Investigating the spatial representation and plasticity rules of a cortically dri

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Humans have the ability to learn and execute a wide range of complex motor behaviors that are integral to everyday life, from playing the piano to speaking, but little is known about how these behaviors are represented within the brain. A number of studies across species have attempted to elucidate the circuit organization of forebrain motor centers, but the range of behaviors used to address this issue has been limited to innate and relatively simple movements. Songbirds offer an excellent experimental model to study the organization of identified cortical circuits underlying a complex learned motor behavior. Distinct motor regions of the songbird brain have been identified that play an essential role in song production. One of these areas is the nucleus HVC (proper name), which has been shown to be the site of motor sequence generation for the song. Premotor neurons in HVC fire very sparely during singing, exhibiting a short burst of action potentials at a single precise moment within each rendition of the song. Different neurons burst at different times in the song, suggesting that these neurons form a sparse representation of time. Although it has been estimated that a group of approximately 200 neurons are simultaneously active at any moment during the song, practically nothing is known of how this network of premotor neurons is organized in the brain and the level of plasticity inherent in this organization. The two specific aims discussed in this proposal seek to address these issues. Using two-photon microscopy to visualize the network of HVC neurons in vivo, we will investigate the spatiotemporal organization of the song circuit and conduct a longitudinal study of song-related activity. In particular, Aim 1 will address whether there is a universal motor map for song performance, such that cells in specific regions of the nucleus are invariantly associated with similar temporal properties across a population of individuals. It will also determine whether neighboring neurons within an individual form clusters based on their temporal properties. Aim 2 will test whether the temporal properties of these premotor neurons shift over time, and the degree of plasticity inherent in the network. These experiments will be the first to examine the rules governing the spatial representation of a skilled motor behavior in the brain and the extent to which this premotor network changes over time.