scholarly journals Algorithms underlying flexible phototaxis in larval zebrafish

2020 ◽  
Author(s):  
Alex B. Chen ◽  
Diptodip Deb ◽  
Armin Bahl ◽  
Florian Engert
Keyword(s):  
Biological Control ◽  
Optimal Control ◽  
Control Systems ◽  
Environmental Conditions ◽  
Environmental Variables ◽  
Optimal Range ◽  
Behavioral Experiments ◽  
Set Point ◽  
Phototactic Behavior ◽  
Larval Zebrafish

SUMMARYTo thrive, organisms must maintain physiological and environmental variables in optimal ranges. However, in a dynamic world, the optimal range of a variable might fluctuate depending on the organism’s state or environmental conditions. Given these fluctuations, how do biological control systems maintain optimal control of physiological and environmental variables? We explored this question by studying the phototactic behavior of larval zebrafish. We demonstrate, with behavioral experiments and computational modeling, that larval zebrafish use phototaxis to maintain environmental luminance at a set point that depends on luminance history. We further show that fish compute this set point using information from both eyes, and that the set point fluctuates on a timescale of seconds when environmental luminance changes. These results expand on previous studies, where phototaxis was found to be primarily positive, and suggest that larval zebrafish, rather than consistently turning towards the brighter areas, exert homeostatic control over the luminance of their surroundings. Furthermore, we show that fluctuations in the surrounding luminance feed back on the system to drive allostatic changes to the luminance set point. Our work has uncovered a novel principle underlying phototaxis in larval zebrafish and characterized a behavioral algorithm by which larval zebrafish exert control over a sensory variable.

scholarly journals Algorithms underlying flexible phototaxis in larval zebrafish

2021 ◽  
Author(s):  
Alex B. Chen ◽  
Diptodip Deb ◽  
Armin Bahl ◽  
Florian Engert
Keyword(s):  
Biological Control ◽  
Visual Field ◽  
Control Systems ◽  
Environmental Variables ◽  
Homeostatic Control ◽  
Set Point ◽  
Phototactic Behavior ◽  
Larval Zebrafish ◽  
The Mean

To thrive, organisms must maintain physiological and environmental variables in suitable ranges. Given that these variables undergo constant fluctuations over varying timescales, how do biological control systems maintain control over these values? We explored this question in the context of phototactic behavior in larval zebrafish. We demonstrate that larval zebrafish use phototaxis to maintain environmental luminance at a set point, that the value of this set point fluctuates on a timescale of seconds when environmental luminance changes, and that it is determined by calculating the mean input across both sides of the visual field. These results expand on previous studies of flexible phototaxis in larval zebrafish; they suggest that larval zebrafish exert homeostatic control over the luminance of their surroundings, and that feedback from the surroundings drives allostatic changes to the luminance set point. As such, we describe a novel behavioral algorithm with which larval zebrafish exert control over a sensory variable.

scholarly journals The influence of dynamic environmental interactions on detection efficiency of acoustic transmitters in a large, deep, freshwater lake

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Natalie V. Klinard ◽  
Edmund A. Halfyard ◽  
Jordan K. Matley ◽  
Aaron T. Fisk ◽  
Timothy B. Johnson
Keyword(s):  
Study Design ◽  
Environmental Conditions ◽  
Power Output ◽  
Environmental Variables ◽  
Acoustic Telemetry ◽  
Detection Efficiency ◽  
Data Interpretation ◽  
Heterogeneous Environments ◽  
Depth Range ◽  
Dynamic Relationship

Abstract Background Acoustic telemetry is an increasingly common method used to address ecological questions about the movement, behaviour, and survival of freshwater and marine organisms. The variable performance of acoustic telemetry equipment and ability of receivers to detect signals from transmitters have been well studied in marine and coral reef environments to inform study design and improve data interpretation. Despite the growing use of acoustic telemetry in large, deep, freshwater systems, detection efficiency and range, particularly in relation to environmental variation, are poorly understood. We used an array of 90 69-kHz acoustic receivers and 8 sentinel range transmitters of varying power output deployed at different depths and locations approximately 100–9500 m apart for 215 days to evaluate how the detection efficiency of acoustic receivers varied spatially and temporally in relation to environmental conditions. Results The maximum distance that tags were detected ranged from 5.9 to 9.3 km. Shallow tags consistently had lower detection efficiency than deep tags of the same power output and detection efficiency declined through the winter months (December–February) of the study. In addition to the distance between tag and receiver, thermocline strength, surface water velocity, ice thickness, water temperature, depth range between tag and receiver, and number of fish detections contributed to explaining variation in detection efficiency throughout the study period. Furthermore, the most significant models incorporated interactions between several environmental variables and tag–receiver distance, demonstrating the complex temporal and spatial relationships that exist in heterogeneous environments. Conclusions Relying on individual environmental variables in isolation to interpret receiver performance, and thus animal behaviour, may be erroneous when detection efficiency varies across distances, depths, or tag types. As acoustic telemetry becomes more widely used to study ecology and inform management, it is crucial to understand its limitations in heterogeneous environments, such as freshwater lakes, to improve the quality and interpretation of data. We recommend that in situ range testing and retrospective analysis of detection efficiency be incorporated into study design for telemetry projects. Furthermore, we caution against oversimplifying the dynamic relationship between detection efficiency and environmental conditions for the sake of producing a correction that can be applied directly to detection data of tagged animals when the intended correction may not be justified.

Numerical Simulation of the “Floating Spiral” Pipeline Installation Procedure: Second Stage, Spiral Transportation, Behavior Under Waves

2008 ◽  
Author(s):  
Bruno Martins Jacovazzo ◽  
Fabri´cio Nogueira Correˆa ◽  
Carl Horst Albrecht ◽  
Breno Pinheiro Jacob ◽  
Fernando Gomes da Silva Torres ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Optimal Control ◽  
Environmental Conditions ◽  
Companion Paper ◽  
Time Constraints ◽  
Second Stage ◽  
Parametric Studies ◽  
Large Length ◽  
Transportation Behavior ◽  
Flat Spiral

The Floating Spiral pipeline installation method consists basically in winding the pipeline into a huge floating spiral, and towing this assembly to the installation site, where the spiral is then unwound and lowered to the seabed. In this method the pipeline is fabricated onshore, as the spiral is created, under well controlled conditions and relatively relaxed time constraints. Therefore the welds can be better inspected, which allows for optimal control of quality in pipeline manufacturing. The first stage of the installation process by this method consists in setting the pipeline afloat and winding it elastically to form a large flat spiral. This stage is studied in a companion paper [1], to be also presented at IPC2008. The second stage consists in towing the floating spiral pipeline employing standard tugboats before laying it at the installation site. The objective of this work is, therefore, to present results of parametric studies for a large length pipeline at this second stage of the Floating Spiral method. The focus now is in the pipeline behavior under wave environmental conditions during transportation. Several numerical simulations are performed and the results are discussed and compared.

The synthesis method of regulators for multichannel systems using neural networks

2020 ◽  
pp. 111-118
Author(s):  
Александр Александрович Воевода ◽  
Дмитрий Олегович Романников
Keyword(s):  
Neural Networks ◽  
Reinforcement Learning ◽  
Automatic Control ◽  
Control Systems ◽  
Synthesis Method ◽  
Neural Net ◽  
Initial State ◽  
Set Point ◽  
Automatic Control Systems ◽  
Policy Gradient

Синтез регуляторов для многоканальных систем - актуальная и сложная задача. Одним из возможных способов синтеза является применение нейронных сетей. Нейронный регулятор либо обучают на предварительно рассчитанных данных, либо используют для настройки параметров ПИД-регулятора из начального устойчивого положения замкнутой системы. Предложено использовать нейронные сети для регулирования двухканального объекта, при этом обучение будет выполняться из неустойчивого (произвольного) начального положения с применением методов обучения нейронных сетей с подкреплением. Предложена структура нейронной сети и замкнутой системы, в которой уставка задается при помощи входного параметра нейронной сети регулятора The problem for synthesis of automatic control systems is hard, especially for multichannel objects. One of the approaches is the use of neural networks. For the approaches that are based on the use of reinforcement learning, there is an additional issue - supporting of range of values for the set points. The method of synthesis of automatic control systems using neural networks and the process of its learning with reinforcement learning that allows neural networks learning for supporting regulation is proposed in the predefined range of set points. The main steps of the method are 1) to form a neural net input as a state of the object and system set point; 2) to perform modelling of the system with a set of randomly generated set points from the desired range; 3) to perform a one-step of the learning using the Deterministic Policy Gradient method. The originality of the proposed method is that, in contrast to existing methods of using a neural network to synthesize a controller, the proposed method allows training a controller from an unstable initial state in a closed system and set of a range of set points. The method was applied to the problem of stabilizing the outputs of a two-channel object, for which stabilization both outputs and the first near the input set point is required

scholarly journals A New Structure to Design Optimal Control Systems

1994 ◽  
Vol 27 (11) ◽  
pp. 101-104 ◽  
Author(s):  
L. Keviczky ◽  
C.S. Bányász
Keyword(s):  
Optimal Control ◽  
Control Systems
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