Closed-loop optogenetic control of gamma oscillations and emotional learning

项目摘要 意义重大。了解某些刺激或情况与危险或有益的联系的能力 结果通常是有利的。然而，这样的学习也可能导致自我强化的循环 有害的行为。因此，实现对网络机制的控制将是有用的，该机制规范 习得的情绪行为的获得和表达。这是我们在这里追求的目标。 背景资料。杏仁基底外侧核(BLA)的主要神经元是获得和表达 有条件性的情绪行为。然而，他们中很少有人被情感刺激所激活。 这一悖论的解决之道在于伽马的同步影响。事实上，伽马极大地 增强发射的同步性，放大BLA细胞对目标的影响。然而，它几乎不会改变BLA的解雇 费率。因此，我们将研究增强或抑制血乳酸伽马对情绪学习的影响。为此， 我们将把光遗传学与可编程的多通道信号处理器相结合，这种处理器被称为“现场编程”。 BLOB门阵列“(FGA)。与计算机不同，现场可编程门阵列允许近乎瞬时的信号分析和条件化 光刺激传输，实时提供对伽马等快速神经元事件的前所未有的控制。 接近。表达小白蛋白(PV)的中间神经元在伽马的发生中起着关键作用。因此， 通过注入AAV5-hSyn病毒，将兴奋性视蛋白的表达限制在PV细胞中。 Flex-Chronos-GFP在PV-cre大鼠血中的表达。然后，为了增强或抑制伽马，光基因的激发 光伏电池的时间将分别与其首选或非首选伽马发射阶段一致。 拟议的工作：在目标#1中，我们将确定哪个伽马子带在BLA中表达最强烈 以及与什么事件(条件刺激或反应)有关。我们将记录单位和LFP活动，而大鼠 了解不同的条件刺激可以预测奖励传递(CS-R)或即将到来的足击(CS-S)。我们的 飞行员数据表明，伽马功率的最大变化发生在伽马中带，而中伽马带 伽马与不同的条件反应(CRS)有不同的联系。基于这些结果，在目标2中，我们 将测试在CS-R或CS-S期间增强或抑制血乳酸中伽马是否促进或损害 食欲和防御性CRS的表达。最后，在目标3中，我们将测试是增强还是抑制血乳酸 训练后的伽马有助于或损害食欲和防御性CRS的巩固。事实上，我们 此前发现，在30分钟后的情感唤醒学习体验中，中伽马能量 血乳酸的增加，这种增加的幅度与记忆中的个体差异有关 召回。在AIMS 2-3中，控制组将包括随机组，其中相同的光刺激序列将被 在病毒只会驱动报告表达的情况下，无论正在进行的伽马、无视蛋白组， 和其他频率组来测试我们操作的频率专一性。

Project Summary Significance. The ability to learn that some stimuli or situations are associated with dangerous or rewarding outcomes is generally advantageous. However, such learning can also lead to a self-reinforcing cycle of harmful behaviors. Thus, it would be useful to achieve control over the network mechanisms that regulate the acquisition and expression of learned emotional behaviors. This is the objective we pursue here. Background. Principal basolateral amygdala (BLA) neurons are essential for the acquisition and expression of conditioned emotional behaviors. Yet, remarkably few of them are activated by emotionally-valenced stimuli. The solution to this paradox resides in the synchronizing influence of gamma. Indeed, gamma drastically increases firing synchrony, amplifying the impact of BLA cells on their targets. Yet, it barely alters BLA firing rates. Thus, we will study the impact of boosting or dampening BLA gamma on emotional learning. To this end, we will combine optogenetics with programmable multi-channel signal processors, known as “field programma- ble gate arrays” (FPGAs). Unlike computers, FPGAs allow nearly instantaneous signal analysis and conditional light stimulus delivery, providing unprecedented control over fast neuronal events like gamma, in real time. Approach. Parvalbumin (PV)-expressing interneurons play a critical role in the genesis of gamma. Thus, expression of the excitatory opsin Chronos will be restricted to PV cells, by infusing the virus AAV5-hSyn- FLEX-Chronos-GFP in the BLA of PV-cre rat. Then, to boost or dampen gamma, the optogenetic excitation of PV cells will be timed to coincide with their preferred or non-preferred gamma firing phase, respectively. Proposed work: In Aim #1, we will determine what gamma sub-band is most strongly expressed in the BLA and in relation to what events (conditioned stimuli or responses). We will record unit and LFP activity while rats learn that different conditioned stimuli predict reward delivery (CS-R) or an impending footshock (CS-S). Our pilot data indicates that the largest changes in gamma power occur in the mid-gamma band and that mid- gamma is differentially related to distinct conditioned responses (CRs). Based on these results, in Aim #2, we will test whether enhancing or dampening BLA mid-gamma during the CS-R or CS-S facilitates or impairs the expression of appetitive and defensive CRs. Last, in Aim 3, we will test whether enhancing or dampening BLA gamma after training facilitates or impairs the consolidation of appetitive and defensive CRs. Indeed, we previously found that in the 30 min following an emotionally arousing learning experience, mid-gamma power increases in the BLA and that the magnitude of this increase correlates with individual variations in memory recall. In Aims 2-3, control groups will include random groups where the same trains of light stimuli will be delivered irrespective of ongoing gamma, no-opsin groups where the virus will only drive reporter expression, and other frequency groups to test the frequency specificity of our manipulations.