Traveling waves in neocortical circuits: Mechanisms, computational roles in sensory processing, and impact on sensory perception

项目摘要/摘要 神经科学研究的一个重要的长期目标是了解大尺度的时空 大脑中出现的神经活动模式以及它们是否对塑造大脑的 计算过程，从而哺乳动物的行为。值得注意的是，神经活动的行波具有 与感觉、认知和运动行为有关，这个团队最近发现内在旅行 视觉皮层区域的波(ITW)预测诱发的尖峰活动和视觉知觉的大小 非人类灵长类动物清醒时的敏感度。然而，目前尚不清楚iTW是否反映了 皮层功能的潜在基本机制，或者它们是否可能仅仅是表面现象。 这个项目将研究新皮质iTW在视觉感知中的作用，并由一个理论模型指导。 ITW活动的一部分，该活动对导致 ITW的时空特征及其在感觉行为中的作用。这个模型是基于一个尖峰网络。 神经元，并预测iTW从水平皮质纤维的解剖组织中产生并导致 在以波的形式传播的兴奋性(E)和抑制性(I)群体活动的平衡变化中，该模型 进一步预测，iTW在视觉皮质区域之间在视网膜上是协调的，这种协调 是iTW改善知觉的机制。然而，这些预测可能是错误的。经验主义 对模型预测的测试将需要对特定神经元类型的活动进行测量，覆盖广泛的领域- 在清醒行为的动物身上，具有极佳的空间和时间分辨率。 为了进行这样的测量，该团队最近发明了几项新技术：(1)基因编码 荧光电压指示器(GEVI)，它们将针对特定的E或I神经群体；(2)定制的 双色荧光介镜追踪2种神经元亚阈值电压动态的研究 一次，横跨8毫米视野，横跨绒猴和小鼠皮质的多个皮质区域；(3) 透明电极阵列，允许同时在大脑皮层进行LFP测量 用电压成像研究E和I布居活度；(4)透明层状电极阵列测量 跨越不同皮质层的细胞的尖峰活动。通过结合使用这四项创新，在 在猴子和老鼠执行视觉检测任务时，研究小组将测试理论模型的预测 并了解不同的皮质神经元类型如何影响ITW的动力学和知觉敏感性。 目的1验证E/I群体活动在小鼠和绒猴体内以iTW形式传播的假设。AIM 2测试 ITW在大脑皮层区域的视网膜定位协调的预测，以及这种协调增强 感知敏感度。目标3将从理论上解释目标1和目标2的结果 接地尖峰网络模型。总体而言，通过使用创新的新技术，这个跨学科团队将 提供对大脑研究具有深远重要性的长期概念问题的关键见解。

PROJECT SUMMARY/ABSTRACT An important longstanding goal in neuroscience research is to understand how large-scale spatiotemporal patterns of neural activity emerge in the brain and whether they have a direct role in shaping the brain’s computational processes and thereby mammalian behavior. Notably, traveling waves of neural activity have been implicated in sensory, cognitive, and motor behaviors, and this team recently found that intrinsic traveling waves (iTWs) in visual cortical areas predict the magnitude of evoked spiking activity and visual perceptual sensitivity in awake, behaving non-human primates. However, it remains unclear whether iTWs reflect an underlying fundamental mechanism of cortical function or whether they might simply be epiphenomenal. This project will examine the role of neocortical iTWs in visual perception and is guided by a theoretical model of iTW activity that makes specific testable and falsifiable predictions about the mechanisms that give rise to the spatiotemporal features of iTWs and their roles in sensory behavior. The model is based on a network of spiking neurons and predicts that iTWs emerge from the anatomical organization of horizontal cortical fibers and result in shifts in the balance of excitatory (E) and inhibitory (I) population activity that travel as waves, The model further predicts that iTWs are retinotopically coordinated across visual cortical areas, and that this coordination is the mechanism by which iTWs improve perception. However, these predictions could be wrong. Empirical tests of the model’s predictions will require activity measurements from specific neuron-types, across wide fields- of-view, and with excellent spatial and temporal resolution in awake behaving animals. To perform such measurements, the team recently invented several new technologies: (1) genetically encoded fluorescent voltage indicators (GEVIs) that they will target to specific E or I neural populations; (2) a custom-built dual-color fluorescence mesoscope to track the subthreshold population voltage dynamics of 2 neuron-types at once, across a 8-mm field-of-view spanning multiple cortical areas in marmoset and mouse cortex; (3) transparent electrode arrays that allow measurements of LFPs to be performed across the cortex concurrently with voltage imaging studies of E and I population activity; (4) transparent laminar electrode arrays to measure the spiking activity of cells across the different cortical layers. By combining the use of these four innovations in marmosets and mice performing a visual detection task, the team will test the predictions of the theoretical model and learn how different cortical neuron-types impact iTW dynamics and perceptual sensitivity. Aim 1 tests the hypothesis that E/I population activity travels as iTWs in mice and marmosets. Aim 2 tests the prediction that iTWs are coordinated retinotopically across cortical areas, and that this coordination enhances perceptual sensitivity. Aim 3 will account mechanistically for the results of Aims 1 and 2 in a theoretically grounded spiking network model. Overall, by using innovative new technologies this interdisciplinary team will provide key insights into longstanding conceptual issues of profound importance to brain research.