Neural circuits for flexible audiomotor learning

用于灵活音频运动学习的神经电路

• 批准号: 10299630
• 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/10299630
• 关键词: Acoustics; Animals; Auditory; Auditory area; Auditory system; Axon; Behavior; Behavioral; Behavioral Paradigm; Brain; Calcium; Cells; Code; Color; Complement; Data; Development; Discrimination; Discrimination Learning; Disease; 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; Play; Post-Traumatic Stress Disorders; Process; Psychological reinforcement; Publishing; Rewards; Role; Sensory; 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; classical conditioning; excitatory neuron; experience; flexibility; in vivo; nervous system disorder; neural circuit; neuromechanism; neuroregulation; optogenetics; receptive field; relating to nervous system; 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具有显著的适应性;显著的经验和行为 环境可以从根本上改变声音的处理，以便使神经回路敏感， 行为相关的信息。中央听觉系统如何学会联想 声音到奖励，以及相关的，行为背景如何调节这种可塑性？的 感觉信号的表现形式，如语音，音乐和其他形式的 声学学习对生存至关重要。然而，这些表征的形成 实时学习在很大程度上仍然是未知的。在这个建议中，我们认为学习可以 分为两个不同的学习过程：最初的获得和随后的获得。 知识的表达。获取涉及学习核心歧视学习， 作为行为的基础，表达需要在上下文中使用这种后天的辨别。 在大多数实验室任务中，获取和表达通常被混为一谈， 这是我们对中枢听觉系统学习机制理解的一个重要空白。 此外，习得和表达之间的分离对以下方面具有重要意义： 发展和语言障碍。例如，舒缓的音乐可以引起神经典型的 自闭症患者的行为，否则严重的症状。我们的目标是识别可分离的 神经机制，使感觉运动获得与上下文表达。 最近，我们已经表明，我们可以精确地分离收购从表达在一个 感觉运动奖励学习任务。因此，我们现在有一个强大的行为方法， 在学习过程中将习得与表达分开。在本提案中，我们将定义 听觉皮层中的神经回路使这两个方面的学习成为可能。听觉 众所周知，大脑皮层是可塑性的主要场所;声音和 奖赏会引起皮层神经元的“调谐”变化。胆碱能基底前脑， 此外，它还被认为是中枢神经系统感受野可塑性的一个强有力的驱动因素。 听觉系统这些可塑性机制可能反映了基本的神经变化， 与任务知识的获取有关。A1也受到大脑状态和环境的严重调节， 提示A1也可能在任务知识的表达中发挥作用。在此，我们建议 听觉皮层神经元的联合收割机同步实时双光子成像（目的1） 和胆碱能轴突（Aim 2-3）。我们将执行AC的因果操作（目标1）， 胆碱能活性（目的2-3），体内全细胞电压钳记录（目的2），以及详细的 行为分析（目标1-3），以确定听觉学习的神经基础。