Multipopulation voltage imaging for network insights in temporal lobe epilepsy

项目摘要 海马是内侧颞叶癫痫（TLE）的关键结构，由不同的神经元组成。 细胞类型和子电路。这些电路元件如何工作以及重要的是它们如何相互作用可以提供 癫痫的关键见解，包括发作。癫痫被认为是一种“网络障碍”;正确的 了解癫痫中的网络相互作用对于全面了解这种疾病至关重要， 从而开发新的治疗选择。一套新的电压指示器允许无与伦比的 并同时研究这些电路元件。因此，我们将把这些先进的方法应用于 在清醒的慢性癫痫动物体内，使我们能够回答目前无法解决的问题， 其他方法-检查特征，包括阈下膜电位变化和分辨 即使在高水平活动期间也会出现个别尖峰。使用慢性TLE小鼠模型，我们将在 在发作间期、发作前期和整个发作期间，无明显癫痫样活动的时期 活动，以及发作后时期-为我们提供了一个完整的图片活动模式在不同的发作期 states.在这项初步工作中，我们专注于投射到内侧前额叶皮层的CA 1锥体神经元 (PC投射到内侧内嗅皮层（PC-12 MEC）的CA 1锥体神经元，以及 抑制性神经元，具体包括PV神经元。选择这些电路元件是因为它们的已知特性。 不同的互动。具体地说，前额叶皮层mPFC为PV神经元提供了强兴奋， PV神经元的抑制。相反地，PC CAMMEC接受来自局部PV神经元的强烈抑制，但提供了 PV神经元的兴奋相对有限。因此，我们将能够第一次研究这些问题， 电路元件的活动模式在体内相互关联，以及在癫痫动物中如何变化。 发作谱我们预测PV中间神经元的活动将与PC的PCAMMEC减少有关，但与此无关。 无癫痫样发作状态下的PC和mPFC锥体神经元活动。在发作间期的峰电位，我们假设， 中间神经元广泛地被激活，抑制将限制两个锥体细胞群中活性， 神经元在这些事件中。我们进一步预测，与发作间期尖峰不同，在发作事件期间， 抑制性神经元放电将不足以抑制锥体细胞，并且它们将甚至更早地参与 在电图癫痫发作期间。随着持续的发作活动，我们假设会有进一步的 由于PV细胞（但不是其他中间神经元）中的去极化阻滞，抑制性约束被破坏，导致 进一步增加活动，特别是在PC MEMMEC神经元。如果我们的假设是错误的， 关于慢性癫痫中这些神经元群体活动模式的有价值的信息。此外，本发明的目的是， 这代表了用我们的数据集和这些数据的未来应用可检验的假设的一小部分。 癫痫的治疗方法我们致力于确保癫痫社区能够实施 这些方法可以解决广泛的重要问题。

PROJECT ABSTRACT The hippocampus is a critical structure in mesial temporal lobe epilepsy (TLE), and is comprised of different cell types and subcircuits. How these circuit elements behave and importantly how they interact may provide key insights into epilepsy, including ictogenesis. Epilepsy is recognized as a “network disorder”; a proper understanding of network interactions in epilepsy is crucial to a full understanding of the disorder and consequently the development of novel treatment options. A new suite of voltage indicators allows unparalleled and simultaneous investigation of such circuit elements. We will therefore apply these cutting-edge methods in vivo, in awake, chronically epileptic animals, allowing us to answer questions not currently addressable with other methods – examining features including subthreshold membrane potential changes and resolving individual spikes even during high levels of activity. Using a mouse model of chronic TLE, we will image during periods free of overt epileptiform activity, during interictal spikes, during preictal periods, and throughout ictal activity, as well as postictal periods – providing us will a full picture of activity patterns across different ictal states. In this initial work, we focus on CA1 pyramidal neurons that project to the medial prefrontal cortex (PCmPFC) and CA1 pyramidal neurons that project to the medial entorhinal cortex (PCMEC), in addition to inhibitory neurons, including PV neurons specifically. These circuit elements were chosen due to their known and distinct interactions. Specifically, PCmPFC provide strong excitation to local PV neurons, but receive little inhibition from PV neurons. Conversely, PCMEC receive strong inhibition from local PV neurons but provide relatively limited excitation to PV neurons. We will therefore be able to examine, for the first time, how these circuit elements’ activity patterns relate to one another in vivo and how this changes in epileptic animals across the ictal spectrum. We predict that PV interneurons’ activity will be associated with reduced PCMEC but not PCmPFC pyramidal neuron activity in epileptiform-free states. During interictal spiking, we hypothesize that interneurons broadly are activated and that inhibition will constrain activity in both populations of pyramidal neurons during these events. We further predict that, unlike during interictal spikes, during ictal events, inhibitory neuronal firing will not be sufficient to restrain pyramidal cells, and they will be engaged even early during electrographic seizures. With continued ictal activity, we hypothesize that there will be a further breakdown in inhibitory restraint due to depolarization block in PV cells (but not other interneurons), resulting in a further increase in activity specifically in PCMEC neurons. If our hypotheses are incorrect, we gain equally valuable information about the activity patterns of these neuronal populations in chronic epilepsy. Additionally, this represents a fraction of the hypotheses testable with our data set and with future application of these methods to questions in epilepsy. We are committed to ensuring that the epilepsy community can implement these methods to address a wide range of important questions.