Joy Putney Thesis Proposal:
Temporal encoding, coordination, and adaptation in a comprehensive, spike-resolved motor program
Dr. Simon Sponberg; School of Biological Sciences; Georgia Institute of Technology
Dr. Young-Hui Chang; School of Biological Sciences; Georgia Institute of Technology
Dr. Ilya Nemenman; Department of Physics; Emory University
Dr. Garrett Stanley; Department of Biomedical Engineering; Georgia Institute of Technology & Emory University
Animals must execute robust, agile movement in a variety of biomechanical and environmental contexts. The nervous system must encode information for movement across multiple muscles in such a way that an animal can adapt to these changing contexts. Understanding how nervous systems functionally encode movement across multiple muscles will deepen our understanding of neural circuits and how the brain works as well as inform the design of better neuroprostheses and brain-machine interfaces. Due partly to recent public funding efforts like the BRAIN initiative, we now have unprecedented access to highly dimensional neural data sets and a large data analysis toolbox. Despite the proliferation of cutting-edge experimental tools, peripheral motor commands and encoding strategies are relatively unexplored. A limitation to the study of peripheral motor programming is the difficulty of recording simultaneously from all neurons involved in controlling a behavior, since most behaviors involve multiple muscles innervated by many neurons. Using a comprehensive, spike-resolved motor program of 10 muscles in the hawk moth, Manduca sexta, I propose investigating how a full complement of neural signals for movement encode information, coordinate muscles, and adapt to motor task changes. I first established a temporal encoding mechanism for consistency and coordination in a naturalistic behavior (Aim 1). We showed that the amount of temporally encoded information was higher than rate encoded information for hawk moth flight. We also demonstrated that coordination of pairwise combinations of muscles involves the sharing of temporally encoded information, not rate encoded information. These results indicate that a consistent, mixed encoding strategy is implemented across a motor program and that coordination requires temporal encoding. By using virtual reality (VR) to sample the full range of motion a hawk moth can produce in flight, I will investigate the importance of coordination for flight stability (Aim 2). I will implement closed loop feedback in this VR environment to determine the effects of neural variability on adaptation in a learning paradigm where the feedback gains are altered (Aim 3). Finally, I will tie these concepts together through causal experiments where I investigate the importance of timing for determining motor output and how coordination and adaptation in the motor program affect response to a simulated injury through EMG stimulation (Aim 4).