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

Overview of attention for article published in PLoS Computational Biology, September 2011
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Title
Monkeys and Humans Share a Common Computation for Face/Voice Integration
Published in
PLoS Computational Biology, September 2011
DOI 10.1371/journal.pcbi.1002165
Pubmed ID
Authors

Chandramouli Chandrasekaran, Luis Lemus, Andrea Trubanova, Matthias Gondan, Asif A. Ghazanfar

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.

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Geographical breakdown

Country Count As %
United States 6 5%
Germany 3 3%
Chile 1 <1%
United Kingdom 1 <1%
France 1 <1%
Spain 1 <1%
Belgium 1 <1%
Unknown 102 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 22%
Researcher 25 22%
Student > Master 16 14%
Student > Bachelor 8 7%
Professor > Associate Professor 6 5%
Other 18 16%
Unknown 17 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 21%
Psychology 23 20%
Neuroscience 19 16%
Medicine and Dentistry 7 6%
Linguistics 3 3%
Other 17 15%
Unknown 23 20%