Fish use an ability to sense water motion to coordinate behaviors as varied as prey capture, schooling, and spawning. This sense is facilitated by the lateral line system, which is an array of receptors, known as neuromasts, on the surface of the body. Neuromasts appear in a wide variety of shapes and sizes within and among species of fish. However, it is unclear how this variation affects the ability of fish to detect water flow. The aim of the proposed research is to develop a model for the micromechanics of neuromasts that will describe how differences in the form of neuromasts affect their sensitivity. This aim will be achieved by research organized in three stages. In the first stage, experiments will measure material properties of individual neuromasts in the larvae of zebrafish (Danio rerio). In particular, the stiffness of neuromasts will be measured by recording the bending of these structures when loaded with a fine thread of glass. These measurements will be incorporated into a computational model to be developed in the second stage of the project. This model will consider the hydrodynamics of a stimulus, the structural dynamics of the neuromast, and their mechanical interactions in order to predict how a neuromast deflects in response to fluid flow. The third stage of this project will test this model by measuring the deflections and neurobiological signals of neuromasts in response to oscillatory flow over a wide range of frequencies. Once the model has been verified by these experiments, it will provide a basis for interpreting how differences in the size and shape of neuromasts influence the function of the lateral line system. This will allow for consideration of functional changes over the course of developmental and evolutionary transformation. The work will involve student training in an integrative and interdisciplinary area that combines computational approaches with physiological assessment of lateral line function.
