Peptidergic neurons in error computations and behavioral flexibility

项目概要 在动态环境中生存要求行为具有灵活性和适应性。一个有机体必须 预测哪些行为会导致奖励，计算结果与这些预测的差异（预测 错误），并相应地调整行为策略。神经元编码预测误差可以被发现 在许多与奖赏相关的大脑结构中，腹侧被盖区和外侧缰核的密度最高 （LHb）。转录分析发现，LHb包含一组不同的混合细胞类型，但在 目前，预测错误编码神经元如何映射到转录定义的缰细胞上是未知的 类型因此，我们缺乏一个遗传细胞类型框架来识别和选择性地操纵它们，以更好地 了解他们在行为中的作用。为了满足这一需求，该提案旨在确定Tac1LHb神经元如何 编码奖励参数，在动态环境中调整其响应，并影响行为灵活性。 我们的中心假设是，预测错误触发Tac1LHb神经元的活动，并促进灵活的行为。 在目标1中，我们将使用群体水平和单个单位记录来确定不同的奖励参数 （奖励概率，奖励历史，奖励间隔和奖励大小）调节Tac1LHb活性， 结果。在目标2中，我们将确定Tac1LHb活性的回路和突触水平机制， 随着奖励历史的变化而变化。在目标3中，我们提出在反向学习任务中操纵Tac1LHb活性， 确定它是否是必要的行为灵活性，并测试一个理论模型描述的计算 Tac1LHb活性在决策中的作用Tac1基因编码神经肽P物质， 该提案将确定肽能信号在该回路中突触传递中的作用，以及其 影响行为。完成拟议的研究计划将建立一个细胞类型解决的观点， 错误编码神经元，并证明了Tac1LHb神经元在行为灵活性中的关键作用。赤字 行为灵活性是几种神经精神疾病的标志，包括精神分裂症，多动症，强迫症， 和抑郁症关于细胞类型和功能的联合信息有可能促进新的治疗方法 以治疗这些疾病中的适应不良行为为目标。

PROJECT SUMMARY Survival in dynamic environments demands that behaviors are flexible and adaptive. An organism must make predictions about which actions lead to rewards, calculate how outcomes differ from those predictions (prediction errors), and adapt a behavioral strategy accordingly. Neurons encoding prediction errors can be found throughout many reward-related brain structures, with the highest densities in the VTA and the lateral habenula (LHb). Transcriptional analyses have found the LHb contains a diverse set of intermingled cell types, but at present, it is unknown how prediction error-encoding neurons map onto transcriptionally-defined habenular cell types. Therefore, we lack a genetic cell type framework to identify and selectively manipulate them to better understand their role in behavior. To address this need, this proposal aims to determine how Tac1LHb neurons encode reward parameters, adapt their responses in dynamic environments, and impact behavioral flexibility. Our central hypothesis is that prediction errors trigger activity in Tac1LHb neurons and promote flexible behavior. In Aim 1, we will use population level and single unit recordings to determine how different reward parameters (reward probability, reward history, reward interval, and reward size) modulate Tac1LHb activity at unexpected outcomes. In Aim 2, we will determine the circuit- and synaptic-level mechanisms by which Tac1LHb activity changes with reward history. In Aim 3, we propose to manipulate Tac1LHb activity in a reversal learning task to determine if it is necessary for behavioral flexibility, and to test a theoretical model describing the computational role of Tac1LHb activity in decision-making. The Tac1 gene encodes the neuropeptide Substance P and our proposal will determine the role of peptidergic signaling in synaptic transmission in this circuit, as well as its impact on behavior. Completion of the proposed research program will establish a cell-type resolved view of error-encoding neurons and demonstrate a key role for Tac1LHb neurons in behavioral flexibility. Deficits in behavioral flexibility are a hallmark of several neuropsychiatric disorders, including schizophrenia, ADHD, OCD, and depression. Joint information on cell typology and function has the potential to advance new therapeutic targets to treat maladaptive behavior in these disorders.