Reward Encoding and Anxiety

工程 摘要/摘要 焦虑感 是 一个 大多数精神疾病的衰弱症状，包括创伤后应激障碍，重度抑郁症， 精神分裂症、自闭症和毒瘾。焦虑症的治疗大多局限于苯二氮类药物，它们有 滥用的可能性，并产生多种认知和行为副作用，包括增加 患上痴呆症。替代治疗或预防策略的设计取决于更好的 对焦虑的神经基础的理解。虽然动物研究到目前为止已经告诉我们关于 恐惧和焦虑的功能神经解剖学，现实生活中焦虑的负面影响超出了厌恶 感觉，并涉及持续的目标导向行为的中断。例如，焦虑与 缺乏对奖励驱动行为的灵活控制，以及当受到奖励驱动的行为受到 出现令人厌恶的结果的风险。这些行为缺陷的神经基础在很大程度上是未知的。因此， 推动这一应用程序的实验目标的首要研究问题是：焦虑如何影响 目标导向行为的神经元编码？为了解决这个问题，试验性的一个主要挑战 方法是创造一种背景焦虑状态，不妨碍动物以目标为导向和 在来自多个区域的电生理记录期间奖励任务。考虑到这一点，我们建议 使用两个互补的焦虑症实验模型，结合创新和临床相关 测量奖赏相关两个区域神经元的动态协调时的行为任务 行为的加工和灵活控制：腹侧被盖区(VTA)和背内侧前额叶皮质 (DmPFC)。具体目标是基于计算型模型设计的，其假设是 初步数据支持：(1)行为差异(控制和焦虑状态之间)是特定于 涉及冲突情况下的行动选择或可能出现不良结果的情况；(2)差异 (在控制和焦虑状态之间)在冲突/厌恶结果和 涉及dmPFC中编码动作的神经元的招募减少，以及 DmPFC神经活动和VTA多巴胺神经元。这种方法是新颖而有意义的，因为 对与焦虑等症状相关的异常神经活动的神经计算理解会有所帮助 确定描述这些症状的病因和生理学的生物标志物和临床措施。

PROJECT SUMMARY/ABSTRACT Anxiety is a debilitating symptom of most psychiatric disorders including PTSD, major depression, schizophrenia, autism and addiction. Treatment of anxiety is mostly limited to benzodiazepines, which have abuse potential and produce multiple cognitive and behavioral side effects, including increased propensity to develop dementia. Design of alternative treatments or prevention strategies is contingent upon a better understanding of the neuronal basis of anxiety. While animal studies have so far informed us about the functional neuroanatomy of fear and anxiety, the negative impact of real-life anxiety extends beyond aversive feelings and involves disruptions in ongoing goal-directed behaviors. For example, anxiety is associated with deficits in flexible control of reward-driven actions and expression of motivated behavior when it is subject to the risk of an aversive outcome. The neural basis of these behavioral deficits is largely unknown. Thus, the overarching research question that drives the experimental aims of this application is: How does anxiety affect neuronal encoding of goal-directed behaviors? To address this question, a major challenge of the experimental approach is to create a background state of anxiety that does not prohibit animals to perform goal-oriented and rewarded tasks during electrophysiological recordings from multiple regions. With this in mind, we propose to use two complementary experimental models of anxiety in combination with innovative and clinically relevant behavioral tasks while measuring dynamic coordination between neurons of two regions implicated in reward processing and flexible control of behavior: ventral tegmental area (VTA) and dorsomedial prefrontal cortex (dmPFC). Specific aims are designed based on a computational-style model with assumptions that are supported by preliminary data: (1) behavioral differences (between control and anxiety states) are specific to conditions that involve action selection under conflict or the risk of an aversive outcome; (2) differences (between control and anxiety states) in neuronal activity are observed during conflict/aversive outcomes and involve diminished recruitment of action encoding neurons in dmPFC and disrupted coordination between dmPFC neural activity and VTA dopamine neurons. This approach is novel and significant because a neurocomputational understanding of aberrant neural activity relevant to symptoms such as anxiety can help identify biological markers and clinical measures that delineate etiology and physiology of those symptoms.