Prediction Error

Contributors:

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Project

Description: In extended realities (VR/AR/MR) sampling body movements enables the design of natural interactions. In concert with neural markers, detecting where things start to feel off as well as building novel interactions is feasible. The core motivation of this research is to bring neuroscientific research findings to application, leveraging a variety of supplementary signals, such as body movements and other wearables, to design robust interactive experiences that feel natural.

Wiki

When using any of these resources in any form of publication please cite https://dl.acm.org/citation.cfm?id=3300657 and acknowledge the originating institution as: Department of Biopsychology and Neuroergonomics, Institute of Psychology and Ergonomics, TU Berlin, Germany. In the paper https://dl.acm.org/citation.cfm?id=3300657 we detected conflicts in visuo-haptic integration by analyzing event-re...

Files

Loading files...

Citation

Components

  • Experiment Code (Unity)

    Unity environment eliciting prediction error brain responses in an interactive reach-to-touch VR scenario.

    Recent Activity

    Loading logs...

  • Data: Behavior & EEG

    BIDS formatted EEG/MoBI data hosted on openneuro

    Recent Activity

    Loading logs...

  • Paper at ACM CHI'19

    Source material of CHI'19 paper: Detecting Visuo-Haptic Mismatches in Virtual Reality using the Prediction Error Negativity of Event-Related Brain Pot...

    Recent Activity

    Loading logs...

Tags

Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.