Organization of neural coding and plasticity in L2/3 of mouse S1 cortex

小鼠 S1 皮质 L2/3 的神经编码组织和可塑性

• 批准号: 10653516
• 负责人: Daniel Feldman
• 金额: $ 47.45万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10653516
• 关键词: Anatomy; Attention; Attention deficit hyperactivity disorder; Basic Science; Biological Models; Calcium; Capsicum; Cells; Cerebral cortex; Code; Cues; Data; Detection; Equilibrium; Future; Image; Interneurons; Investigation; Learning; Maps; Measures; Modeling; Mus; Nature; Neighborhoods; Neurodevelopmental Disorder; Neurons; Output; Pattern; Performance; Property; Psychological reinforcement; Pyramidal Cells; Recording of previous events; Rewards; Rodent; Role; Sampling; Sensory; Site; Sodium Chloride; Somatosensory Cortex; Specificity; Stimulus; Structure; Testing; Vibrissae; attentional modulation; autism spectrum disorder; cognitive process; experience; flexibility; improved; neural; neural circuit; novel; optogenetics; response; segregation; selective attention; sensory cortex; two-photon; whisker discrimination

Summary Non-topographic, intermixed representations (salt-and-pepper maps) of sensory information are common in cerebral cortex, but how neural coding and plasticity are organized within them is unclear. We propose that salt-and-pepper maps contain distinct pyramidal (PYR) subnetworks with differential roles in coding stability and flexibility (including learning and attentional modulation). To test this, we study the whisker map in layer 2/3 of mouse somatosensory cortex (S1), where PYR cells tuned for the columnar whisker (CW) and for non- columnar (non-CW) whiskers are intermixed in each column. We recently discovered that non-CW tuned cells show marked tuning instability across days, while CW-tuned cells have stable tuning. This reveals that the L2/3 salt-and-pepper map has two components: a stable columnar map of CW-tuned cells, intermixed with non-CW tuned cells that are unstably tuned and have little columnar topography. We propose that CW- and non-CW tuned cells are distinct PYR subcircuits with different roles in coding and plasticity. This is a novel model of S1 circuit function. We predict that the CW network provides coding stability, while non-CW cells are the primary site for plasticity and learning. Based on preliminary data, we hypothesize that tuning instability in non-CW cells is internally driven, and acts to sample novel sensory codes which may then be stabilized by experience or reward. This is a novel hypothesis for how sensory maps balance stability and plasticity—by segregating these functions in different subcircuits. In Aim 1, we use longitudinal 2-photon calcium imaging to understand the nature and origins of tuning instability, and to test whether experience or reinforcement stabilizes whisker tuning. In Aim 2, we evaluate whether CW and non-CW networks represent distinct functional networks with different sensory coding and plasticity properties. We test our central hypothesis that non-CW cells are the primary locus of sensory plasticity and learning within the map. Aim 3 asks how attention modulates neural coding within intermixed maps. We developed a selective attention task in which mice use history-dependent cues to guide attention to a specific whisker to improve detection performance. Mice show robust spatial attention to cued whiskers. Attention lasts ~10 sec and is driven by recent pairing of whisker stimuli with reward. Preliminary data show that attention enhances whisker-evoked activity of PYR cells encoding the attended whisker in S1. This establishes S1 as a powerful site to study cortical mechanisms of attention. We will use 2-photon imaging and Neuropixels recording to study how attention modulates sensory coding in S1, including measuring the size and CW- or non-CW network specificity of the attentional spotlight. In a major effort, we use imaging and optogenetics to identify the control circuits for attention in S1, with initial focus on VIP interneurons. Together, these studies will reveal how plasticity and attentional modulation are organized within a canonical salt-and-pepper map.

概括 感官信息的非地形、混合表示（椒盐图）常见于 大脑皮层，但神经编码和可塑性在其中的组织方式尚不清楚。 椒盐图包含不同的金字塔 (PYR) 子网络，在编码稳定性方面具有不同的作用 和灵活性（包括学习和注意力调节）为了测试这一点，我们研究了层中的胡须图。 小鼠体感皮层 (S1) 的 2/3，其中 PYR 细胞针对柱状须 (CW) 和非 我们最近发现非 CW 调谐单元中混合有柱状（非 CW）晶须。 在几天内表现出明显的调谐不稳定，而 CW 调谐的细胞具有稳定的调谐。 L2/3 椒盐图有两个组成部分：CW 调谐单元的稳定柱状图，与 非 CW 调谐单元的调谐不稳定且具有很少的柱状形貌。 非 CW 调谐单元是不同的 PYR 子电路，在编码和可塑性方面具有不同的作用。 这是 S1 电路功能的新颖模型，我们预测 CW 网络提供编码稳定性， 根据初步数据，我们勇敢地说，非 CW 细胞是可塑性和学习的主要场所。 非 CW 细胞中的调谐不稳定性是内部驱动的，并且用于采样可能的新颖感觉代码 然后通过经验或奖励来稳定。这是关于感觉图如何平衡稳定性的新颖假设。 和可塑性——通过将这些功能分离在不同的子电路中，在目标 1 中，我们使用纵向 2 光子。 钙成像来了解调谐不稳定性的本质和起源，并测试经验或 在目标 2 中，我们评估 CW 和非 CW 网络是否具有代表性。 我们测试我们的中枢，具有不同的感官编码和可塑性特性。 假设非 CW 细胞是地图内感觉可塑性和学习的主要场所。 目标 3 询问注意力如何调节混合图中的神经编码。我们开发了一种选择性的方法。 注意力任务，其中小鼠使用历史依赖的线索来引导注意力到特定的胡须以提高 小鼠对提示胡须表现出强大的空间注意力，注意力持续约 10 秒。 由最近的胡须刺激与奖励配对驱动，初步数据表明注意力会增强。 胡须诱发的 PYR 细胞编码 S1 中的胡须，这确立了 S1 的强大功能。 我们将使用 2 光子成像和神经像素记录来研究皮质注意力机制。 研究注意力如何调节 S1 中的感觉编码，包括测量大小以及 CW 或非 CW 在一项重大努力中，我们使用成像和光遗传学来识别注意力聚光灯的网络特异性。 S1 中的注意力控制电路，最初关注 VIP 中间神经元。 这些研究将共同​​揭示可塑性和注意力调节是如何在一个 规范的椒盐图。