The neural mechanisms underlying learned motor behaviors are one of the least understood aspects of neuroscience, yet treatment of motor deficits after injury or disease is a significant clinical need. A better understanding of the organization of motor control could lead to effective treatments that provide enhancements of motor plasticity, or brain machine interfaces for functional restoration. However, at the cellular level, little is known about how brain circuits are able to learn and reproduce temporal sequences. One the greatest challenges involved in investigating natural motor control is the lack of repeatability of the learned motor skill. To image neuronal activity during the execution o a highly complex, yet stereotyped, behavior we propose to develop a transgenic songbird expressing the genetically-encoded Ca++ indicator GCaMP6. We will use the zebra finch, a species that learns to produce an extremely stereotyped song pattern, with strikingly small trial-to trial variations. Thus, this system provides a rare model from which to tightly correlate functional changes in neuronal activity to specific and readily measurable behavioral changes. Uncovering principles relating motor behavior and cell type specific circuit activity will provide key insights governing sensory-motor learning, adaptive plasticity in response to injury, and also provide insights for the development of next generation brain-machine interfaces.
Understanding how neurons participate in the learning and implementation of sequences is a fundamental question in brain science. For example, any movement results from the sequential activation of neurons that eventually control the muscles. To be able to implement treatments for disorders of movement resulting from disease (such as stroke or Parkinson's disease) or injury it is necessary to learn how sequences of neuronal activity are encoded in the brain at the level of individual cells. The ideal experimental system t achieve this goal would be an animal model that exhibited a learned motor behavior that is highly stereotypical, with minimal trial-to-trial variability. We propose to generate a transgenic songbird that would allow us to investigate how their brains organize sequences of neural activity as they learn and produce a highly stereotypical song. This project has the potential to provide insights for the development of next generation of brain-computer prosthetic interfaces for the treatment of movement disorders.
| Liberti 3rd, William A; Markowitz, Jeffrey E; Perkins, L Nathan et al. (2016) Unstable neurons underlie a stable learned behavior. Nat Neurosci 19:1665-1671 |
| Markowitz, Jeffrey E; Liberti 3rd, William A; Guitchounts, Grigori et al. (2015) Mesoscopic patterns of neural activity support songbird cortical sequences. PLoS Biol 13:e1002158 |
