Neurofeedback Training for BCI Control

Brain–computer interfaces for communication and control

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Motor imagery and direct brain-computer communication

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Brain–machine interfaces: past, present and future

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A spelling device for the paralysed

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Neural mechanisms underlying brain waves: from neural membranes to networks

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Motor imagery activates primary sensorimotor area in humans

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Activation of human primary motor cortex during action observation: A neuromagnetic study

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The non-invasive Berlin Brain–Computer Interface: Fast acquisition of effective performance in untrained subjects

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EEG-based discrimination between imagination of right and left hand movement

Pfurtscheller, G., Neuper, C., Flotzinger, D., & Pregenzer, M. (1997) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(97)00080-1 · Cited by 904 · see citing works

Mu rhythm modulation during observation of an object-directed grasp

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Brain–Computer Communication: Motivation, Aim, and Impact of Exploring a Virtual Apartment

Leeb, R., Lee, F., Keinrath, C., Scherer, R., Bischof, H., & Pfurtscheller, G. (2007) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2007.906956 · Cited by 514 · see citing works

EEG-based neuroprosthesis control: A step towards clinical practice

Müller-Putz, G. R., Scherer, R., Pfurtscheller, G., & Rupp, R. (2005) · Neuroscience Letters · doi:10.1016/j.neulet.2005.03.021 · Cited by 477 · see citing works

Towards adaptive classification for BCI

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Motor imagery and action observation: Modulation of sensorimotor brain rhythms during mental control of a brain–computer interface

Neuper, C., Scherer, R., Wriessnegger, S. C., & Pfurtscheller, G. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.11.015 · Cited by 421 · see citing works

Hand Movement Direction Decoded from MEG and EEG

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Linear and nonlinear methods for brain-computer interfaces

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Brain-computer communication: Self-regulation of slow cortical potentials for verbal communication

Kübler, A., Neumann, N., Kaiser, J., Kotchoubey, B., Hinterberger, T., & Birbaumer, N. (2001) · Archives of Physical Medicine and Rehabilitation · doi:10.1053/apmr.2001.26621 · Cited by 351 · see citing works

An Asynchronously Controlled EEG-Based Virtual Keyboard: Improvement of the Spelling Rate

Scherer, R., Müller, G., Neuper, C., Graimann, B., & Pfurtscheller, G. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.827062 · Cited by 340 · see citing works

Suppression of seizures in an epileptic following sensorimotor EEG feedback training

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An auditory oddball (P300) spelling system for brain‐computer interfaces

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Basic Concepts and Clinical Findings in the Treatment of Seizure Disorders with EEG Operant Conditioning

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Clinical application of an EEG-based brain–computer interface: a case study in a patient with severe motor impairment

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A Brain–Computer Interface Controlled Auditory Event‐Related Potential (P300) Spelling System for Locked‐In Patients

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Learned self-regulation of EEG frequency components affects attention and event-related brain potentials in humans

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Action–perception connection and the cortical mu rhythm

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Annotation: Neurofeedback – train your brain to train behaviour

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Human Cortical Electroencephalography (EEG) Rhythms during the Observation of Simple Aimless Movements: A High-Resolution EEG Study

Babiloni, C., Babiloni, F., Carducci, F., Cincotti, F., Cocozza, G., Percio, C. D., Moretti, D. V., & Rossini, P. M. (2002) · NeuroImage · doi:10.1006/nimg.2002.1192 · Cited by 253 · see citing works

EEG evidence for mirror neuron activity during the observation of human and robot actions: Toward an analysis of the human qualities of interactive robots

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Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis

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Enhancement of Left-Right Sensorimotor EEG Differences During Feedback-Regulated Motor Imagery

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Walking from thought

Pfurtscheller, G., Leeb, R., Keinrath, C., Friedman, D. A., Neuper, C., Guger, C., & Slater, M. (2006) · Brain Research · doi:10.1016/j.brainres.2005.11.083 · Cited by 225 · see citing works

Motor imagery and EEG-based control of spelling devices and neuroprostheses

Neuper, C., Muller-Putz, G. R., Scherer, R., & Pfurtscheller, G. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)59025-9 · Cited by 209 · see citing works

The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome

Birbaumer, N., Hinterberger, T., Kübler, A., & Neumann, N. (2003) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2003.814439 · Cited by 196 · see citing works

A fully on-line adaptive BCI

Vidaurre, C., Schloogl, A., Cabeza, R., Scherer, R., & Pfurtscheller, G. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.873542 · Cited by 195 · see citing works

A brain-computer interface with vibrotactile biofeedback for haptic information

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Validating the efficacy of neurofeedback for optimising performance

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Neurofeedback treatment of epilepsy

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Learning to control brain rhythms: making a brain-computer interface possible

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Vibrotactile Feedback for Brain-Computer Interface Operation

Febo Cincotti, A., Kauhanen, L., Fabio Aloise, A., Palomäki, T., Caporusso, N., Jylänki, P., Donatella Mattia, A., Babiloni, F., Vanacker, G., Nuttin, M., et al. (2007) · Computational Intelligence and Neuroscience · doi:10.1155/2007/48937 · Cited by 160 · see citing works

Motor Cortex in Voluntary Movements: A Distributed System for Distributed Functions

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EEG-based communication and control: short-term role of feedback

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Critical validation studies of neurofeedback

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Somatomotor and visceromotor correlates of operantly conditioned 12–14 c/sec sensorimotor cortical activity

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Walking by Thinking: The Brainwaves Are Crucial, Not the Muscles!

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Neurofeedback for the management of attention-deficit/hyperactivity disorders.

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Critical Decision-Speed and Information Transfer in the “Graz Brain–Computer Interface”

Krausz, G., Scherer, R., Korisek, G., & Pfurtscheller, G. (2003) · Applied Psychophysiology and Biofeedback · doi:10.1023/a:1024637331493 · Cited by 90 · see citing works

An Auditory Brain-Computer Interface Based on the Self-Regulation of Slow Cortical Potentials

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Automated feature selection with a distinction sensitive learning vector quantizer

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EEG feedback training: Enhancement of somatosensory cortical activity

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Viewing Moving Objects in Virtual Reality Can Change the Dynamics of Sensorimotor EEG Rhythms

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Overcoming the barriers to effective treatment for attention-deficit/hyperactivity disorder: A neuro-educational approach

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UNCONSCIOUS OPERANT CONDITIONING IN THE PARADIGM OF BRAIN-COMPUTER INTERFACE BASED ON COLOR PERCEPTION

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Graz Brain-Computer Interface (BCI) II

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Predictors of seizure reduction after self-regulation of slow cortical potentials as a treatment of drug-resistant epilepsy

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Human Cortical Electroencephalography (EEG) Rhythms during the Observation of Simple Aimless Movements: A High-Resolution EEG Study

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Cardiac responses induced during thought-based control of a virtual environment

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Auditory Feedback for Brain Computer Interface Management – An EEG Data Sonification Approach

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The Effect of Moisture Absorption on the Fatigue Crack Propagation Resistance of Acrylic Bone Cement / Der Einfluβ der Flüssigkeitsabsorption auf die Bruchzähigkeit von Knochenzement

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Wheels of Motion

MacKay, W. A. (2004) · Frontiers in neuroscience · doi:10.1201/9780203503584.ch7 · Cited by 19 · see citing works

The Neural Underpinnings of Neurofeedback Training

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Auditory feedback of human EEG for direct brain-computer communication

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EEG ‐Based Brain‐Computer Interface System

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ResearchArticle Vibrotactile Feedback for Brain-Computer Interface Operation

Febo Cincotti, A., Kauhanen, L., Fabio Aloise, A., Palom, T., Caporusso, N., Jyl, P., Donatella Mattia, A., Babiloni, F., Vanacker, G., Nuttin, M., et al. (2007) · Cited by 9 · see citing works

EEG-based Brain-Computer Interface Systems and Signal Processing

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A review of classification algorithms for EEG-based brain–computer interfaces: A 10 year update

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Could Anyone Use a BCI?

Allison, B. Z., & Neuper, C. (2010) · Human-computer interaction series · doi:10.1007/978-1-84996-272-8_3 · Cited by 357 · see citing works

Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design

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Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features

Nguyen, C. H., Karavas, G. K., & Artemiadis, P. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa8235 · Cited by 289 · see citing works

Two Brains, One Game: Design and Evaluation of a Multiuser BCI Video Game Based on Motor Imagery

Bonnet, L., Lotte, F., & Lécuyer, A. (2013) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2012.2237173 · Cited by 187 · see citing works

Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns

Jeunet, C., N’Kaoua, B., Subramanian, S., Hachet, M., & Lotte, F. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143962 · Cited by 182 · see citing works

Brain computer interface based applications for training and rehabilitation of students with neurodevelopmental disorders. A literature review

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The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

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Advances in user-training for mental-imagery-based BCI control

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Review of real brain-controlled wheelchairs

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Brain enhancement through cognitive training: a new insight from brain connectome

Taya, F., Sun, Y., Babiloni, F., Thakor, N. V., & Bezerianos, A. (2015) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00044 · Cited by 102 · see citing works

Brain-Machine Interfaces: A Tale of Two Learners

Perdikis, S., & Millán, J. D. R. (2020) · IEEE Systems Man and Cybernetics Magazine · doi:10.1109/msmc.2019.2958200 · Cited by 87 · see citing works

Performance of Motor Imagery Brain-Computer Interface Based on Anodal Transcranial Direct Current Stimulation Modulation

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A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey

Zhu, H. Y., Hieu, N. Q., Hoang, D. T., Nguyen, D. N., & Lin, C. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3387124 · Cited by 75 · see citing works

Asynchronous BCI Based on Motor Imagery With Automated Calibration and Neurofeedback Training

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Using Recent BCI Literature to Deepen our Understanding of Clinical Neurofeedback: A Short Review

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Towards improved BCI based on human learning principles

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The effect of multimodal and enriched feedback on SMR-BCI performance

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Cooperation in mind: Motor imagery of joint and single actions is represented in different brain areas

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Continuous Tactile Feedback for Motor-Imagery Based Brain-Computer Interaction in a Multitasking Context

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Virtual reality for assessment of patients suffering chronic pain: a case study

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The Impact of Different Visual Feedbacks in User Training on Motor Imagery Control in BCI

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Comparison of subject-independent and subject-specific EEG-based BCI using LDA and SVM classifiers

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Consumer-Grade Electroencephalogram and Functional Near-Infrared Spectroscopy Neurofeedback Technologies for Mental Health and Wellbeing

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Benchmarking Brain-Computer Interfaces Outside the Laboratory: The Cybathlon 2016

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Improving Motor Imagery-Based Brain-Computer Interface Performance Based on Sensory Stimulation Training: An Approach Focused on Poorly Performing Users

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Walking Imagery Evaluation in Brain Computer Interfaces via a Multi-View Multi-Level Deep Polynomial Network

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Online detection of auditory attention with mobile EEG: closing the loop with neurofeedbackPreprint

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