Unimodal statistical learning produces multimodal object-like representations
- Central European University, Hungary
- University of Cambridge, United Kingdom
Abstract
The concept of objects is fundamental to cognition and is defined by a consistent set of sensory properties and physical affordances. Although it is unknown how the abstract concept of an object emerges, most accounts assume that visual or haptic boundaries are crucial in this process. Here, we tested an alternative hypothesis that boundaries are not essential but simply reflect a more fundamental principle: consistent visual or haptic statistical properties. Using a novel visuo-haptic statistical learning paradigm, we familiarised participants with objects defined solely by across-scene statistics provided either visually or through physical interactions. We then tested them on both a visual familiarity and a haptic pulling task, thus measuring both within-modality learning and across-modality generalisation. Participants showed strong within-modality learning and 'zero-shot' across-modality generalisation which were highly correlated. Our results demonstrate that humans can segment scenes into objects, without any explicit boundary cues, using purely statistical information.
Data availability
The scripts for all of the analysis reported in the manuscript can be found here https://github.com/GaborLengyel/Visual-Haptic-Statistical-Learning. There is a README file that explains both where the data can be found (Open Science Framework https://osf.io/456qb/) and how to run the analysis.
Article and author information
Author details
Alexandros Pantelides
Funding
ERC Consolidator Grant (ERC-2016-COG/726090)
- Máté Lengyel
Royal Society Noreen Murray Professorship in Neurobiolog (RP120142)
- Daniel M Wolpert
EU-FP7 Marie Curie CIG (CIG 618918)
- József Fiser
Wellcome Trust: New Investigator Award (095621/Z/11/Z)
- Máté Lengyel
National Institutes of Health (NIH R21 HD088731)
- József Fiser
Wellcome Trust: Senior Investigator Award (097803/Z/11/Z)
- Daniel M Wolpert
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Jörn Diedrichsen, University of Western Ontario, Canada
Ethics
Human subjects: All participants gave informed consent. All experimental protocols were approved by the University of Cambridge Psychology Ethics Committee.
Version history
- Received: November 27, 2018
- Accepted: April 30, 2019
- Accepted Manuscript published: May 1, 2019 (version 1)
- Version of Record published: May 21, 2019 (version 2)
Copyright
© 2019, Lengyel et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Unimodal statistical learning produces multimodal object-like representations
eLife 8:e43942.
https://doi.org/10.7554/eLife.43942
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