A cortico-collicular network for hearing and noise avoidance responses in bats

蝙蝠的听力和噪音回避反应的皮质-丘脑网络

• 批准号: 520223571
• 负责人: Dr. Julio Hechavarria
• 金额: --
• 依托单位: Frankfurt Institute for Advanced Studies (FIAS)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/520223571?language=en
• 关键词: cortico; collicular; network; hearing; noise

Acoustic noise is a main source of disturbance for animals that use sounds for navigation (echolocation) and social communication. Noise can mask sensory responses to relevant stimuli and thus affect the ability to negotiate the environment. To avoid noise, animals rely on a variety of behaviors such as increasing call level and modifying the pitch and timing of vocalizations. Noise avoidance is a typical example of active sensing in which animals rely on sensory representations of the noise to adjust the physical attributes of their calls. The aim of this project is to investigate the role of the cortico-subcortical network composed of frontal cortex, auditory cortex and inferior colliculus in noise avoidance in bats. Bats are a well-established animal model for research in hearing and vocal behavior, and they thus provide a strong theoretical framework for studying noise avoidance circuits. Our guiding hypothesis is that noise avoidance involves an interplay between ascending and descending neural pathways that connect cortical and subcortical structures forming direct and indirect sensing loops. We propose a tandem project in which an experimentalist (Hechavarria, GU Frankfurt am Main) and a computational group (Triesch, FIAS, Frankfurt am Main) will team-up to record, model, and perturb the frontal cortex-auditory cortex-inferior colliculus network. In our experiments, bats will echolocate in noisy and quiet environments while they are swung in a pendulum. We will: i) record from cortical and subcortical areas simultaneously in behaving bats, ii) perturb neural activity by deactivating brain areas with focus on the frontal cortex, and iii) develop models with feedforward and feedback connectivity to understand how cortico-midbrain loops participate in the active efficient coding of information in noisy environments.

对于使用声音进行导航（回声定位）和社会交流的动物来说，声学噪声是干扰的主要来源。噪音可以掩盖对相关刺激的感官反应，从而影响对环境的适应能力。为了避免噪音，动物依赖于各种行为，如增加呼叫水平和修改音调和发声的时间。避噪是主动感知的一个典型例子，其中动物依赖于对噪音的感官表征来调整其叫声的物理属性。本研究的目的是探讨由额叶皮层、听觉皮层和下丘组成的皮层-皮层下网络在蝙蝠噪声回避中的作用。蝙蝠是研究听觉和发声行为的成熟动物模型，因此它们为研究噪声回避回路提供了强有力的理论框架。我们的指导性假设是，噪声回避涉及上行和下行神经通路之间的相互作用，这些通路连接皮层和皮层下结构，形成直接和间接的感知回路。我们提出了一个串联的项目，其中一个实验者（Hechavarria，GU法兰克福am Main）和一个计算组（Triesch，FIAS，法兰克福am Main）将合作记录，建模和扰动额叶皮层-听觉皮层-下丘网络。在我们的实验中，当蝙蝠在钟摆中摆动时，它们会在嘈杂和安静的环境中进行回声定位。我们将：i）在行为蝙蝠中同时从皮层和皮层下区域进行记录，ii）通过使大脑区域失活并专注于额叶皮层来扰乱神经活动，以及iii）开发具有前馈和反馈连接的模型，以了解皮质-中脑回路如何参与噪声环境中信息的主动有效编码。