Sensory Encoding of Surface Waves by the Banded Kokopu Galaxias Fasciatus

Abstract

This thesis studies the encoding of surface waves in the lateral line system of the banded kokopu Galaxias fasciatus. It addresses the physics of surface waves, the transduction process at the lateral line receptors, and the generation of neural activity in the primary afferent neurons. The time course and amplitude of surface wave stimuli can be reproduced accurately through modelling procedures in either the time or frequency domain. All that is required is either a recording of a single waveform, or its frequency spectrum. Electrophysiology shows clearly that the complex nature of surface waves are cleariy encoded in the primary afferent responses. Within the canal subsystem, responses showed a range from those that encoded the high frequency wavecycles of the surface waves, to those that encoded a more complete representation of the frequencies in a waveform. The directional sensitivity of the superficial and canal subsystems is also clearly evident. Modelling demonstrated that the response of superficial neuromasts were best described by the waveform of the velocity of fluid motion over their surface. For the canal subsystem, no clear distinction could be made between velocity or acceleration as being the best indicator of the neural response. However, the modelling did show that waveforms could be found which provided a good match to the canal systems response. Finally, a single compartment model of a neuron is developed which produces neural simulations that are indistinguishable from the actual neural recordings. Their ability to exhibit the same degree of phase locking, spontaneous activity, response magnitude, and interstimulas variability provides us with a useful tool with which to address theories of stimulus localisation at a more physiologically realistic level. The mechanism used by G. fasciatus to determine the angle and distance of a stimulus is, likely to use both time and intensity information. A hypothetical model is presented for a robust mechanism that could account for the accuracy of this fish, even in circumstances likely to result in variable input to the system.