Scent marks as social signals inGalago crassicaudatus II. Discrimination between individuals by scent

1982 ◽  
Vol 8 (8) ◽  
pp. 1153-1165 ◽  
Author(s):  
Anne B. Clark
Keyword(s):  
Social Signals ◽  
Scent Marks

scholarly journals Olfactory contacts mediate plasticity in male aggression with variable male density

2016 ◽  
Vol 97 (2) ◽  
pp. 444-454 ◽  
Author(s):  
Nelika K. Hughes ◽  
Peter B. Banks
Keyword(s):  
Social Environment ◽  
Competitive Ability ◽  
House Mice ◽  
Social Signals ◽  
Scent Marks ◽  
Male Density ◽  
Periodic Contact ◽  
Physical Interactions ◽  
Fluctuating Populations ◽  
Male House

Abstract Males typically adjust their reproductive strategies based on the perceived density and relative abilities of nearby competitors. In high-density populations, repeated encounters facilitate reliable, learned associations between individuals and their relative competitive abilities. In contrast, opportunities to form such associations are limited when densities are low or in flux, increasing the risk that individuals will unintentionally engage in potentially costly interactions with higher-quality or aggressive opponents. To maximize their fitness, individuals in low-density and fluctuating populations therefore need a general way to assess their current social environment, and thus their relative competitive ability. Here, we investigate how olfactory social signals (scent marks) might perform this function. We manipulated the perceived social environment of isolated, male house mice ( Mus domesticus ) via their periodic contact with scent marks from 3 or 9 male conspecifics, or a control of no scents, over 15 days. We then paired them with an unknown opponent and examined how the diversity of recent scent contact mediated their behavior towards dominant or subordinate opponents. There was an overall pattern for increasing scent diversity to significantly reduce male mice’s aggression (tail rattling and lunging) towards their opponents, and also their willingness to engage in reciprocal investigation. Such cautiousness was not indicative of perceived subordinance, however; the diversity of recent scent contact did not affect mice’s investigation of their opponent’s scents, and some measures of aggression were greater when mice faced dominant opponents. These results suggest that house mice can use scent signals to assess their current social environment in the absence of physical interactions, modifying their behavior in ways that are predicted to reduce their risks of injury when the likelihood of encountering unknown opponents increases.

Does context matter? Effects of robot appearance and reliability on social attention differs based on lifelikeness of gaze task

2020 ◽  
Author(s):  
Abdulaziz Abubshait ◽  
Patrick P. Weis ◽  
Eva Wiese
Keyword(s):  
Cognitive Processing ◽  
Social Cognitive ◽  
Physical Appearance ◽  
Mental States ◽  
Social Attention ◽  
Social Cues ◽  
Social Signals ◽  
Mind Perception ◽  
The Social ◽  
Behavioral Features

Social signals, such as changes in gaze direction, are essential cues to predict others’ mental states and behaviors (i.e., mentalizing). Studies show that humans can mentalize with non-human agents when they perceive a mind in them (i.e., mind perception). Robots that physically and/or behaviorally resemble humans likely trigger mind perception, which enhances the relevance of social cues and improves social-cognitive performance. The current ex-periments examine whether the effect of physical and behavioral influencers of mind perception on social-cognitive processing is modulated by the lifelikeness of a social interaction. Participants interacted with robots of varying degrees of physical (humanlike vs. robot-like) and behavioral (reliable vs. random) human-likeness while the lifelikeness of a social attention task was manipulated across five experiments. The first four experiments manipulated lifelikeness via the physical realism of the robot images (Study 1 and 2), the biological plausibility of the social signals (Study 3), and the plausibility of the social con-text (Study 4). They showed that humanlike behavior affected social attention whereas appearance affected mind perception ratings. However, when the lifelikeness of the interaction was increased by using videos of a human and a robot sending the social cues in a realistic environment (Study 5), social attention mechanisms were affected both by physical appearance and behavioral features, while mind perception ratings were mainly affected by physical appearance. This indicates that in order to understand the effect of physical and behavioral features on social cognition, paradigms should be used that adequately simulate the lifelikeness of social interactions.

scholarly journals Lymphocytic Choriomeningitis Virus Alters the Expression of Male Mouse Scent Proteins

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1180
Author(s):  
Michael B. A. Oldstone ◽  
Brian C. Ware ◽  
Amanda Davidson ◽  
Mark C. Prescott ◽  
Robert J. Beynon ◽  
...  
Keyword(s):  
Mate Selection ◽  
Lymphocytic Choriomeningitis ◽  
T Cell Response ◽  
Mature Male ◽  
Cytotoxic T Cell ◽  
Scent Marks ◽  
High Concentration ◽  
Embryo Survival ◽  
Major Urinary Proteins ◽  
The Individual

Mature male mice produce a particularly high concentration of major urinary proteins (MUPs) in their scent marks that provide identity and status information to conspecifics. Darcin (MUP20) is inherently attractive to females and, by inducing rapid associative learning, leads to specific attraction to the individual male’s odour and location. Other polymorphic central MUPs, produced at much higher abundance, bind volatile ligands that are slowly released from a male’s scent marks, forming the male’s individual odour that females learn. Here, we show that infection of C57BL/6 males with LCMV WE variants (v2.2 or v54) alters MUP expression according to a male’s infection status and ability to clear the virus. MUP output is substantially reduced during acute adult infection with LCMV WE v2.2 and when males are persistently infected with LCMV WE v2.2 or v54. Infection differentially alters expression of darcin and, particularly, suppresses expression of a male’s central MUP signature. However, following clearance of acute v2.2 infection through a robust virus-specific CD8 cytotoxic T cell response that leads to immunity to the virus, males regain their normal mature male MUP pattern and exhibit enhanced MUP output by 30 days post-infection relative to uninfected controls. We discuss the likely impact of these changes in male MUP signals on female attraction and mate selection. As LCMV infection during pregnancy can substantially reduce embryo survival and lead to lifelong infection in surviving offspring, we speculate that females use LCMV-induced changes in MUP expression both to avoid direct infection from a male and to select mates able to develop immunity to local variants that will be inherited by their offspring.

scholarly journals Recognizing Human Races through Machine Learning—A Multi-Network, Multi-Features Study

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 195
Author(s):  
Adrian Sergiu Darabant ◽  
Diana Borza ◽  
Radu Danescu
Keyword(s):  
Race And Ethnicity ◽  
Large Scale ◽  
Recognition Rate ◽  
Social Signals ◽  
Image Characteristics ◽  
Race Effect ◽  
Race Ethnicity ◽  
The Impact ◽  
Facial Images ◽  
Ethnicity Classification

The human face holds a privileged position in multi-disciplinary research as it conveys much information—demographical attributes (age, race, gender, ethnicity), social signals, emotion expression, and so forth. Studies have shown that due to the distribution of ethnicity/race in training datasets, biometric algorithms suffer from “cross race effect”—their performance is better on subjects closer to the “country of origin” of the algorithm. The contributions of this paper are two-fold: (a) first, we gathered, annotated and made public a large-scale database of (over 175,000) facial images by automatically crawling the Internet for celebrities’ images belonging to various ethnicity/races, and (b) we trained and compared four state of the art convolutional neural networks on the problem of race and ethnicity classification. To the best of our knowledge, this is the largest, data-balanced, publicly-available face database annotated with race and ethnicity information. We also studied the impact of various face traits and image characteristics on the race/ethnicity deep learning classification methods and compared the obtained results with the ones extracted from psychological studies and anthropomorphic studies. Extensive tests were performed in order to determine the facial features to which the networks are sensitive to. These tests and a recognition rate of 96.64% on the problem of human race classification demonstrate the effectiveness of the proposed solution.

scholarly journals Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0174182
Author(s):  
Maurits Kaptein ◽  
Robin van Emden ◽  
Davide Iannuzzi
Keyword(s):  
Optimization Methods ◽  
Social Signals ◽  
Social Phenomena ◽  
Experimental Physics

Smiles as Multipurpose Social Signals

2017 ◽  
Vol 21 (11) ◽  
pp. 864-877 ◽  
Author(s):  
Jared Martin ◽  
Magdalena Rychlowska ◽  
Adrienne Wood ◽  
Paula Niedenthal
Keyword(s):  
Social Signals

Congestion Avoidance Routing Based on Large-Scale Social Signals

2016 ◽  
Vol 17 (9) ◽  
pp. 2613-2626 ◽  
Author(s):  
Kun He ◽  
Zhongzhi Xu ◽  
Pu Wang ◽  
Lianbo Deng ◽  
Lai Tu
Keyword(s):  
Large Scale ◽  
Congestion Avoidance ◽  
Social Signals
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