Neural circuits for flexible audiomotor learning

用于灵活音频运动学习的神经电路

• 批准号: 10512051
• 负责人: Kishore V Kuchibhotla
• 金额: $ 48.79万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-11-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10512051
• 关键词: Acoustics; Animals; Association Learning; Auditory; Auditory area; Auditory system; Axon; Behavior; Behavioral; Behavioral Paradigm; Brain; Calcium; Cells; Code; Color; Complement; Data; Development; Discrimination; Discrimination Learning; Disease; Dissociation; Educational process of instructing; Exhibits; Image; Impairment; Knowledge; Knowledge acquisition; Laboratories; Language Disorders; Learning; Link; Measures; Mediating; Modeling; Monitor; Mus; Music; Neurobiology; Neuronal Plasticity; Neurons; Pathology; Patients; Pattern; Phase; Post-Traumatic Stress Disorders; Process; Psychological reinforcement; Publishing; Rewards; Role; Sensory; Shapes; Signal Induction; Signal Transduction; Site; Speech; Stereotyping; Stimulus; Symptoms; Synapses; System; Testing; Time; Training; Water; Whole-Cell Recordings; Work; auditory stimulus; autism spectrum disorder; basal forebrain; behavioral response; cholinergic; excitatory neuron; experience; flexibility; improved; in vivo; nervous system disorder; neural; neural circuit; neuromechanism; neuroregulation; optogenetics; receptive field; response; sound; spatiotemporal; two-photon; voltage clamp

The mammalian auditory system is remarkably adaptive; salient experiences and behavioral contexts can fundamentally alter the processing of sounds in order to sensitize neural circuits to behaviorally relevant information. How does the central auditory system learn to associate sounds to rewards, and relatedly, how does behavioral context mediate this plasticity? The formation of representations of sensory signals such as speech, music, and other forms of acoustic learning is critical for survival. And, yet, the formation of these representations during real-time learning remains largely unknown. In this proposal, we posit that learning can be dissociated into two distinct learning processes: the initial acquisition and subsequent expression of knowledge. Acquisition involves learning the core discrimination learning that underlie a behavior, and expression entails the use of this acquired discrimination in context. Acquisition and expression have typically been conflated in most laboratory tasks, leaving an important gap in our understanding of learning mechanisms in the central auditory system. Moreover, dissociating between acquisition and expression has important implications for development and language disorders. For example, soothing music can elicit neurotypical behavior in autism patients with otherwise severe symptoms. We aim to identify the separable neural mechanisms that enable sensorimotor acquisition versus contextual expression. Recently, we have shown that we can precisely dissociate acquisition from expression in a sensorimotor reward learning task. Thus, we now have a powerful behavioral approach to isolate acquisition from expression during learning. In this proposal, we will define the precise neural circuitry in the auditory cortex that enables these two aspects of learning. The auditory cortex is known to be a major site of plasticity; associative learning between sounds and rewards induce shifts in the “tuning” of cortical neurons. The cholinergic basal forebrain, moreover, has been implicated as a potent driver of receptive field plasticity in the central auditory system. These plasticity mechanisms likely reflect fundamental neural changes that are linked to acquisition of task knowledge. A1 is also heavily modulated by brain state and context, suggesting that A1 may also play a role in expression of task knowledge. Here, we propose to combine simultaneous real-time two-photon imaging of neurons in the auditory cortex (Aim 1) and cholinergic axons (Aim 2-3). We will perform causal manipulations of AC (Aim 1), cholinergic activity (Aims 2-3), in vivo whole-cell voltage clamp recordings (Aim 2), and detailed behavioral analysis (Aims 1-3) to determine the neural basis of audiomotor learning.

哺乳动物的听觉系统对于显着的体验和行为的适应能力很差。 环境可以从根本上改变声音的处理，从而使神经回路对声音敏感 行为相关信息。中枢听觉系统如何学习关联。 听起来与奖励有关，行为环境如何调节这种可塑性？ 感觉信号表征的形成，例如语音、音乐和其他形式的 然而，声音学习对于生存至关重要。 实时学习在很大程度上仍然未知。在这个提案中，我们假设学习可以是。 分为两个不同的学习过程：初始获取和随后的获取 知识的获取涉及学习核心辨别力。 行为的基础，而表达则需要在上下文中使用这种后天的歧视。 在大多数实验室任务中，获取和表达通常被混为一谈，留下了 我们对中枢听觉系统学习机制的理解存在重大差距。 此外，习得和表达之间的分离对于 例如，舒缓的音乐可以引起神经发育障碍。 我们的目标是确定具有其他严重症状的自闭症患者的行为。 实现感觉运动习得与情境表达的神经机制。 最近，我们已经证明，我们可以精确地将习得与表达分开 因此，我们现在有了一种强大的行为方法来完成感觉运动奖励学习任务。 在这个提案中，我们将精确地定义学习过程中的习得和表达。 听觉皮层中的神经回路实现了这两个方面的学习。 众所周知，皮层是声音和可塑性之间的联想学习的主要场所； 奖励会引起皮质神经元“调节”的变化，胆碱能基底前脑， 此外，它被认为是中央感受野可塑性的有效驱动因素 这些可塑性机制可能反映了基本的神经变化。 A1 与任务知识的获取也受到大脑状态和环境的严重调节， 表明A1也可能在任务知识的表达中发挥作用。在这里，我们建议： 结合听觉皮层神经元的同时实时双光子成像（目标 1） 和胆碱能轴突（目标 2-3），我们将对 AC 进行因果操作（目标 1）， 胆碱能活性（目标 2-3）、体内全细胞电压钳记录（目标 2）以及详细信息 行为分析（目标 1-3）以确定听觉运动学习的神经基础。