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

Rotation-based metric on the Riemannian manifold of SPD matrices with applications to source data selection for brain-computer interface transfer learning.

Frontiers in human neuroscience·2026
Same author

Neural Speech Tracking with EEG: Integrating Acoustics and Linguistics for Hearing Aid Users.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Improving auditory attention decoding in noisy environments for listeners with hearing impairment through contrastive learning.

Journal of neural engineering·2025
Same author

Deep learning-based auditory attention decoding in listeners with hearing impairment<sup></sup>.

Journal of neural engineering·2024
Same author

Identifiability issues in estimating the impact of interventions on Covid-19 spread.

IFAC-PapersOnLine·2024
Same author

Improving EEG-based decoding of the locus of auditory attention through domain adaptation<sup></sup>.

Journal of neural engineering·2023
Same journal

Vowel acoustic parameters in speech assessment and rehabilitation of minimally verbal and speech-motor-impaired autistic children: a narrative review.

Frontiers in human neuroscience·2026
Same journal

Toward clinical translation of TMS-EEG: an integrative review of multidimensional neurophysiological measures.

Frontiers in human neuroscience·2026
Same journal

The causal efficacy of consciousness: a neuroscientific analysis and explanation.

Frontiers in human neuroscience·2026
Same journal

Temporal-oscillatory entrainment: a multi-timescale framework for rhythmic coordination from neural to social frequencies.

Frontiers in human neuroscience·2026
Same journal

Role of AQP4 in ameliorating heat stress-induced cellular injury in a cell line model through active heat acclimation.

Frontiers in human neuroscience·2026
Same journal

Correction: Cognitive state monitoring for neuroadaptive information visualization.

Frontiers in human neuroscience·2026
See all related articles

Related Experiment Video

Updated: Sep 3, 2025

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

784

Multi-Armed Bandits in Brain-Computer Interfaces.

Frida Heskebeck1, Carolina Bergeling2, Bo Bernhardsson1

  • 1Department of Automatic Control, Lund University, Lund, Sweden.

Frontiers in Human Neuroscience
|July 25, 2022
PubMed
Summary
This summary is machine-generated.

The multi-armed bandit (MAB) problem helps optimize decisions in Brain-Computer Interfaces (BCIs). This review explores MAB applications to enhance BCI performance during calibration and real-time use.

Keywords:
Brain-Computer Interface (BCI)calibrationmulti-armed bandit (MAB)real-time optimizationreinforcement learning

More Related Videos

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

9.2K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K

Related Experiment Videos

Last Updated: Sep 3, 2025

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

784
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

9.2K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K

Area of Science:

  • Neuroscience
  • Machine Learning
  • Human-Computer Interaction

Background:

  • The multi-armed bandit (MAB) problem involves optimizing sequential decisions under uncertainty.
  • MAB frameworks are relevant for adaptive systems like Brain-Computer Interfaces (BCIs).
  • Current MAB applications in BCIs are limited but show significant potential.

Purpose of the Study:

  • To introduce the multi-armed bandit (MAB) problem and its relevance to the Brain-Computer Interface (BCI) community.
  • To review existing MAB methodologies and their applicability to BCI systems.
  • To highlight current research and future directions for MAB in BCIs.

Main Methods:

  • Literature review of multi-armed bandit (MAB) algorithms.
  • Analysis of MAB problem formulations and standard solution methods.
  • Interpretation of MAB concepts within the context of Brain-Computer Interface (BCI) operations.

Main Results:

  • MAB offers a robust framework for optimizing decision-making in dynamic BCI environments.
  • Exploration of MAB's potential to improve BCI performance during both calibration and real-time use.
  • Identification of state-of-the-art MAB techniques applicable to BCI.

Conclusions:

  • Multi-armed bandits (MAB) present a promising avenue for advancing Brain-Computer Interface (BCI) technology.
  • Further research into MAB optimization can significantly enhance BCI adaptive capabilities.
  • This review provides a foundation for researchers exploring MABs in BCIs.