Single neuron mechanisms of sensory-motor learning

感觉运动学习的单神经元机制

基本信息

批准号：
9097816
负责人：
Timothy James Gardner
金额：
$ 35.81万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-15 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9097816
关键词：
Accelerometer Address Adult Animal Behavior Area Basal Ganglia Behavior Birds Brain Cells Code Data Disease Fire - disasters Future Health Hour Human Individual Injury Learning Length Life Mammals Martes zibellina Measurement Measures Memory Microscopic Motor Motor Cortex Motor Skills Movement Nature Neurons Noise Patients Pattern Performance Plant Roots Process Property Prosthesis Published Comment Recording of previous events Recovery Research Resolution Rewards Sensory Shapes Signal Transduction Songbirds Testing Therapeutic Therapeutic Intervention Time Trauma base bird song brain computer interface brain machine interface calcium indicator design improved insight learned behavior millisecond motor control motor learning motor skill learning nerve injury neural circuit programs rate of change relating to nervous system research study sensory feedback sensory mechanism tool zebra finch

项目摘要

DESCRIPTION (provided by applicant): Humans maintain learned motor skills over long time-scales-for days, years or even decades. However, little is known about how the brain achieves this stability. Some studies indicate that while motor skills can remain stable for years, the individual neurons controlling them may significantly change their firing properties over the course of hours. In another view, the tuning of individual neurons is as stable as the motor skill itself. The central hypothesis of this project is that the brain encodes learned behaviors on two distinct levels - a mesoscopic level that is highly stable, and a microscopic level in which single neurons change and are influenced by the recent history of motor performance errors. In other words, the stability of a memory is rooted not in single neuron stability, but in network patterns that persist in spite of drifting activity in individual neurons. This project investigates this hypothesis by examining the neural basis of song in zebra finches. The neural circuits that underly song behavior are well defined, extensively studied, and in key respects homologous to the cortico-basal ganglia circuits that underly sensory-motor learning in mammals. For this project, the key value of the songbird is the stability of its behavior. A songbird can sing the same learned song with great precision for years providing a unique opportunity to examine how motor skills are preserved over long time-scales. Using new tools for stable recording from neurons, the project examines single neuron tuning and network patterns underlying song over time scales of days to months. To accelerate changes in the song motor program the project uses a brain-machine interface that generates brief bursts of noise during singing whenever the brain activates specific groups of neurons. Preliminary data reveals that birds can learn to reduce this interfering noise, and improve the quality of their songs by controlling the pattern of activity in the targeted neurons. Through the brain-machine interface and other experiments, significant preliminary data reveals that whereas mesoscopic dynamical patterns in premotor cortex are stable, individual neurons can drift in and out of the ensemble pattern, and adjust their activity to minimize performance errors. This project will reveal the rules of this process with cellular resolution. Insights gained from these experiments have the potential to impact human health. If single neurons drift in motor control, then knowing the rules that govern this drift will be critical to therapeutic interventions that promote recovery after injury, or create sable brain- machine interfaces for human prosthetics.

描述（由申请人提供）：人类在很长一段时间内（数天、数年甚至数十年）保持习得的运动技能。然而，人们对大脑如何实现这种稳定性知之甚少。一些研究表明，虽然运动技能可以保持稳定多年，但控制它们的单个神经元可能会在几个小时内显着改变其放电特性。另一种观点认为，单个神经元的调节与运动技能本身一样稳定。该项目的中心假设是，大脑在两个不同的层面上对习得的行为进行编码——一个是高度稳定的介观层面，另一个是单一的微观层面。神经元发生变化并受到最近运动表现错误历史的影响。换句话说，记忆的稳定性并非植根于单个神经元的稳定性，而是植根于尽管单个神经元的活动发生漂移但仍持续存在的网络模式。该项目通过检查斑胸草雀鸣叫的神经基础来研究这一假设。歌曲行为背后的神经回路已被明确定义、广泛研究，并且在关键方面与哺乳动物感觉运动学习背后的皮质基底神经节回路同源。对于这个项目，鸣鸟的关键价值是其行为的稳定性。鸣禽可以多年精确地唱同一首习得的歌曲，这提供了一个独特的机会来检查运动技能如何在长时间范围内保存。该项目使用新的神经元稳定记录工具，在数天到数月的时间尺度上检查单个神经元的调谐和歌曲背后的网络模式。为了加速歌曲运动程序的变化，该项目使用了脑机接口，只要大脑激活特定的神经元组，唱歌时就会产生短暂的噪音爆发。初步数据表明，鸟类可以学会减少这种干扰噪音，并通过控制噪音模式来提高歌曲的质量。目标神经元的活动。通过脑机接口和其他实验，重要的初步数据表明，虽然前运动皮层的细观动力学模式是稳定的，但单个神经元可以在整体模式中漂移，并调整其活动以最大限度地减少性能误差。该项目将通过细胞分辨率揭示这一过程的规则。从这些实验中获得的见解有可能影响人类健康。如果单个神经元在运动控制中发生漂移，那么了解控制这种漂移的规则对于促进损伤后恢复或为人体假肢创建稳定的脑机接口的治疗干预至关重要。