Positive and Negative Valence Systems Underlying Suicide in Youth

项目总结/摘要 自杀是青少年的一个主要公共卫生问题，也是该年龄组的第二大死亡原因， 强调有必要调查青少年自杀问题。两个最突出的风险因素， 青少年自杀是过去自杀企图和抑郁发作的诊断，每一个独立 自杀未遂的风险会增加10到30倍然而，尽管超过80%的自杀青年 在尝试时出现抑郁症状，只有30%的抑郁青年会尝试 自杀这些数据表明，有自杀企图的抑郁青少年代表了一种独特的 神经生物学亚组然而，目前，我们还没有生物标志物来识别那些抑郁的年轻人， 会有自杀行为这项建议解决了这一关切。我们提出的模型是：（1）快感缺乏是 与抑郁青年自杀风险增加有关;（2）积极效价（PVS）缺陷（奖励 期望、成绩、正预测误差）和负效价（NVS）多动（负预测 错误，疼痛回避）有助于快感缺失和自杀行为的抑郁青年;（3） 缰核（Hb）是一个小的边缘中枢，通过抑制奖赏信号在PVS/NVS过程中起着关键作用。 对疼痛和损失的反应;（4）高分辨率MRI的最新进展解决了先前的技术限制， 研究像血红蛋白这样的小结构。这些进展现在使我们能够研究潜在的神经回路 神经解剖学严格框架中的PVS和NVS。为了支持，我们记录了青少年 抑郁症的核心症状，只有快感缺乏，而不是易怒，与抑郁症中的自杀行为有关。 青年同样，我们发现快感缺乏和诱捕都与自杀倾向独立相关 有自杀倾向的住院病人我们还开发了奖励侧翼（RFT）和奖励预测 错误（RPET）功能磁共振成像任务和确定的大脑功能，在奖励预期，实现，积极和 负预测误差。值得注意的是，RPET和热痛任务引起可测量的Hb激活。 此外，利用优化的分割和播种方法，我们映射了Hb内在功能， 在成年人和有精神症状的青少年中的连接性。在我们工作的基础上，我们提出了一个紧密的 一项综合性研究，以检验PVS缺陷和NVS活动过度是自杀原因的总体假设 抑郁青年的行为我们将研究30名有自杀倾向和30名无自杀倾向的抑郁青少年，年龄在12-17岁， 年龄、性别和利手相匹配的组。所有人都将进行全面的临床评估（诊断， 行为测量，计算机化奖励任务）。神经影像学研究将包括结构MRI、静息状态 和任务fMRI（RFT，RPET，热痛）。机器学习算法将用于检查哪些PVS/NVS 抑郁青年自杀行为的预测过程。

PROJECT SUMMARY/ABSTRACT Suicide is a major public health concern in adolescents and the second leading cause of death in this age group, highlighting the need to investigate suicide in adolescents. The two most prominent risk factors for completed suicide in youth are a past suicide attempt and a diagnosis of a depressive episode, each independently representing a 10- to 30-fold increased risk for completed suicide. However, while over 80% of suicidal youth present with depressive symptoms at the time of the attempt, only 30% of depressed youth will ever attempt suicide. These data suggest that depressed adolescents with prior suicide attempts represent a distinct neurobiological subgroup. However, at present, we have no biomarkers to identify those depressed youth who will engage in suicidal behavior. This proposal addresses this concern. Our proposed model is: (1) anhedonia is associated with heightened suicidal risk in depressed youth; (2) both positive valence (PVS) deficits (reward expectancy, attainment, positive prediction error) and negative valence (NVS) hyperactivity (negative prediction error, pain avoidance) contribute to anhedonia and underlie suicidal behavior in depressed youth; (3) the habenula (Hb), a small limbic hub, plays a key role in PVS/NVS processes by inhibiting reward signaling in response to pain and loss; and (4) recent advances in high-resolution MRI address prior technical constraints in studying small structures such as the Hb. These advances now allow us to study the neuronal circuitry underlying PVS and NVS in a neuroanatomically rigorous framework. In support, we documented that of adolescent depression’s core symptoms, only anhedonia, not irritability, was associated with suicidality among depressed youth. Similarly, we found that both anhedonia and entrapment were independently associated with suicidality in acutely suicidal hospitalized individuals. We also developed the reward flanker (RFT) and reward prediction error (RPET) fMRI tasks and identified brain function during reward anticipation, attainment, and positive and negative prediction errors. Notably, both RPET and a thermal pain task elicited measurable Hb activation. Additionally, utilizing an optimized segmentation and seeding approach, we mapped Hb intrinsic functional connectivity in adults and in adolescents with psychiatric symptoms. Building upon our work, we propose a tightly integrative study to test the overall hypothesis that both PVS deficiency and NVS hyperactivity underlie suicidal behavior in depressed youth. We will study 30 suicidal and 30 non-suicidal depressed adolescents, ages 12-17, group matched for age, sex, and handedness. All will have comprehensive clinical evaluations (diagnoses, behavioral measures, computerized reward task). Neuroimaging studies will include structural MRI, resting-state and task fMRI (RFT, RPET, thermal pain). Machine learning algorithms will be used to examine which PVS/NVS processes predict suicidal behavior in depressed youth.