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440 gorilla images11/20/2023 Grouping conspecifics into classes (categories) reduces the enormous amount of information in a complex social environment and enables the organism to react efficiently to a specific individual ( Zayan and Vauclair, 1998 Ghirlanda and Enquist, 2003 Lombardi, 2008).įor individual recognition (IR) subjects learn the individually distinctive phenotype of conspecifics (signature), store their mental representations as a single natural category (prototype) and assign specific properties to this individual ( Zayan, 1994 Yorzinski, 2017). Two different categories of class-level recognition have been described: (i) “receivers learn the signaller’s individually distinctive characteristics and associate these characteristics with inferred class-specific information about the signaller,” or (ii) “receivers match the signaller’s phenotype to an internal template associated with different classes” ( Tibbetts and Dale, 2007). Along this continuum, the ability to recognize conspecifics has been categorized into class-level recognition or individual recognition, and the latter might be seen as a special case of the former ( Tibbetts and Dale, 2007 Yorzinski, 2017). ![]() These different levels of distinctiveness describe an ascending continuum from simpler to increasingly complex social recognition. Social recognition is based on the process of dividing conspecifics into different categories, such as homo-vs. However, the higher number of trials in Te4 suggests that both groups formed the learning rule of choosing either the known (Group A) or the unknown goat (Group B) over the course of Te1 to Te3 and then failed after the rule was reversed, providing evidence that goats can associate 2D photos of conspecifics with real animals. The lack of spontaneous preferences for the photo of the familiar conspecific in the pretests of Te1 to Te3 in Group A, as well as the lack of differences in the number of trials to learn the discriminations between both groups, do not at first glance suggest that the goats established a correspondence between real conspecifics and their 2D representations. In Te4, in contrast, the animals took 403 and 385 trials, respectively, to learn the task. The goats learned the discriminations in Te1 to Te3 within two (Te1 and Te2) and three training days (Te3), respectively, and they needed between 91 and 174 trials to reach the learning criterion, with no statistically significant differences between the groups. Finally, in a reversal test (Te4) we reversed this principle. That is, the rewarded photo was familiar to Group A, but unfamiliar to Group B. ![]() Tests were presented as 4-choice tasks, with one photo from Group A (rewarded) plus three photos from Group B (distractors). ![]() Using a computer-controlled learning device, in three tests, goats of two experimental groups (A and B) had to discriminate portrait (Te1), profile (Te2) or headless body photos (Te3) of conspecifics. ![]() In the current study, we investigated whether goats are able to discriminate photos of familiar and unfamiliar conspecifics, whether they not only process the photos as visual stimuli, but also understand them as virtual copies of real conspecifics and whether they grasp the concept of familiarity. However, animals may discriminate the images merely as visual stimulus combinations without establishing referential relationships to the individuals depicted. To study individual recognition in animals, discrimination tasks are often conducted by presenting 2D images of real conspecifics.
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