Functional circuitry and computation of the visual thalamus

视觉丘脑的功能电路和计算

• 批准号: 10577537
• 负责人: Liang Liang
• 金额: $ 40.26万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10577537
• 关键词: Address; Animals; Arousal; Axon; Behavior monitoring; Behavioral; Biophysics; Brain; Brain region; Calcium; Calcium Signaling; Chronic; Color; Conscious; Dendrites; Dorsal; Esthesia; Eye; Face; Foundations; Future; Genetic; Goals; Head; Image; Individual; Knowledge; Lateral Geniculate Body; Locomotion; Logic; Mammals; Measures; Mental disorders; Methodology; Methods; Midbrain structure; Modeling; Movement; Mus; Neurons; Pattern Formation; Play; Process; Property; Resolution; Retina; Role; Route; Sensory; Shapes; Signal Transduction; Source; Stream; Synapses; Testing; Thalamic structure; Travel; Vision; Visual; Visual Cortex; Visual Perception; Visual evoked cortical potential; Visuospatial; Work; awake; calcium indicator; experimental study; flexibility; imaging approach; imaging platform; innovation; interest; nervous system disorder; neural; neural circuit; neurodevelopment; novel; optogenetics; preference; receptive field; response; restraint; retinal axon; retinogeniculate; spatial relationship; superior colliculus Corpora quadrigemina; two-photon; visual information; visual processing

PROJECT SUMMARY/ABSTRACT The dorsal lateral geniculate nucleus (dLGN) of the thalamus routes visual signals from the eye to the visual cortex and provides critical support for conscious visual sensation. Rather than being a simple relay station, a growing body of evidence is revealing that the mouse dLGN plays an active role in shaping visual information flow to the cortex by selectively converging and integrating diverse streams of inputs. Studies of retinal inputs to the dLGN have provided rich knowledge about the organization and development of neural circuits for mammalian species. However, much less is known about the non-retinal inputs although they contribute to ~90% of total inputs to the dLGN. How the visual and behavioral state information conveyed by non-retinal inputs combines with information from the retina to impact thalamic visual processing remains a topic of great experimental and theoretical interest. Direct functional characterization of inputs to the dLGN in awake behaving animals has been hindered by the difficulty in performing high-resolution recording of subcortical brain regions. To address this challenge, we established a chronic, high-resolution, deep-brain two-photon calcium imaging platform to simultaneously measure visual responses in hundreds of retinal axonal boutons. Here, we have further expanded our imaging capacity to simultaneously record signals from calcium indicators of two different colors that are expressed in retinal and non-retinal inputs respectively. With these innovations, we will determine how the diverse inputs from the midbrain superior colliculus coordinate with retinal inputs at multiple levels to reinforce or broaden channels of visual information in the dLGN. The highly conserved colliculogeniculate axons possess several synaptic properties that resemble those of retinogeniculate axons, including comingling axonal boutons on the proximal dendrites of dLGN neurons and providing strong synaptic inputs that can elicit neural firing in target neurons. However, it remains unclear how the collicular inputs combine with retinal inputs and contribute to visual responses of dLGN neurons. In Aim 1, we will determine the functional and spatial relationships between retinal and collicular inputs to the dLGN. In Aim 2, we will reveal the modulation of colliculogeniculate inputs by behavioral states. In Aim 3, we will determine the contribution of collicular inputs to visual responses of dLGN neurons. These experiments will reveal rules for functional convergence between retinal and collicular inputs and demonstrate how they act in concert or in competition to sculpt thalamic visual computation. Our findings will also contribute to the understanding of how afferent visual signals are transformed into visual feature selectivity in the dLGN and how behavioral states impact this process, providing the foundation for the understanding and treatment of neurological disorders involving improper neural circuit connectivity and signal integration.

项目摘要/摘要 丘脑背外侧膝状体核(Dlgn)将视觉信号从眼睛传递到视觉。 大脑皮质，并为有意识的视觉感觉提供关键支持。不是简单的中继站，而是一个 越来越多的证据表明，老鼠的dLGN在塑造视觉信息方面发挥着积极的作用 通过选择性地汇聚和整合不同的输入流，流向大脑皮层。视网膜输入到视网膜的研究 DLGN提供了丰富的关于神经回路的组织和发展的知识 哺乳动物物种。然而，对非视网膜输入的了解要少得多，尽管它们占到了~90% 占dlgn总投入的比例。非视网膜输入所传达的视觉和行为状态信息 结合来自视网膜的信息来影响丘脑的视觉处理仍然是一个伟大的主题 实验和理论兴趣。清醒行为中dLGN输入的直接功能表征 动物一直受到对大脑皮质下区域进行高分辨率记录的困难的阻碍。 为了应对这一挑战，我们建立了一种慢性、高分辨率、脑深部双光子钙成像 该平台可同时测量数百个视网膜轴突的视觉反应。在这里，我们有 进一步扩展了我们的成像能力，可以同时记录来自两个不同钙指示剂的信号 分别在视网膜和非视网膜输入中表示的颜色。有了这些创新，我们将确定 来自中脑上丘的不同输入如何与视网膜输入在多个水平上协调 加强或拓宽dlgn中的视觉信息渠道。高度保守的丘状原性轴突 具有几个类似于视网膜生成轴突的突触特性，包括形成轴突 DLGN神经元近端树突上的突触，并提供可诱发神经的强大突触输入 向目标神经元开火。然而，尚不清楚丘状传入如何与视网膜传入结合，以及 对dLGN神经元的视觉反应有贡献。在目标1中，我们将确定功能和空间 视网膜和丘系传入dLGN之间的关系。在目标2中，我们将揭示 通过行为状态使输入产生黑色素生成。在目标3中，我们将确定皮层输入对 DLGN神经元的视觉反应。这些实验将揭示函数收敛的规律 视网膜和丘脑输入，并演示它们如何协调或竞争地塑造丘脑视觉 计算。我们的发现也将有助于理解传入视觉信号是如何转换的 DLGN中的视觉特征选择性以及行为状态如何影响这一过程，为 用于了解和治疗涉及神经回路连接不当的神经疾病和 信号集成。