scholarly journals Automated, predictive, and interpretable inference of Caenorhabditis elegans escape dynamics

2019 ◽  
Vol 116 (15) ◽  
pp. 7226-7231 ◽  
Author(s):  
Bryan C. Daniels ◽  
William S. Ryu ◽  
Ilya Nemenman
Keyword(s):  
Artificial Intelligence ◽  
Caenorhabditis Elegans ◽  
Escape Response ◽  
Escape Behavior ◽  
Dynamical Variable ◽  
Motor Systems ◽  
Natural Systems ◽  
Escape Dynamics ◽  
Functional Logic ◽  
Interpretable Models

The roundworm Caenorhabditis elegans exhibits robust escape behavior in response to rapidly rising temperature. The behavior lasts for a few seconds, shows history dependence, involves both sensory and motor systems, and is too complicated to model mechanistically using currently available knowledge. Instead we model the process phenomenologically, and we use the Sir Isaac dynamical inference platform to infer the model in a fully automated fashion directly from experimental data. The inferred model requires incorporation of an unobserved dynamical variable and is biologically interpretable. The model makes accurate predictions about the dynamics of the worm behavior, and it can be used to characterize the functional logic of the dynamical system underlying the escape response. This work illustrates the power of modern artificial intelligence to aid in discovery of accurate and interpretable models of complex natural systems.

scholarly journals Automated, predictive, and interpretable inference of C. elegans escape dynamics

2018 ◽  
Author(s):  
Bryan C. Daniels ◽  
William S. Ryu ◽  
Ilya Nemenman
Keyword(s):  
Artificial Intelligence ◽  
Escape Response ◽  
Escape Behavior ◽  
Dynamical Variable ◽  
Motor Systems ◽  
Natural Systems ◽  
C Elegans ◽  
Escape Dynamics ◽  
Functional Logic ◽  
Interpretable Models

AbstractThe roundworm C. elegans exhibits robust escape behavior in response to rapidly rising temperature. The behavior lasts for a few seconds, shows history dependence, involves both sensory and motor systems, and is too complicated to model mechanistically using currently available knowledge. Instead we model the process phenomenologically, and we use the Sir Isaac dynamical inference platform to infer the model in a fully automated fashion directly from experimental data. The inferred model requires incorporation of an unobserved dynamical variable, and is biologically interpretable. The model makes accurate predictions about the dynamics of the worm behavior, and it can be used to characterize the functional logic of the dynamical system underlying the escape response. This work illustrates the power of modern artificial intelligence to aid in discovery of accurate and interpretable models of complex natural systems.

Something Old, Something New, Something Borrowed, Something Blue: Part 3 – An Elephant Never Forgets

2017 ◽  
Vol 26 (3) ◽  
pp. 433-437
Author(s):  
Mark Dougherty
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Natural Systems ◽  
European Court ◽  
New Knowledge ◽  
The Right ◽  
Contextual Environment ◽  
The Brain ◽  
Index Services ◽  
Incomplete Picture

AbstractForgetting is an oft-forgotten art. Many artificial intelligence (AI) systems deliver good performance when first implemented; however, as the contextual environment changes, they become out of date and their performance degrades. Learning new knowledge is part of the solution, but forgetting outdated facts and information is a vital part of the process of renewal. However, forgetting proves to be a surprisingly difficult concept to either understand or implement. Much of AI is based on analogies with natural systems, and although all of us have plenty of experiences with having forgotten something, as yet we have only an incomplete picture of how this process occurs in the brain. A recent judgment by the European Court concerns the “right to be forgotten” by web index services such as Google. This has made debate and research into the concept of forgetting very urgent. Given the rapid growth in requests for pages to be forgotten, it is clear that the process will have to be automated and that intelligent systems of forgetting are required in order to meet this challenge.

Mechanics of the fast-start: muscle function and the role of intramuscular pressure in the escape behavior of amia calva and polypterus palmas

1998 ◽  
Vol 201 (22) ◽  
pp. 3041-3055 ◽  
Author(s):  
MW Westneat ◽  
ME Hale ◽  
MJ Mchenry ◽  
JH Long
Keyword(s):  
Muscle Activity ◽  
Escape Response ◽  
Muscle Force ◽  
Escape Behavior ◽  
Pressure Change ◽  
The Body ◽  
Intramuscular Pressure ◽  
Fast Start ◽  
Amia Calva

The fast-start escape response is a rapid, powerful body motion used to generate high accelerations of the body in virtually all fishes. Although the neurobiology and behavior of the fast-start are often studied, the patterns of muscle activity and muscle force production during escape are less well understood. We studied the fast-starts of two basal actinopterygian fishes (Amia calva and Polypterus palmas) to investigate the functional morphology of the fast-start and the role of intramuscular pressure (IMP) in escape behavior. Our goals were to determine whether IMP increases during fast starts, to look for associations between muscle activity and elevated IMP, and to determine the functional role of IMP in the mechanics of the escape response. We simultaneously recorded the kinematics, muscle activity patterns and IMP of four A. calva and three P. palmas during the escape response. Both species generated high IMPs of up to 90 kPa (nearly 1 atmosphere) above ambient during the fast-start. The two species showed similar pressure magnitudes but had significantly different motor patterns and escape performance. Stage 1 of the fast-start was generated by simultaneous contraction of locomotor muscle on both sides of the body, although electromyogram amplitudes on the contralateral (convex) side of the fish were significantly lower than on the ipsilateral (concave) side. Simultaneous recordings of IMP, escape motion and muscle activity suggest that pressure change is caused by the contraction and radial swelling of cone-shaped myomeres. We develop a model of IMP production that incorporates myomere geometry, the concept of constant-volume muscular hydrostats, the relationship between fiber angle and muscle force, and the forces that muscle fibers produce. The timing profile of pressure change, behavior and muscle action indicates that elevated muscle pressure is a mechanism of stiffening the body and functions in force transmission during the escape response.

scholarly journals Drosophila melanogaster foragingregulates a nociceptive-like escape behavior through a developmentally plastic sensory circuit

2019 ◽  
Vol 117 (38) ◽  
pp. 23286-23291 ◽  
Author(s):  
Jeffrey S. Dason ◽  
Amanda Cheung ◽  
Ina Anreiter ◽  
Vanessa A. Montemurri ◽  
Aaron M. Allen ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Escape Response ◽  
Escape Behavior ◽  
Parasitoid Wasp ◽  
Nociceptive Response ◽  
Thermal Nociception ◽  
Nociceptive Neurons ◽  
Increased Sensitivity ◽  
Activity Dependent

Painful or threatening experiences trigger escape responses that are guided by nociceptive neuronal circuitry. Although some components of this circuitry are known and conserved across animals, how this circuitry is regulated at the genetic and developmental levels is mostly unknown. To escape noxious stimuli, such as parasitoid wasp attacks,Drosophila melanogasterlarvae generate a curling and rolling response. Rover and sitter allelic variants of theDrosophila foraging(for) gene differ in parasitoid wasp susceptibility, suggesting a link betweenforand nociception. By optogenetically activating cells associated with each offor’s promoters (pr1–pr4), we show that pr1 cells regulate larval escape behavior. In accordance with rover and sitter differences in parasitoid wasp susceptibility, we found that rovers have higher pr1 expression and increased sensitivity to nociception relative to sitters. Thefornull mutants display impaired responses to thermal nociception, which are rescued by restoringforexpression in pr1 cells. Conversely, knockdown offorin pr1 cells phenocopies thefornull mutant. To gain insight into the circuitry underlying this response, we used an intersectional approach and activity-dependent GFP reconstitution across synaptic partners (GRASP) to show that pr1 cells in the ventral nerve cord (VNC) are required for the nociceptive response, and that multidendritic sensory nociceptive neurons synapse onto pr1 neurons in the VNC. Finally, we show that activation of the pr1 circuit during development suppresses the escape response. Our data demonstrate a role offorin larval nociceptive behavior. This function is specific toforpr1 neurons in the VNC, guiding a developmentally plastic escape response circuit.

Effects of the antibiotic tetracycline on the reproduction, growth and population growth rate of the nematode Caenorhabditis elegans

Nematology ◽  
2014 ◽  
Vol 16 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Matthew Vangheel ◽  
Walter Traunspurger ◽  
Nicole Spann
Keyword(s):  
Growth Rate ◽  
Caenorhabditis Elegans ◽  
Population Growth ◽  
Surface Waters ◽  
Population Growth Rate ◽  
Significant Risk ◽  
Protein Synthesis Inhibitors ◽  
Natural Systems ◽  
C Elegans ◽  
Growth And Reproduction

The antibiotic tetracycline (TC) has been reported in natural systems, a consequence of its abundant usage in farming. TCs are protein synthesis inhibitors that are effective against bacteria but adverse effects on non-target organisms, whilst less well understood, have also been demonstrated. This study is the first investigation into the effects of this common antibiotic on the growth, reproduction and population growth rate (PGR) of the nematode Caenorhabditis elegans. All toxicological endpoints were shown to be affected negatively. TC concentrations as low as 5 mg l−1 (5 ppm) significantly reduced growth and reproduction, and even lower concentrations (3 mg l−1 or 3 ppm) significantly decreased the PGR. These levels are much higher than the TC concentrations detected in surface waters, sediments and soils (0.005-300 ppb). However, although the antibiotic might not pose a direct significant risk to nematodes in the natural environment, its use in RNAi experiments involving C. elegans may cause unwanted effects that influence interpretations of the results.

scholarly journals Preconditioning With Natural Microbiota Strain Ochrobactrum vermis MYb71 Influences Caenorhabditis elegans Behavior

2021 ◽  
Vol 11 ◽  
Author(s):  
Carola Petersen ◽  
Barbara Pees ◽  
Christina Martínez Christophersen ◽  
Matthias Leippe
Keyword(s):  
Caenorhabditis Elegans ◽  
Avoidance Behavior ◽  
Choice Behavior ◽  
Escape Behavior ◽  
Multiple Choice ◽  
Future Research ◽  
C Elegans ◽  
Main Driver ◽  
Pathogen Avoidance ◽  
Natural Microbiota

In comparison with the standard monoxenic maintenance in the laboratory, rearing the nematode Caenorhabditis elegans on its natural microbiota improves its fitness and immunity against pathogens. Although C. elegans is known to exhibit choice behavior and pathogen avoidance behavior, little is known about whether C. elegans actively chooses its (beneficial) microbiota and whether the microbiota influences worm behavior. We examined eleven natural C. elegans isolates in a multiple-choice experiment for their choice behavior toward four natural microbiota bacteria and found that microbiota choice varied among C. elegans isolates. The natural C. elegans isolate MY2079 changed its choice behavior toward microbiota isolate Ochrobactrum vermis MYb71 in both multiple-choice and binary-choice experiments, in particular on proliferating bacteria: O. vermis MYb71 was chosen less than other microbiota bacteria or OP50, but only after preconditioning with MYb71. Examining escape behavior and worm fitness on MYb71, we ruled out pathogenicity of MYb71 and consequently learned pathogen avoidance behavior as the main driver of the behavioral change toward MYb71. The change in behavior of C. elegans MY2079 toward microbiota bacterium MYb71 demonstrates how the microbiota influences the worm’s choice. These results might give a baseline for future research on host–microbiota interaction in the C. elegans model.

scholarly journals Cognitive Mimetics for Designing Intelligent Technologies

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Tuomo Kujala ◽  
Pertti Saariluoma
Keyword(s):  
Artificial Intelligence ◽  
Pattern Matching ◽  
Interaction Design ◽  
Human Information Processing ◽  
Motor Systems ◽  
Design Problems ◽  
Important Method ◽  
Sensory Motor ◽  
Intelligent Technology ◽  
Technical Solutions

Design mimetics is an important method of creation in technology design. Here, we review design mimetics as a plausible approach to address the problem of how to design generally intelligent technology. We argue that design mimetics can be conceptually divided into three levels based on the source of imitation. Biomimetics focuses on the structural similarities between systems in nature and technical solutions for solving design problems. In robotics, the sensory-motor systems of humans and animals are a source of design solutions. At the highest level, we introduce the concept of cognitive mimetics, in which the source for imitation is human information processing. We review and discuss some historical examples of cognitive mimetics, its potential uses, methods, levels, and current applications, and how to test its success. We conclude by a practical example showing how cognitive mimetics can be a highly valuable complimentary approach for pattern matching and machine learning based design of artificial intelligence (AI) for solving specific human-AI interaction design problems.

scholarly journals Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 953 ◽  
Author(s):  
Anjali Ramachandran ◽  
Rabee Rustum ◽  
Adebayo J. Adeloye
Keyword(s):  
Artificial Intelligence ◽  
Parallel Computing ◽  
Anaerobic Digestion ◽  
Soft Computing ◽  
Optimal Solution ◽  
Self Organization ◽  
Economic Factors ◽  
Comprehensive Review ◽  
Natural Systems ◽  
Engineered Systems

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.

scholarly journals Application Of Artificial Intelligence Techniques Aiming At Energy Efficiency And Parameter Estimation In Industrial Motor Systems

2008 ◽  
Vol 13 (4) ◽  
pp. 209-216
Author(s):  
Wellington Rocha Araújo ◽  
Luciana Cambraia Leite ◽  
Saulo Gomes Moreira ◽  
Valmir Machado Pereira ◽  
Amâncio Rodrigues da Silva Júnior
Keyword(s):  
Artificial Intelligence ◽  
Energy Efficiency ◽  
Parameter Estimation ◽  
Motor Systems ◽  
Artificial Intelligence Techniques

scholarly journals Networks of Causal Linkage Between Eigenmodes Characterize Behavioral Dynamics of Caenorhabditis elegans

2021 ◽  
Vol 17 (9) ◽  
pp. e1009329
Author(s):  
Erik Saberski ◽  
Antonia K. Bock ◽  
Rachel Goodridge ◽  
Vitul Agarwal ◽  
Tom Lorimer ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Animal Behavior ◽  
Escape Response ◽  
Model Organism ◽  
Model Organisms ◽  
High Dimensional ◽  
Behavioral Differences ◽  
Behavioral Dynamics ◽  
Mutant Strains ◽  
Behavioral States

Behavioral phenotyping of model organisms has played an important role in unravelling the complexities of animal behavior. Techniques for classifying behavior often rely on easily identified changes in posture and motion. However, such approaches are likely to miss complex behaviors that cannot be readily distinguished by eye (e.g., behaviors produced by high dimensional dynamics). To explore this issue, we focus on the model organism Caenorhabditis elegans, where behaviors have been extensively recorded and classified. Using a dynamical systems lens, we identify high dimensional, nonlinear causal relationships between four basic shapes that describe worm motion (eigenmodes, also called “eigenworms”). We find relationships between all pairs of eigenmodes, but the timescales of the interactions vary between pairs and across individuals. Using these varying timescales, we create “interaction profiles” to represent an individual’s behavioral dynamics. As desired, these profiles are able to distinguish well-known behavioral states: i.e., the profiles for foraging individuals are distinct from those of individuals exhibiting an escape response. More importantly, we find that interaction profiles can distinguish high dimensional behaviors among divergent mutant strains that were previously classified as phenotypically similar. Specifically, we find it is able to detect phenotypic behavioral differences not previously identified in strains related to dysfunction of hermaphrodite-specific neurons.

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