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Biosystems
Volume 90, Issue 1, July-August 2007, Pages 263-272
 
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doi:10.1016/j.biosystems.2006.09.030    
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Copyright © 2006 Elsevier Ireland Ltd All rights reserved.

Symbols are not uniquely human

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Sidarta Ribeiroa, 1, Angelo Loulab, c, 1, Ivan de Araújoa, Ricardo Gudwinb and João Queirozb, d, Corresponding Author Contact Information, E-mail The Corresponding Author

aInternational Institute of Neuroscience of Natal (IINN), Rua Professor Francisco Luciano de Oliveira, 2460, Bairro Candelária, 59066-060, Natal, RN, Brazil

bDepartment of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering (FEEC), State University of Campinas (UNICAMP), Av. Albert Einstein 400, 13083-852 Campinas, SP, Brazil

cInformatics Area, Department of Exact Sciences (DEXA), State University of Feira de Santana (UEFS), Km 3, BR116, Campus Universitário, 44031-460 Feira de Santana, BA, Brazil

dInstitute of Biology, Federal University of Bahia (UFBA), Rua Barão de Geremoabo, 147 Campus de Ondina, 40170-290 Salvador, BA, Brazil


Received 1 June 2006; 
revised 29 August 2006; 
accepted 2 September 2006. 
Available online 15 September 2006.

Abstract

Modern semiotics is a branch of logics that formally defines symbol-based communication. In recent years, the semiotic classification of signs has been invoked to support the notion that symbols are uniquely human. Here we show that alarm-calls such as those used by African vervet monkeys (Cercopithecus aethiops), logically satisfy the semiotic definition of symbol. We also show that the acquisition of vocal symbols in vervet monkeys can be successfully simulated by a computer program based on minimal semiotic and neurobiological constraints. The simulations indicate that learning depends on the tutor–predator ratio, and that apprentice-generated auditory mistakes in vocal symbol interpretation have little effect on the learning rates of apprentices (up to 80% of mistakes are tolerated). In contrast, just 10% of apprentice-generated visual mistakes in predator identification will prevent any vocal symbol to be correctly associated with a predator call in a stable manner. Tutor unreliability was also deleterious to vocal symbol learning: a mere 5% of “lying” tutors were able to completely disrupt symbol learning, invariably leading to the acquisition of incorrect associations by apprentices. Our investigation corroborates the existence of vocal symbols in a non-human species, and indicates that symbolic competence emerges spontaneously from classical associative learning mechanisms when the conditioned stimuli are self-generated, arbitrary and socially efficacious. We propose that more exclusive properties of human language, such as syntax, may derive from the evolution of higher-order domains for neural association, more removed from both the sensory input and the motor output, able to support the gradual complexification of grammatical categories into syntax.

Keywords: Symbols; Semiotic and neurobiological constraints; Computer simulation of symbol learning

Article Outline

1. Introduction
2. Methods
3. Results
4. Discussion
Acknowledgements
References





Corresponding Author Contact InformationCorresponding author. Tel.: +55 19 3788 3819/3706; fax: +55 19 3289 1395.
1 These authors contributed equally to this work.

Biosystems
Volume 90, Issue 1, July-August 2007, Pages 263-272
 
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