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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Text Sequence Stimulation for High-Speed and Comfortable SSVEP-BCI.

Cyborg and bionic systems (Washington, D.C.)·2026
Same author

A color-coded SSVEP-based brain-computer interface.

Journal of neural engineering·2026
Same author

The application effect of the 5E-microteaching integration model in the standardized training of general practitioners.

Frontiers in medicine·2026
Same author

Can the Use of Telehealth Guidance Services Reduce Depressive Symptoms Among Family Caregivers of Older Adults with Cognitive Impairment? A Moderated-Mediation Model.

Healthcare (Basel, Switzerland)·2026
Same author

Research on the drilling pipe health monitoring and intelligent life prediction management platform.

Scientific reports·2026
Same author

A High-Speed Visual BCI Based on Hybrid Frequency-Phase-Space Encoding and High-Density EEG Decoding.

Cyborg and bionic systems (Washington, D.C.)·2026

Related Experiment Video

Updated: Jul 23, 2025

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
08:25

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

10.8K

A sub-region combination scheme for spatial coding in a high-frequency SSVEP-based BCI.

Ruochen Hu1, Gege Ming2,3, Yijun Wang2,3,4

  • 1Department of Biomedical Engineering, Tsinghua University, Beijing, People's Republic of China.

Journal of Neural Engineering
|July 19, 2023
PubMed
Summary

This study developed a novel spatial coding scheme for high-frequency steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs). The findings demonstrate that sub-region SSVEP responses can predict joint region responses, enabling effective BCI operation.

Keywords:
brain-computer interfacesspatial codingsteady-state visual evoked potentialssub-region combination

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K

Related Experiment Videos

Last Updated: Jul 23, 2025

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
08:25

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

10.8K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Spatial coding is crucial for enhancing steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs).
  • Understanding the relationship between local and global visual field stimulation is key to optimizing SSVEP responses.
  • Existing methods may not fully leverage spatial information for BCI performance.

Purpose of the Study:

  • To develop and evaluate a novel sub-region combination scheme for spatial coding in high-frequency SSVEP-BCIs.
  • To investigate if SSVEPs generated by stimulating individual sub-regions can predict responses from combined joint regions.
  • To assess the performance of a spatially-coded BCI paradigm using this scheme.

Main Methods:

  • An annular visual field was divided into eight sub-regions, with 60 Hz visual stimuli presented to individual and combined regions.
  • SSVEP responses from sub-regions were superimposed to simulate responses from joint regions.
  • A four-class spatially-coded BCI paradigm was used for offline and online performance evaluation.

Main Results:

  • The proposed scheme successfully implemented a spatially-coded visual BCI with satisfactory performance and imperceptible flicker.
  • Offline analysis showed classification accuracy of 89.69 ± 8.75% and an information transfer rate (ITR) of 24.35 ± 7.09 bits/min with 3s data length.
  • Online BCI system achieved an average accuracy of 87.50 ± 9.13% and an ITR of 22.48 ± 6.71 bits/min with 3s data length.

Conclusions:

  • The study validates the feasibility of predicting joint region SSVEP responses from sub-region stimulations.
  • This spatial coding approach offers potential for extending to other frequency bands and developing more complex BCI paradigms.
  • The findings lay the groundwork for future advancements in SSVEP-based BCI technology.