Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Mar 1, 2026

Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy
07:53

Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy

Published on: August 5, 2022

2.5K

Enhancement of Group Perception via a Collaborative Brain-Computer Interface.

Davide Valeriani, Riccardo Poli, Caterina Cinel

    IEEE Transactions on Bio-Medical Engineering
    |May 26, 2017
    PubMed
    Summary

    This study enhanced group performance in visual search using a hybrid collaborative brain-computer interface (cBCI). The cBCI, incorporating neural, eye-tracking, and response time data, significantly improved group decision accuracy over standard methods.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Decoding semantic categories: insights from an fMRI ALE meta analysis.

    Journal of neural engineering·2025
    Same author

    Novel sequential BCI speller based on ERPs and event-related slow cortical potentials.

    Journal of neural engineering·2025
    Same author

    Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools.

    Scientific data·2025
    Same author

    Special issue on brain-computer interfaces: highlighting research from the 10th International Brain-Computer Interface Meeting.

    Journal of neural engineering·2025
    Same author

    Editorial: Datasets for brain-computer interface applications, volume II.

    Frontiers in neuroscience·2025
    Same author

    Master classes of the tenth international brain-computer interface meeting: showcasing the research of BCI trainees.

    Journal of neural engineering·2025

    Area of Science:

    • Neuroscience
    • Human-Computer Interaction
    • Cognitive Science

    Background:

    • Group decision-making accuracy is crucial in various real-world scenarios.
    • Previous collaborative brain-computer interfaces (cBCIs) showed potential but required further enhancement for challenging tasks.
    • Optimizing group performance in complex cognitive tasks remains an active area of research.

    Purpose of the Study:

    • To improve group performance in a difficult visual search task using a hybrid collaborative brain-computer interface (cBCI).
    • To evaluate the effectiveness of integrating neural features, response times, and eye movement data within a cBCI framework.
    • To compare the accuracy of cBCI-assisted group decisions against traditional majority-based decisions.

    Main Methods:

    • Participants performed a visual search task with stimuli presented briefly (250 ms).

    More Related Videos

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
    04:44

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

    Published on: July 21, 2021

    5.1K
    Assessment and Communication for People with Disorders of Consciousness
    07:37

    Assessment and Communication for People with Disorders of Consciousness

    Published on: August 1, 2017

    9.7K

    Related Experiment Videos

    Last Updated: Mar 1, 2026

    Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy
    07:53

    Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy

    Published on: August 5, 2022

    2.5K
    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
    04:44

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

    Published on: July 21, 2021

    5.1K
    Assessment and Communication for People with Disorders of Consciousness
    07:37

    Assessment and Communication for People with Disorders of Consciousness

    Published on: August 1, 2017

    9.7K
  • Local temporal correlation common spatial pattern (LTCCSP) was employed to extract neural features from EEG data.
  • Feature vectors were augmented with response times and eye movement data; a classifier estimated individual confidence for a confidence-weighted majority vote.

    • Main Results:

    • The hybrid cBCI, utilizing LTCCSP neural features, response times, and eye movement data, significantly enhanced decision accuracy compared to prior systems.
    • cBCI-assisted groups demonstrated superior accuracy over identically sized non-BCI groups.
    • The system showed improved performance across various group sizes, even on a more demanding visual task.

    Conclusions:

    • Technological enhancements in the hybrid cBCI led to significant improvements in group decision-making accuracy.
    • The developed cBCI outperforms standard majority voting methods for group decisions in challenging tasks.
    • This advancement opens possibilities for real-world applications where minimizing decision errors is critical.