Functional analyses of the vocal central pattern generators of African clawed frogs

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The most salient output of brain function is behavior, but how the nervous system produces behavior is not well understood, largely because most of the neural pathways underlying behavior in vertebrates are complicated. In this research project, the vocal behavior of African clawed frogs is used as a model because their vocal neural pathways are simple, straight forward, and accessible using techniques previously developed in the PI's laboratory. Traditionally, the signal within behavioral neural pathways has been considered to flow in one direction, from the upstream command center to the output station in the brain that activates muscles that generate behavior. However, the investigators recently obtained evidence that, in addition to activating muscles, the neuronal signal from the output station also flows back to the command center within the brain. It is hypothesized that the feedback signal plays an important role in shaping the behavior of animals. In this study, functional roles of the feedback signal will be examined using a variety of experimental techniques. The results of the study will provide us with an understanding of how behaviors are generated in general, and may shed light on the importance of feedback signal for behavioral neural circuitry in general. In addition to the significance of the scientific outcomes, the project will be used as an opportunity to train students from diverse backgrounds, including under-represented minorities, in the field of neuroscience. A major goal in neuroscience is to understand how neural networks function to generate motor programs that underlie behavior. Although analyses of a complete neural network that generates behavior is a formidable task, the central vocal network of African clawed frog, Xenopus laevis, allows detailed investigation of the dynamic organization of the brain in action. In this study, the investigators will carry out cellular analyses of the newly discovered population of neurons that projects back from the motor nucleus to the premotor nucleus using electrophysiological and optogenetic approaches. The application of optogenetic tools to non-genetic model organisms such as Xenopus laevis is still in its infancy. One of the goals of the project is to perfect the technique so that it can be utilized by a broader community of comparative neuroscientists. The results of the study will not only provide insight into the structure and function of the rhythm-generating neural network underlying functional behavior at the cellular level, but also may reveal the potential importance of a feedback loop within a neural network to generate stable neuronal rhythms. Rhythmic neuronal activity is not limited to motor systems, but is prevalent across the entire CNS and is considered to underlie important functions such as perception and cognition. Thus, understanding the biophysical principles that govern rhythm generation using a simple neural network has a potential to elucidate mechanisms underlying neuronal oscillations in general.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.