Object localization through the lateral line system of fish: theory and experiment

2007 ◽  
Vol 194 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Julie Goulet ◽  
Jacob Engelmann ◽  
Boris P. Chagnaud ◽  
Jan-Moritz P. Franosch ◽  
Maria D. Suttner ◽  
...  
2007 ◽  
Vol 8 (S2) ◽  
Author(s):  
Julie Goulet ◽  
Jacob Engelmann ◽  
Boris Chagnaud ◽  
Jan-Moritz Franosch ◽  
J Leo van Hemmen

Author(s):  
Taekyeong Jeong ◽  
Janggon Yoo ◽  
Daegyoum Kim

Abstract Inspired by the lateral line systems of various aquatic organisms that are capable of hydrodynamic imaging using ambient flow information, this study develops a deep learning-based object localization model that can detect the location of objects using flow information measured from a moving sensor array. In numerical simulations with the assumption of a potential flow, a two-dimensional hydrofoil navigates around four stationary cylinders in a uniform flow and obtains two types of sensory data during a simulation, namely flow velocity and pressure, from an array of sensors located on the surface of the hydrofoil. Several neural network models are constructed using the flow velocity and pressure data, and these are used to detect the positions of the hydrofoil and surrounding objects. The model based on a long short-term memory network, which is capable of learning order dependence in sequence prediction problems, outperforms the other models. The number of sensors is then optimized using feature selection techniques. This sensor optimization leads to a new object localization model that achieves impressive accuracy in predicting the locations of the hydrofoil and objects with only 40$\%$ of the sensors used in the original model.


2015 ◽  
Vol 113 (2) ◽  
pp. 657-668 ◽  
Author(s):  
Rafael Levi ◽  
Otar Akanyeti ◽  
Aleksander Ballo ◽  
James C. Liao

The ability of fishes to detect water flow with the neuromasts of their lateral line system depends on the physiology of afferent neurons as well as the hydrodynamic environment. Using larval zebrafish ( Danio rerio), we measured the basic response properties of primary afferent neurons to mechanical deflections of individual superficial neuromasts. We used two types of stimulation protocols. First, we used sine wave stimulation to characterize the response properties of the afferent neurons. The average frequency-response curve was flat across stimulation frequencies between 0 and 100 Hz, matching the filtering properties of a displacement detector. Spike rate increased asymptotically with frequency, and phase locking was maximal between 10 and 60 Hz. Second, we used pulse train stimulation to analyze the maximum spike rate capabilities. We found that afferent neurons could generate up to 80 spikes/s and could follow a pulse train stimulation rate of up to 40 pulses/s in a reliable and precise manner. Both sine wave and pulse stimulation protocols indicate that an afferent neuron can maintain their evoked activity for longer durations at low stimulation frequencies than at high frequencies. We found one type of afferent neuron based on spontaneous activity patterns and discovered a correlation between the level of spontaneous and evoked activity. Overall, our results establish the baseline response properties of lateral line primary afferent neurons in larval zebrafish, which is a crucial step in understanding how vertebrate mechanoreceptive systems sense and subsequently process information from the environment.


Zoomorphology ◽  
2020 ◽  
Author(s):  
Harald Ahnelt ◽  
David Ramler ◽  
Maria Ø. Madsen ◽  
Lasse F. Jensen ◽  
Sonja Windhager

AbstractThe mechanosensory lateral line of fishes is a flow sensing system and supports a number of behaviors, e.g. prey detection, schooling or position holding in water currents. Differences in the neuromast pattern of this sensory system reflect adaptation to divergent ecological constraints. The threespine stickleback, Gasterosteus aculeatus, is known for its ecological plasticity resulting in three major ecotypes, a marine type, a migrating anadromous type and a resident freshwater type. We provide the first comparative study of the pattern of the head lateral line system of North Sea populations representing these three ecotypes including a brackish spawning population. We found no distinct difference in the pattern of the head lateral line system between the three ecotypes but significant differences in neuromast numbers. The anadromous and the brackish populations had distinctly less neuromasts than their freshwater and marine conspecifics. This difference in neuromast number between marine and anadromous threespine stickleback points to differences in swimming behavior. We also found sexual dimorphism in neuromast number with males having more neuromasts than females in the anadromous, brackish and the freshwater populations. But no such dimorphism occurred in the marine population. Our results suggest that the head lateral line of the three ecotypes is under divergent hydrodynamic constraints. Additionally, sexual dimorphism points to divergent niche partitioning of males and females in the anadromous and freshwater but not in the marine populations. Our findings imply careful sampling as an important prerequisite to discern especially between anadromous and marine threespine sticklebacks.


2006 ◽  
Vol 193 (2) ◽  
pp. 271-277 ◽  
Author(s):  
S. Gelman ◽  
A. Ayali ◽  
E. D. Tytell ◽  
A. H. Cohen

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