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A dyadic brain model of ape gestural learning, production and representation

  • Brad Gasser
  • Michael ArbibEmail author
Original Paper
Part of the following topical collections:
  1. Evolving the study of gesture

Abstract

It has been argued that variation in gesture usage among apes is influenced either by differential sampling of an innate ‘gesture space’ (Hobaiter and Byrne in Anim Cogn 14:745–767, 2011) or through the ‘mutual shaping of behavior’ (Halina et al. in Anim Cogn 16(4):653–666, 2013) referred to as ontogenetic ritualization. In either case, learning must play some role in how individuals come to use particular gestures—either through reinforcement within the set of innately specified gestures, or through the ritualization of some action following periods of direct interaction between pairs of individuals. Building on a prior computational model detailing learning during ontogenetic ritualization (Arbib et al. in Philos Trans R Soc Lond B Biol Sci 369(1644):20130414, 2014,  https://doi.org/10.1098/rstb.2013.0414), we here present a single integrative dyadic brain model (simulating selected brain and body dynamics of two interacting apes) that can account for many observed gestural patterns, while additionally showing that both of the claimed paths toward competent gestural performance are predicated on social influences—even the usage of inherited gestures demands learning about others’ behaviors.

Keywords

Computational model Gesture Social learning Apes Ontogenetic ritualization Dyadic brain modeling 

Notes

Funding

This material is based in part on work supported by the National Science Foundation under Grant no. BCS-1343544 “INSPIRE Track 1: Action, Vision and Language, and their Brain Mechanisms in Evolutionary Relationship” (Michael A. Arbib, Principal Investigator).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

10071_2018_1228_MOESM1_ESM.docx (1.6 mb)
The Gesture and Behavior DataBase (GBDB) and resources for the behavioral sciences (DOCX 1600 KB)
10071_2018_1228_MOESM2_ESM.docx (611 kb)
Methods and implementation details (DOCX 611 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.USC Brain ProjectUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Neuroscience Graduate ProgramUniversity of Southern CaliforniaLos AngelesUSA
  3. 3.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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