围内促进自杀过程中的过渡，(2)提高个体化 在几小时到几天的时间尺度上预测情绪失调和自杀念头，以及(3)提前 在几分钟的时间范围内，对危机中失败的解决方案的搜索的神经计算描述。为 作为一种典型的人格障碍，我们保留了对bpd的历史关注，但我们也强调 多个潜在内化和外化维度对自杀者的可分离贡献 进程。我们的团队在自杀研究方面有互补的专业知识(东布罗夫斯基，派)，边缘人格 和经验抽样(联合调查员Hallquist和Wright，以及顾问Pilkonis)，决定 神经科学(Dombrovski和Hallquist)和包括机器学习在内的定量方法(Hallquist和 莱特，顾问雅各布森现在加入)。我们于2017年开始领导这项研究，促进招聘，以及 与2012-17年度相比，出版物数量翻了两番。拟议的创新包括专注于 人际关系特征的临床突出方面，密集和扩展的EMA与被动感知的整合， 原计算型支持下高认知负荷下的动态决策研究 模型，以及最近开发和验证的用于功能磁共振分析的多水平方法。临床上，理解 人际特质因素对自杀的影响及自杀风险个性化模型的构建 推进自杀预测和及时干预措施的发展。预期结果将推动 自杀过程概念模型与层次化维度的统一 精神病理学模型，识别一般自杀过程与个人特有的自杀过程，并阐明 认知需求下的决策是自杀危机的代表。与NIMH的情况一致 优先研究自杀的议程，这项工作将解决自杀风险的机制，同时调查 RDoC的强化学习和有限能力结构，从而将RDoC与层次化连接起来 精神病理学的维度模型。

This competing continuation proposal extends and deepens a productive program of longitudinal research on suicidal behavior in a cohort of 303 people with borderline personality disorder (BPD) with a prospectively ascertained high risk for serious suicide attempts. Our studies in 2017-22 focused on the pathway from interpersonal experiences to suicidal behavior, integrating three timescales: naturalistic prediction of suicidal behavior over years; prediction of suicidal ideation over days; and experimental interrogation of decision processes over minutes. Taken together, our findings show that the emergence of suicidal ideation from interpersonal conflict is catalyzed by internalizing psychopathology, whereas the transition to suicidal behavior is facilitated by externalizing psychopathology and neurobehavioral alterations in decision-making. Building on this work, we propose to (1) examine interpersonal traits and specific facets that cause decompensation in BPD and facilitate transitions in the suicidal process on a timescale of years, (2) improve individualized prediction of emotion dysregulation and suicidal thoughts on a timescale of hours to days, and (3) advance a neurocomputational account of the failed search for solutions in a crisis on a timescale of minutes. For continuity, we retain the historic focus on BPD as a prototypical personality disorder, yet we also emphasize dissociable contributions of multiple underlying internalizing and externalizing dimensions to the suicidal process. Our team has complementary expertise in suicide research (Dombrovski, PI), borderline personality and experience sampling (co-investigators Hallquist and Wright, and consultant Pilkonis), decision neuroscience (Dombrovski and Hallquist), and quantitative methods including machine learning (Hallquist and Wright, with consultant Jacobson joining now). We began leading the study in 2017, boosting recruitment, and quadrupling the number of publications compared to 2012-17. Proposed innovations include a focus on clinically salient facets of interpersonal traits, integration of intensive and extended EMA with passive sensing, an investigation of dynamic decision-making under high cognitive load supported by an original computational model, and a recently developed and validated multi-level approach to fMRI analysis. Clinically, understanding the suicidogenic effects of interpersonal trait facets and elaboration of personalized models of suicide risk will advance suicide prediction and development of just-in-time interventions. Expected results will advance the field of suicide research by unifying conceptual models of the suicidal process with hierarchical dimensional models of psychopathology, identifying general vs. person-specific suicidogenic processes, and elucidating decision-making under cognitive demands representative of the suicidal crisis. In line with the NIMH’s prioritized research agenda on suicide, this work will address mechanisms of suicide risk, while investigating RDoC’s reinforcement learning and limited capacity constructs and thus bridging RDoC with hierarchical dimensional models of psychopathology.