CRCNS: Visual Modulation of Panoramic Auditory Spatial Processing

在日常活动中，我们的空间感是由协调一致的多感官分析来引导的 来自周围环境的信息。多感官空间信息对于识别和识别 在嘈杂的环境中注意目标声音(例如，夜总会、餐馆)。多感官信息 对于检测已知但不可见的危险也至关重要，因为由声音和视觉编码的空间 不要总是对齐。对于像人类和猴子这样的中心凹物种，视野被限制在前额 空间，而听觉领域是全景，覆盖整个前部和后部空间。后方空间， 然而，在多感官研究中，它基本上被忽视了。在很大程度上，人们仍然不知道它在哪里以及如何 视觉直接影响大脑中的听觉空间处理。这项研究的长期目标是 了解多感官空间知觉和大脑皮层神经机制的基本策略 在大脑中实施这些策略。该提案将研究视觉信息是如何调制的 利用一种综合方法对听觉皮质中360度全景空间进行听觉编码 神经生理学、机械计算建模和预测统计建模。我们 假设视觉空间信息通过以下方式增加额叶空间的听觉表征 改变神经网络动力学的方向偏好。神经生理学实验将 提供对听觉皮质360度空间调谐变化的全面评估 额叶视觉刺激后的神经元。计算模型将有助于识别假定的细胞类型和 揭示记录的细胞外尖峰波形如何依赖于刺激条件和 单元类型。预测性统计建模将确定皮层神经元放电的变异来源 数据，并将预测不同类型细胞在不同条件下的尖峰输出，均为层流 专一性。这一综合方法将提供对听觉空间视觉调制的理解 注重局部节律产生器和单个单位之间特定层级相互作用的加工 活动。这项工作的影响将通过以标准格式、严格的 和透明的模型验证，并使用允许编码的模型描述标准 生成多种不同编程语言或仿真平台的仿真模型 模型重用。 相关性(请参阅说明)： 神经系统整合多感官输入的能力是沟通的关键。 复杂的感觉和社会环境。这种能力的损害是最明显的后果 听力损失。识别听觉皮质如何在视觉环境中编码声音特征将 提高我们对多感官知觉如何在神经回路中实现的理解，从而 揭示真实世界条件下知觉损伤的潜在来源。

In everyday activity, our sense of space is guided by coordinated multisensory analyses of sensory information from the surrounding environment. Multisensory spatial information is critical for identifying and attending to a target sound in a noisy environment (e.g., night bars, restaurants). Multisensory information is also crucial for detecting heard but unseen dangers because the spaces encoded by sounds and sights do not always align. For foveal species like humans and monkeys, the visual field is restricted to the frontal space, whereas the auditory field is panoramic, covering the entire frontal and rear space. The rear space, however, has been largely overlooked in multisensory research. It remains largely unknown where and how vision directly influences auditory spatial processing in the brain. The long-term objective of this study is to understand the fundamental strategies of multisensory spatial perception and cortical neural mechanisms that implement these strategies in the brain. This proposal will investigate how visual information modulates auditory encoding of 360-degree, panoramic space in auditory cortex using an integrated approach based on neurophysiology, mechanistic computational modeling, and predictive statistical modeling. We hypothesize that visuo-spatial information increases auditory representation of the frontal space by changing the directional preference of neural network dynamics. Neurophysiological experiments will provide a comprehensive assessment of changes in the 360-degree spatial tuning of auditory cortex neurons after frontal visual stimulation. Computational models will aid in identifying putative cell types and reveal how heterogeneous recorded extracellular spiking waveforms depend on stimulus conditions and cell type. Predictive statistical modeling will determine the sources of variance in cortical neuron spiking data and will predict spiking output of different cell types under different conditions, all with laminar specificity. This integrated approach will provide an understanding of visual modulation of auditory spatial processing with a focus on the layer-specific interactions between local rhythm generators and single unit activity. The impact of this work will be maximized through sharing of data in standardized formats, rigorous and transparent model validation, and use of model description standards, which allows for code generation for simulating models in many different programming languages or simulation platforms for model re-use. RELEVANCE (See instructions): The ability of the nervous system to integrate multisensory inputs is essential to communications in complex sensory and social environments. Impairment of this ability is the most noticeable outcome of hearing loss. Identifying how the auditory cortex encodes sound features in a visual environment will improve our understanding of how multisensory perception might be implemented in neural circuits, thereby revealing potential sources of perceptual impairment in real-world conditions.