A primary goal of neuroscience is to understand how the many components of the brain interact with each other to give rise to the remarkable capacities of perception, movement, and thinking exhibited by humans and other animals. For most brain regions, the parts list is too long and the function is poorly understood. This proposal takes advantage of an unusual animal--a fish that emits its own electrical field-- in which the brain structure is simple enough and the function sufficiently well understood, so that the detailed structure of neural circuits can be directly linked to function. The project combines high-resolution experimental measurements from individual components of the fish's brain with mathematical modeling to make such links. The specific goal of the proposal is to understand how changes in the strength of connections between neurons allows the fish to learn to ignore sensations produced by its own motor actions, so that the fish is better able to perceive tiny electrical fields generated by insect prey. The work entails extensive collaborative exchange between experimentalists and neural modelers, and will provide students at the undergraduate and graduate level with cross-disciplinary training. Additionally, science projects will be developed and taken to inner-city K-12 classrooms. Finally, the work has implications for our understanding of failures in the neural mechanisms that learn to distinguish self-generated from external sensory signals, a problem that is thought to occur in human neurological disorders such as schizophrenia.
The cerebellum-like electrosensory lobe (ELL) of mormyrid electric fish is an ideal model system for exploring how motor corollary discharge is used to predict self-generated sensory signals. Past work has produced a well-tested model in which spike timing-dependent synaptic plasticity sculpts well-described motor corollary discharge responses into a negative image of the sensory response to the fish's own electric organ discharge (EOD). The goal of this proposal is to extend this model from a description of the recordings of negative images in ELL to an understanding of the fish's ability to use this circuitry to detect the minute electrical signals generated by prey. The project will determine how ELL supports the detection of prey-like signals assessed from extracellular spike trains of identified neuron classes recorded at several key processing stages within the ELL. In parallel, models of ELL adaptive processing will be constructed to identify the essential features needed to account for the measured detection performance at both the neural and the behavioral level. Together, these closely coordinated experimental and theoretical efforts will provide a detailed explanation of how plasticity operating in a well-characterized circuit contributes to behavior.