Wall Detection by Lateral Line Sensory System of Fish

Abstract

This paper investigates modeling of the lateral line of a fish as it approaches a wall. The lateral line system consists of the canal neuromasts (CNs) and superficial neuromasts (SNs). The relative roles of the CNs and SNs in this sensing task is investigated. The CNs detect pressure gradient on the fish’s skin, while SNs detect velocity near the skin. In order to relate these pressure and velocity distribution on the surface of the fish to its surrounding flow, we consider a potential flow coupled with a boundary layer model around the fish’s body. An exact solution is derived by assuming the fish to be infinitesimally thin. For fish-like bodies with finite thickness, the panel method is used to calculate the potential flow around the body. This outer potential flow solution is matched with the boundary layer integral method, to obtain a full viscous solution. The results show that the flow field changes significantly on the wall side of the fish as it approaches the wall, but the changes is mostly observed in a small region around the fish’s head, where the body has high surface curvature. This sensitivity could explain the observed higher concentration of CNs in the head region of most fish. Furthermore, local extreme points may be found in the pressure gradient curve and surface stress curve that correlated to a wall distance while the fish is close to the wall. The analysis of this paper demonstrates that a lateral line sensory system could produce enough information for detecting an upcoming wall.