Single-unit response to AM sound in the auditory cortex.

描述(申请人提供)：单个神经元活动如何与知觉相关？单个神经元如何处理随时间变化的信息，这些信息是如何由它们的临时放电模式编码的？拟议的研究旨在解决这些基本问题。听觉系统在研究这些问题的结合方面是例外的，因为它独特的设计来分析声学环境中的时间结构。调幅(AM)声音提供听觉神经元锁相的声音强度的时间变化。时间刺激结构和时间反应特性之间的这种直接关系为研究大脑中的时间代码提供了一个很好的框架。我们将在非人类受试者的初级听觉皮质(A1)和听觉皮质中外侧野(ML)记录单位反应，同时他们主动辨别AM我们将用向量强度(VS)来表征单个神经元对AM的反应的时间相位锁定。我们还将测量峰值计数以响应AM利用源自信号检测理论的分析技术，我们将基于VS和尖峰计数来确定行为AM敏感性和神经AM敏感性。通过同时记录行为和神经活动，并将它们与类似的统计指标进行比较，这项研究的设计使我们能够直接将神经活动与行为联系起来。在这里，我们旨在解决三个具体的问题：1)时间或速率编码是否能更好地解释AM的分辨能力；2)主动参与AM识别是否提高了神经放电的时间精度以及A1和ML中AM的速率编码；3)A1和ML中的一些神经元活动是否与动物的决策密切相关。对A1和ML的比较研究将有助于理解听觉皮质中时间声音属性的并行和分层加工，以及这种加工是如何受到行为状态的调制的。此外，这项研究将迈出第一步，了解附近神经元之间活动的同步性程度，这对于推导神经敏感性如何被一群神经元解释的模型至关重要。这项研究将增加对语音是如何处理的理解，因为语音中含有丰富的AM这也将增加对时间处理的理解，这与几种学习障碍有关。另外，人工耳蜗将声音的幅度和时间信息作为主要线索进行传递，理解时间信息是如何在听觉系统的上游进行处理的，应该有助于设计这些假体，以改善残疾人的听力。

DESCRIPTION (provided by applicant): How does single neuron activity relate to perception? How do single neurons process temporally varying information, and how is this information encoded by their temporal firing pattern? The proposed study aims to address these fundamental questions. The auditory system is exceptional to study the union of these questions because of its unique design to analyze temporal structure in the acoustic environment. Amplitude-modulated (AM) sound provides temporal variation in sound intensity to which auditory neurons phase-lock. This straightforward relationship between temporal stimulus structure and temporal response properties provides an excellent framework to investigate temporal codes in the brain. We will record single-units responses in the primary auditory cortex (A1) and the middle-lateral field of the auditory cortex (ML) of non-human subjects while they actively discriminate AM. We will characterize temporal phase- locking of single neuron responses to AM with vector strength (VS). We will also measure spike-counts in response to AM. With analytical techniques derived from signal detection theory, we will determine behavioral AM sensitivity and neural AM sensitivity based on both VS and spike-count. By simultaneously recording behavior and neural activity and comparing them with analogous statistical measures, the design of this study allows us to directly link neural activity to behavior. Here, we aim to address three specific questions; 1) whether, temporal or rate codes, can better account for AM discrimination ability; 2) whether active engagement in AM discrimination improves the temporal precision of neural firing as well as rate coding of AM in A1 and ML; 3) whether some neurons' activities in A1 and ML are closely associated with the animal's decisions. Comparative study of A1 and ML will add to the understanding of parallel and hierarchical processing of temporal sound properties in the auditory cortex and how this processing is modulated by behavioral state. In addition, the study will take the first step to understand the degree of synchrony of activity across nearby neurons, which is critical to derive models of how neural sensitivity can be accounted for by a population of neurons. This study will add to the understanding of how speech is processed, as speech is rich with AM. This will also add to the understanding of temporal processing which has been linked to several learning impairments. Additionally, cochlear implants transmit amplitude and temporal information of sound as principal cues, and the understanding of how temporal information is processed upstream in auditory system should help in the design of these prostheses to improve the hearing of the impaired.