EconPapers    
Economics at your fingertips  
 

Computational modeling of human multisensory spatial representation by a neural architecture

Nicola Domenici, Valentina Sanguineti, Pietro Morerio, Claudio Campus, Alessio Del Bue, Monica Gori and Vittorio Murino

PLOS ONE, 2023, vol. 18, issue 3, 1-18

Abstract: Our brain constantly combines sensory information in unitary percept to build coherent representations of the environment. Even though this process could appear smooth, integrating sensory inputs from various sensory modalities must overcome several computational issues, such as recoding and statistical inferences problems. Following these assumptions, we developed a neural architecture replicating humans’ ability to use audiovisual spatial representations. We considered the well-known ventriloquist illusion as a benchmark to evaluate its phenomenological plausibility. Our model closely replicated human perceptual behavior, proving a truthful approximation of the brain’s ability to develop audiovisual spatial representations. Considering its ability to model audiovisual performance in a spatial localization task, we release our model in conjunction with the dataset we recorded for its validation. We believe it will be a powerful tool to model and better understand multisensory integration processes in experimental and rehabilitation environments.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280987 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 80987&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0280987

DOI: 10.1371/journal.pone.0280987

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().

 
Page updated 2025-06-07
Handle: RePEc:plo:pone00:0280987