Skip to main content

Monkeys and Humans Share a Common Computation for Face/Voice Integration

Author(s): Chandrasekaran, Chandramouli; Lemus, Luis; Trubanova, Andrea; Gondan, Matthias; Ghazanfar, Asif A.

To refer to this page use:
Abstract: Speech production involves the movement of the mouth and other regions of the face resulting in visual motion cues. These visual cues enhance intelligibility and detection of auditory speech. As such, face-to-face speech is fundamentally a multisensory phenomenon. If speech is fundamentally multisensory, it should be reflected in the evolution of vocal communication: similar behavioral effects should be observed in other primates. Old World monkeys share with humans vocal production biomechanics and communicate face-to-face with vocalizations. It is unknown, however, if they, too, combine faces and voices to enhance their perception of vocalizations. We show that they do: monkeys combine faces and voices in noisy environments to enhance their detection of vocalizations. Their behavior parallels that of humans performing an identical task. We explored what common computational mechanism(s) could explain the pattern of results we observed across species. Standard explanations or models such as the principle of inverse effectiveness and a "race" model failed to account for their behavior patterns. Conversely, a "superposition model", positing the linear summation of activity patterns in response to visual and auditory components of vocalizations, served as a straightforward but powerful explanatory mechanism for the observed behaviors in both species. As such, it represents a putative homologous mechanism for integrating faces and voices across primates.
Publication Date: 29-Sep-2011
Electronic Publication Date: 29-Sep-2011
Citation: Chandrasekaran, Chandramouli, Lemus, Luis, Trubanova, Andrea, Gondan, Matthias, Ghazanfar, Asif A. (2011). Monkeys and Humans Share a Common Computation for Face/Voice Integration. PLoS Computational Biology, 7 (9), e1002165 - e1002165. doi:10.1371/journal.pcbi.1002165
DOI: doi:10.1371/journal.pcbi.1002165
EISSN: 1553-7358
Pages: e1002165 - e1002165
Type of Material: Journal Article
Journal/Proceeding Title: PLoS Computational Biology
Version: Final published version. This is an open access article.

Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.