scholarly journals Coevolution of cognitive abilities and identity signals in individual recognition systems

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190467 ◽  
Author(s):  
Sara E. Miller ◽  
Michael J. Sheehan ◽  
H. Kern Reeve
Keyword(s):  
Cognitive Abilities ◽  
Phenotypic Diversity ◽  
Individual Recognition ◽  
Experimental Tests ◽  
Selection Gradients ◽  
Sensory Modalities ◽  
Signal Production ◽  
Recognition Systems ◽  
Multiple Species ◽  
Evolving Models

Social interactions are mediated by recognition systems, meaning that the cognitive abilities or phenotypic diversity that facilitate recognition may be common targets of social selection. Recognition occurs when a receiver compares the phenotypes produced by a sender with a template. Coevolution between sender and receiver traits has been empirically reported in multiple species and sensory modalities, though the dynamics and relative exaggeration of traits from senders versus receivers have received little attention. Here, we present a coevolutionary dynamic model that examines the conditions under which senders and receivers should invest effort in facilitating individual recognition. The model predicts coevolution of sender and receiver traits, with the equilibrium investment dependent on the relative costs of signal production versus cognition. In order for recognition to evolve, initial sender and receiver trait values must be above a threshold, suggesting that recognition requires some degree of pre-existing diversity and cognitive abilities. The analysis of selection gradients demonstrates that the strength of selection on sender signals and receiver cognition is strongest when the trait values are furthest from the optima. The model provides new insights into the expected strength and dynamics of selection during the origin and elaboration of individual recognition, an important feature of social cognition in many taxa. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals Mechanisms of recognition in birds and social Hymenoptera: from detection to information processing

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190483 ◽  
Author(s):  
Natacha Rossi ◽  
Sébastien Derégnaucourt
Keyword(s):  
Individual Recognition ◽  
Experimental Tests ◽  
Mate Recognition ◽  
Social Hymenoptera ◽  
Song Control System ◽  
Recognition Systems ◽  
Song Control ◽  
Avian Song ◽  
Evolving Models ◽  
Nest Mate Recognition

In this opinion piece, we briefly review our knowledge of the mechanisms underlying auditory individual recognition in birds and chemical nest-mate recognition in social Hymenoptera. We argue that even though detection and perception of recognition cues are well studied in social Hymenoptera, the neural mechanisms remain a black box. We compare our knowledge of these insect systems with that of the well-studied avian ‘song control system’. We suggest that future studies on recognition should focus on the hypothesis of a distributed template instead of trying to locate the seat of the template as recent results do not seem to point in that direction. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals Complex signals alter recognition accuracy and conspecific acceptance thresholds

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190482 ◽  
Author(s):  
Elizabeth A. Tibbetts ◽  
Ming Liu ◽  
Emily C. Laub ◽  
Sheng-Feng Shen
Keyword(s):  
Low Cost ◽  
Experimental Tests ◽  
Complex Signals ◽  
Informative Signal ◽  
Stable Mechanism ◽  
Individual Based Models ◽  
Sensory Modalities ◽  
Recognition Systems ◽  
Recognition Errors ◽  
Evolving Models

Many aspects of behaviour depend on recognition, but accurate recognition is difficult because the traits used for recognition often overlap. For example, brood parasitic birds mimic host eggs, so it is challenging for hosts to discriminate between their own eggs and parasitic eggs. Complex signals that occur in multiple sensory modalities or involve multiple signal components are thought to facilitate accurate recognition. However, we lack models that explore the effect of complex signals on the evolution of recognition systems. Here, we use individual-based models with a genetic algorithm to test how complex signals influence recognition thresholds, signaller phenotypes and receiver responses. The model has three main results. First, complex signals lead to more accurate recognition than simple signals. Second, when two signals provide different amounts of information, receivers will rely on the more informative signal to make recognition decisions and may ignore the less informative signal. As a result, the particular traits used for recognition change over evolutionary time as sender and receiver phenotypes evolve. Third, complex signals are more likely to evolve when recognition errors are high cost than when errors are low cost. Overall, redundant, complex signals are an evolutionarily stable mechanism to reduce recognition errors. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals Evolutionarily stable investments in recognition systems explain patterns of discrimination failure and success

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190465 ◽  
Author(s):  
Michael J. Sheehan ◽  
H. Kern Reeve
Keyword(s):  
Signal Detection Theory ◽  
Social Insect ◽  
Experimental Tests ◽  
Theory Model ◽  
The Other ◽  
Theme Issue ◽  
Brood Parasites ◽  
Recognition Systems ◽  
Evolving Models ◽  
Evolutionarily Stable

Many animals are able to perform recognition feats that astound us—such as a rodent recognizing kin it has never met. Yet in other contexts, animals appear clueless as when reed warblers rear cuckoo chicks that bear no resemblance to their own species. Failures of recognition when it would seem adaptive have been especially puzzling. Here, we present a simple tug-of-war game theory model examining how individuals should optimally invest in affecting the accuracy of discrimination between desirable and undesirable recipients. In the game, discriminating individuals (operators) and desirable and undesirable recipients (targets and mimics, respectively) can all invest effort into their own preferred outcome. We demonstrate that stable inaccurate recognition will arise when undesirable recipients have large fitness gains from inaccurate recognition relative to the pay-offs that the other two parties receive from accurate recognition. The probability of accurate recognition is often determined by just the relative pay-offs to the desirable and undesirable recipients, rather than to the discriminator. Our results provide a new lens on long-standing puzzles including a lack of nepotism in social insect colonies, tolerance of brood parasites and male birds caring for extra-pair young in their nests, which our model suggests should often lack accurate discrimination. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests'.

scholarly journals Finding a signal hidden among noise: how can predators overcome camouflage strategies?

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190478 ◽  
Author(s):  
James A. M. Galloway ◽  
Samuel D. Green ◽  
Martin Stevens ◽  
Laura A. Kelley
Keyword(s):  
Visual Processing ◽  
Signal Detection Theory ◽  
Experimental Tests ◽  
The Past ◽  
Substantial Progress ◽  
Recognition Systems ◽  
The Relationship ◽  
Evolving Models ◽  
Made In ◽  
Detection And Recognition

Substantial progress has been made in the past 15 years regarding how prey use a variety of visual camouflage types to exploit both predator visual processing and cognition, including background matching, disruptive coloration, countershading and masquerade. By contrast, much less attention has been paid to how predators might overcome these defences. Such strategies include the evolution of more acute senses, the co-opting of other senses not targeted by camouflage, changes in cognition such as forming search images, and using behaviours that change the relationship between the cryptic individual and the environment or disturb prey and cause movement. Here, we evaluate the methods through which visual camouflage prevents detection and recognition, and discuss if and how predators might evolve, develop or learn counter-adaptations to overcome these. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests'.

scholarly journals Individual vocal recognition across taxa: a review of the literature and a look into the future

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190479 ◽  
Author(s):  
Nora V. Carlson ◽  
E. McKenna Kelly ◽  
Iain Couzin
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Experimental Tests ◽  
Mate Recognition ◽  
Review Of The Literature ◽  
Theme Issue ◽  
Animal Kingdom ◽  
Vocal Recognition ◽  
Recognition Systems ◽  
Evolving Models

Individual vocal recognition (IVR) has been well studied in mammals and birds. These studies have primarily delved into understanding IVR in specific limited contexts (e.g. parent–offspring and mate recognition) where individuals discriminate one individual from all others. However, little research has examined IVR in more socially demanding circumstances, such as when an individual discriminates all individuals in their social or familial group apart. In this review, we describe what IVR is and suggest splitting studies of IVR into two general types based on what questions they answer (IVR-singular, and IVR-multiple). We explain how we currently test for IVR, and many of the benefits and drawbacks of different methods. We address why IVR is so prevalent in the animal kingdom, and the circumstances in which it is often found. Finally, we explain current weaknesses in IVR research including temporality, specificity, and taxonomic bias, and testing paradigms, and provide some solutions to address these weaknesses. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals How to learn to recognize conspecific brood parasitic offspring

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190472 ◽  
Author(s):  
Daizaburo Shizuka ◽  
Bruce E. Lyon
Keyword(s):  
Signal Detection Theory ◽  
Experimental Tests ◽  
Brood Parasite ◽  
Learning Mechanism ◽  
Brood Parasites ◽  
Genetic Mechanisms ◽  
Recognition Systems ◽  
Recognition Errors ◽  
The Cost ◽  
Evolving Models

Recognition systems evolve to reduce the risk and costs of making recognition errors. Two main sources of recognition error include perceptual error (error arising from inability to discriminate between objects) and template error (error arising from using the wrong recognition template). We focus on how template error shapes host defence against avian brood parasites. Prior experiments in American coots ( Fulica americana ), a conspecific brood parasite, demonstrated how hosts learn to recognize brood parasitic chicks using predictable patterns of hatching order of host and parasite eggs. Here, we use these results to quantify the benefit of chick rejection as well as the cost of template error, and we then use mathematical models to explore fitness payoffs of chick recognition from different template acquisition mechanisms. We find that fitness differences between mechanisms do not fully explain aspects of the learning mechanism, such as why coots reacquire their recognition template each year. Other constraints arising from mating systems and genetic mechanisms likely influence which learning mechanism for parasitic chick recognition is optimal. Our approach highlights how mechanisms of template acquisition influence other recognition systems, including parasitic chick recognition in other brood parasite hosts. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals Stress signalling in acellular slime moulds and its detection by conspecifics

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190470 ◽  
Author(s):  
L. Briard ◽  
C. Goujarde ◽  
C. Bousquet ◽  
A. Dussutour
Keyword(s):  
Stress Responses ◽  
Experimental Tests ◽  
Slime Moulds ◽  
Rapid Changes ◽  
Unicellular Organisms ◽  
Recognition Systems ◽  
Physiological Reactions ◽  
Evolving Models ◽  
Homogeneous Environment ◽  
Stress Signalling

Unicellular organisms live in unpredictable environments. Therefore, they need to continuously assess environmental conditions and respond appropriately to survive and thrive. When subjected to rapid changes in their environment or to cellular damages, unicellular organisms such as bacteria exhibit strong physiological reactions called stress responses that can be sensed by conspecifics. The ability to detect and use stress-related cues released by conspecifics to acquire information about the environment constitutes an adaptive survival response by prompting the organism to avoid potential dangers. Here, we investigate stress signalling and its detection by conspecifics in a unicellular organism, Physarum polycephalum . Slime moulds were subjected to either biotic (i.e. nutritional) or abiotic (i.e. chemical and light) stressors or left undisturbed while they were exploring a homogeneous environment. Then, we observed the responses of slime moulds facing a choice between cues released by stressed clone mates and cues released by undisturbed ones. We found that slime moulds actively avoided environments previously explored by stressed clone mates. These results suggest that slime moulds, like bacteria or social amoeba, exhibit physiological responses to biotic and abiotic stresses that can be sensed by conspecifics. Our results establish slime moulds as a promising new model to investigate the use of social information in unicellular organisms. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals The evolution of species recognition labels in insects

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190476 ◽  
Author(s):  
Seira Ashley Adams ◽  
Neil Durie Tsutsui
Keyword(s):  
Species Recognition ◽  
Experimental Tests ◽  
Mate Recognition ◽  
Future Directions ◽  
Mating Pheromones ◽  
Body Of Knowledge ◽  
Recognition Systems ◽  
Productive Research ◽  
Species Specific ◽  
Evolving Models

The evolution of pre-zygotic reproductive isolation is a key step in the process of speciation. In many organisms, particularly insects, chemical labels are used as pheromones for species-specific mate recognition. Although an enormous body of knowledge exists regarding the patterns of pheromone chemical ecology, much less is known about the evolutionary processes that underlie the origin of new mating pheromones. Here, we examine case studies that have illuminated the origins of species-specific mating pheromones and suggest future directions for productive research. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

scholarly journals Dissections of Larval, Pupal and Adult Butterfly Brains for Immunostaining and Molecular Analysis

2021 ◽  
Vol 4 (3) ◽  
pp. 53
Author(s):  
Yi Peng Toh ◽  
Emilie Dion ◽  
Antónia Monteiro
Keyword(s):  
Cognitive Abilities ◽  
Rna Extraction ◽  
Fruit Fly ◽  
Neural Mechanisms ◽  
Large Set ◽  
Bicyclus Anynana ◽  
Lepidopteran Species ◽  
Sensory Modalities ◽  
Olfactory Preferences ◽  
Adult Butterfly

Butterflies possess impressive cognitive abilities, and investigations into the neural mechanisms underlying these abilities are increasingly being conducted. Exploring butterfly neurobiology may require the isolation of larval, pupal, and/or adult brains for further molecular and histological experiments. This procedure has been largely described in the fruit fly, but a detailed description of butterfly brain dissections is still lacking. Here, we provide a detailed written and video protocol for the removal of Bicyclus anynana adult, pupal, and larval brains. This species is gradually becoming a popular model because it uses a large set of sensory modalities, displays plastic and hormonally controlled courtship behaviour, and learns visual mate preference and olfactory preferences that can be passed on to its offspring. The extracted brain can be used for downstream analyses, such as immunostaining, DNA or RNA extraction, and the procedure can be easily adapted to other lepidopteran species and life stages.

scholarly journals Signal detection: applying analysis methods from psychology to animal behaviour

2020 ◽  
Vol 375 (1802) ◽  
pp. 20190480 ◽  
Author(s):  
Christian J. Sumner ◽  
Seirian Sumner
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Sensory Information ◽  
Experimental Tests ◽  
Detection Theory ◽  
Animal Behaviour ◽  
Laboratory Animals ◽  
Natural Environments ◽  
Recognition Systems ◽  
Psychological Studies

Conspecific acceptance thresholds (Reeve 1989 Am. Nat. 133 , 407–435), which have been widely applied to explain ecological behaviour in animals, proposed how sensory information, prior information and the costs of decisions determine actions. Signal detection theory (Green & Swets 1966 Signal detection theory and psychophysics ; SDT), which forms the basis of CAT models, has been widely used in psychological studies to partition the ability to discriminate sensory information from the action made as a result of it. In this article, we will review the application of SDT in interpreting the behaviour of laboratory animals trained in operant conditioning tasks and then consider its potential in ecological studies of animal behaviour in natural environments. Focusing on the nest-mate recognition systems exhibited by social insects, we show how the quantitative application of SDT has the potential to transform acceptance rate data into independent indices of cue sensitivity and decision criterion (also known as the acceptance threshold). However, further tests of the assumptions underlying SDT analysis are required. Overall, we argue that SDT, as conventionally applied in psychological studies, may provide clearer insights into the mechanistic basis of decision making and information processing in behavioural ecology. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

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