Experientially Acquired Knowledge of the Self in a Nonhuman Primate



The pressures of developing and maintaining intricate social relationships may have led to the evolution of enhanced cognitive abilities in many social nonhuman species, particularly primates. Knowledge of the dominance ranks and social relationships of other individuals, for example, is important in evaluating one’s position in the prevailing affiliative and dominance networks within a primate society and could be acquired through direct or perceived experience. Allogrooming supplants among female bonnet macaques usually involve the subordinate female of a grooming dyad retreating at the approach of a third female, dominant to both members of the dyad, although, in a few exceptional cases, the dominant member of the dyad could, instead, retreat. Retreat by the dominant individual was observed to be positively correlated to the social attractiveness of her subordinate companion, indicating that individual females successfully evaluate social relationships among other group females. Logistic regression analysis revealed the probability of retreat of the dominant female to be significantly influenced by her own dominance rank and those of the other two interacting females. Individual macaques thus possess egotistical knowledge of their own positions, relative to those of others, in the social hierarchy and appear to, therefore, abstract and mentally represent their own personal attributes as well as those of other members of the group. The experiential acquisition of such cognitive knowledge of the self raises important questions about the possible mechanisms underlying the nature of this mental representation and the general ability to categorize social information in non-verbalizing animal species such as macaques.


Dominance Hierarchy Dominance Rank Rank Difference Dominant Female Triadic Interaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by a research grant on Generativity in Cognitive Networks from the Cognitive Science Research Initiative of the Department of Science and Technology of the Government of India. I would like to thank Filippo Aureli, Niranjan Joshi, Kaberi Kar Gupta, Madhusudan Katti, Arun Venkataraman, Frans de Waal and members of the Tuesday and Wednesday Groups for critical discussions that shaped this work. I am grateful to Samir Acharya, Patralika Chatterjee and Abhijit Chatterjee for valuable logistic support, to Madhav Gadgil for the original discussion that began this work, to Milind Watve who first suggested that I learn about coefficients of variation and to Dhruba Naug who painstakingly wrote all the computer programs for the original analysis. Finally, I would like to express my sincere gratitude to Niranjan Joshi and Kakoli Mukhopadhyay for their constant enthusiasm, support and positive criticism throughout my academic life in Bangalore.


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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.School of Natural and Engineering SciencesNational Institute of Advanced StudiesBangaloreIndia
  2. 2.Centre for NeuroscienceIndian Institute of ScienceBangaloreIndia
  3. 3.Nature Conservation FoundationMysoreIndia

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