Large-scale monitoring of circuits for adaptation and novelty detection in primary visual cortex

项目总结/摘要 在一个充满感官信息的世界里，在静止的情况下过滤掉重复或多余刺激的能力。 保持检测环境变化的能力对生物学的成功至关重要。研究 特征为对重复刺激（适应）的皮层反应降低，对 与这些预期的刺激不同的刺激（新奇感检测）;然而，使 基于它们所经历的上下文对刺激进行灵活编码仍然是未知的。去抑制 微电路，特别是由表达血管活性肠多肽的抑制性中间神经元介导的微电路 （VIP），可能通过改变提供给主要兴奋性神经元的抑制，在这种灵活的编码中发挥作用 （PYRs）在新皮质中。尽管如此，在适应过程中VIP和PYR的神经活动之间的关系， 和新奇检测仍然知之甚少。 在这个建议中，我寻求使用快速双色，三维，双光子钙成像， 在经典视觉过程中同时监测初级视皮层中VIP和PYR神经活动 “古怪”范例（目标1）。这种范式在控制、重复和罕见/偏差方面呈现相同的刺激 上下文，这使得能够直接记录神经反应相同的刺激时，它是一个既定的 规律性和当它是新的，从而偏离既定的规律性。然后我会用数据和理论 分析工具来计算模型新皮层适应和新奇检测（目标2）， 来自PYR和中间神经元群体（包括VIP）的解剖学和神经记录数据，这些数据通常 排除在网络模型之外。这个整体模型的创建可能会揭示基本的电路， 产生对感觉刺激的灵活神经编码。最后，我将整合光遗传学介入工具， 用于双光子成像的电路操作，以直接测试VIP神经活动与 PYR中的适应性和新奇检测。总而言之，这些目标直接解决了BRAIN倡议的几个问题。 2025年高优先级目标：监测神经活动，介入工具，数据和理论分析，以及综合 接近。此外，根据这些目标提出的实验将产生重大的技术和 为申请人提供理论培训，并将促进对兴奋性，抑制性和 跨皮层的去抑制回路在它们的动态神经活动中发散，并且不同地有助于 感觉处理

Project Summary/Abstract In a world filled with sensory information, the ability to filter out repetitive or redundant stimuli while still maintaining the ability to detect change in the environment is critical to biological success. Studies have characterized reduced cortical responses to repetitive stimuli (adaptation) and augmented cortical responses to stimuli that differ from these expected regularities (novelty detection); however, the cortical circuits that enable flexibly encoding stimuli based on the context in which they are experienced remain unknown. Disinhibitory microcircuits, especially those mediated by vasoactive intestinal polypeptide-expressing inhibitory interneurons (VIPs), may play a role in this flexible coding by altering the inhibition supplied to principal excitatory neurons (PYRs) in neocortex. Despite this, the relationship between neural activity of VIPs and PYRs during adaptation and novelty detection remain poorly understood. In this proposal, I seek to use fast dual-color, three-dimensional, two-photon calcium imaging to simultaneously monitor neural activity of both VIPs and PYRs in primary visual cortex during a classic visual “oddball” paradigm (Aim 1). This paradigm presents the same stimulus in control, repetitive, and rare/deviant contexts, which enables directly recording neural responses to the same stimulus when it is an established regularity and when it is novel and thus deviates from established regularity. I will then use data and theory analysis tools to computationally model neocortical adaptation and novelty detection (Aim 2) by incorporating anatomical and neural recording data from PYRs and interneuron populations (including VIPs), which are often excluded from network models. The creation of this holistic model is likely to reveal fundamental circuitry that gives rise to flexible neural encoding of sensory stimuli. Finally, I will integrate optogenetic interventional tools for circuit manipulation with two-photon imaging to directly test the relationship between VIP neural activity and adaptation and novelty detection in PYRs. Altogether, these aims directly address several of the BRAIN Initiative 2025 high priority goals: monitor neural activity, interventional tools, data and theory analysis, and integrated approaches. Furthermore, the experiments proposed under these aims will result in significant technical and theoretical training for the applicant and will advance essential understanding of how excitatory, inhibitory, and disinhibitory circuits across cortical layers diverge in their dynamic neural activity and differentially contribute to sensory processing.