Event-related EEG/MEG synchronization and desynchronization: basic principles

Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties

Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183 · see citing works

THE BERGER RHYTHM: POTENTIAL CHANGES FROM THE OCCIPITAL LOBES IN MAN

ADRIAN, E. D., & MATTHEWS, B. H. C. (1934) · Brain · doi:10.1093/brain/57.4.355 · Cited by 1,396 · see citing works

Event-related synchronization (ERS) in the alpha band — an electrophysiological correlate of cortical idling: A review

Pfurtscheller, G., Stancák, A., & Neuper, C. (1996) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(96)00066-9 · Cited by 1,205 · see citing works

Memory processes, brain oscillations and EEG synchronization

Klimesch, W. (1996) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(96)00057-8 · Cited by 923 · see citing works

Evaluation of event-related desynchronization (ERD) preceding and following voluntary self-paced movement

Pfurtscheller, G., & Aranibar, A. (1979) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(79)90063-4 · Cited by 758 · see citing works

Alpha frequency, cognitive load and memory performance

Klimesch, W., Schimke, H., & Pfurtscheller, G. (1993) · Brain Topography · doi:10.1007/bf01128991 · Cited by 530 · see citing works

Updating P300: An integrative theory of P3a and P3b

Polich, J. (2007) · Clinical Neurophysiology · doi:10.1016/j.clinph.2007.04.019 · Cited by 7,919 · see citing works

EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces

Lawhern, V. J., Solon, A. J., Waytowich, N. R., Gordon, S. M., Hung, C. P., & Lance, B. J. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aace8c · Cited by 5,115 · see citing works

The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes

Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3241 · Cited by 4,225 · see citing works

Shaping Functional Architecture by Oscillatory Alpha Activity: Gating by Inhibition

Jensen, O., & Mazaheri, A. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00186 · Cited by 3,237 · see citing works

Brain Computer Interfaces, a Review

Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012) · Sensors · doi:10.3390/s120201211 · Cited by 2,143 · see citing works

Brain–machine interfaces: past, present and future

Lebedev, M. A., & Nicolelis, M. A. L. (2006) · Trends in Neurosciences · doi:10.1016/j.tins.2006.07.004 · Cited by 1,875 · see citing works

Moving magnetoencephalography towards real-world applications with a wearable system

Boto, E., Holmes, N., Leggett, J., Roberts, G., Shah, V., Meyer, S. S., Muñoz, L. D., Mullinger, K. J., Tierney, T. M., Bestmann, S., et al. (2018) · Nature · doi:10.1038/nature26147 · Cited by 1,377 · see citing works

Spectral fingerprints of large-scale neuronal interactions

Siegel, M., Donner, T. H., & Engel, A. K. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3137 · Cited by 1,295 · see citing works

EEG and MEG: Relevance to Neuroscience

Lopes da Silva, F. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.017 · Cited by 900 · see citing works

Multiclass Brain–Computer Interface Classification by Riemannian Geometry

Barachant, A., Bonnet, S., Congedo, M., & Jutten, C. (2012) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2172210 · Cited by 878 · see citing works

A supramodal accumulation-to-bound signal that determines perceptual decisions in humans

O'Connell, R. G., Dockree, P. M., & Kelly, S. P. (2012) · Nature Neuroscience · doi:10.1038/nn.3248 · Cited by 755 · see citing works

Increases in alpha oscillatory power reflect an active retinotopic mechanism for distracter suppression during sustained visuospatial attention

Kelly, S. P., Lalor, E. C., Reilly, R. B., & Foxe, J. J. (2006) · Journal of Neurophysiology · doi:10.1152/jn.01234.2005 · Cited by 715 · see citing works

Neurophysiological predictor of SMR-based BCI performance

Blankertz, B., Sannelli, C., Halder, S., Hammer, E. M., Kübler, A., Müller, K.-R., Curio, G., & Dickhaus, T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.022 · Cited by 674 · see citing works

Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain–computer interface

LaFleur, K., Cassady, K., Doud, A., Shades, K., Rogin, E., & He, B. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/4/046003 · Cited by 583 · see citing works

Cortex and memory: emergence of a new paradigm

Fuster, J. M. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21280 · Cited by 559 · see citing works

Frontal-midline theta from the perspective of hippocampal “theta”

Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. (2008) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2008.09.005 · Cited by 549 · see citing works

“Thought”–control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia

Pfurtscheller, G., Müller, G. R., Pfurtscheller, J., Gerner, H. J., & Rupp, R. (2003) · Neuroscience Letters · doi:10.1016/s0304-3940(03)00947-9 · Cited by 548 · see citing works

Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior

Cohen, M. X., & Donner, T. H. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00479.2013 · Cited by 494 · see citing works

Induced electrocorticographic gamma activity during auditory perception

Crone, N. E., Boatman, D., Gordon, B., & Hao, L. (2001) · Clinical Neurophysiology · doi:10.1016/s1388-2457(00)00545-9 · Cited by 494 · see citing works

Mental training enhances attentional stability: Neural and behavioral evidence

Lutz, A., Slagter, H. A., Rawlings, N. B., Francis, A. D., Greischar, L. L., & Davidson, R. J. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.1614-09.2009 · Cited by 489 · see citing works

Classification of covariance matrices using a Riemannian-based kernel for BCI applications

Barachant, A., Bonnet, S., Congedo, M., & Jutten, C. (2013) · Neurocomputing · doi:10.1016/j.neucom.2012.12.039 · Cited by 493 · 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

Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review

Congedo, M., Barachant, A., & Bhatia, R. (2017) · Brain-Computer Interfaces · doi:10.1080/2326263x.2017.1297192 · Cited by 456 · see citing works

Single-trial EEG–fMRI reveals the dynamics of cognitive function

Debener, S., Ullsperger, M., Siegel, M., & Engel, A. K. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.09.010 · Cited by 428 · see citing works

Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients

Donati, A. R. C., Shokur, S., Morya, E., Campos, D. S. F., Moioli, R. C., Gitti, C. M., Augusto, P. B., Tripodi, S., Pires, C. G., Pereira, G. A., et al. (2016) · Scientific Reports · doi:10.1038/srep30383 · Cited by 428 · see citing works

Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI‐BOLD signal in primary somatosensory and motor cortex

Ritter, P., Moosmann, M., & Villringer, A. (2009) · Human Brain Mapping · doi:10.1002/hbm.20585 · Cited by 400 · see citing works

Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function

Babiloni, F., Cincotti, F., Babiloni, C., Carducci, F., Mattia, D., Astolfi, L., Basilisco, A., Rossini, P. M., Ding, L., Ni, Y., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.036 · Cited by 412 · see citing works

A Hybrid BCI System Combining P300 and SSVEP and Its Application to Wheelchair Control

Li, Y., Pan, J., Wang, F., & Yu, Z. (2013) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2013.2270283 · Cited by 421 · see citing works

BCILAB: a platform for brain–computer interface development

Kothe, C. A., & Makeig, S. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/5/056014 · Cited by 412 · see citing works

Noninvasive neuroimaging enhances continuous neural tracking for robotic device control

Edelman, B. J., Meng, J., Suma, D., Zurn, C., Nagarajan, E., Baxter, B. S., Cline, C. C., & He, B. (2019) · Science Robotics · doi:10.1126/scirobotics.aaw6844 · Cited by 380 · see citing works

EEG source imaging enhances the decoding of complex right-hand motor imagery tasks

Edelman, B. J., Baxter, B., & He, B. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2467312 · Cited by 370 · see citing works

The Berlin Brain–Computer Interface: Non-Medical Uses of BCI Technology

Blankertz, B., Tangermann, M., Vidaurre, C., Fazli, S., Sannelli, C., Haufe, S., Maeder, C., Ramsey, L., Sturm, I., Curio, G., et al. (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00198 · Cited by 357 · see citing works

The Berlin brain-computer Interface: accurate performance from first-session in BCI-naive subjects

Blankertz, B., Losch, F., Krauledat, M., Dornhege, G., Curio, G., & Muller, K.-R. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.923152 · Cited by 338 · see citing works

The Utility of EEG Band Power Analysis in the Study of Infancy and Early Childhood

Saby, J. N., & Marshall, P. J. (2012) · Developmental Neuropsychology · doi:10.1080/87565641.2011.614663 · Cited by 333 · see citing works

Methodological considerations for studying neural oscillations

Donoghue, T., Schaworonkow, N., & Voytek, B. (2022) · European Journal of Neuroscience · doi:10.1111/ejn.15361 · Cited by 309 · see citing works

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

Neuper, C., Müller, G. R., Kübler, A., Birbaumer, N., & Pfurtscheller, G. (2003) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00387-5 · Cited by 317 · see citing works

Disordered connectivity in the autistic brain: Challenges for the ‘new psychophysiology’

Rippon, G., Brock, J., Brown, C., & Boucher, J. (2007) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2006.03.012 · Cited by 308 · see citing works

Electrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities

He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300 · see citing works

Fast and Slow Oscillations in Human Primary Motor Cortex Predict Oncoming Behaviorally Relevant Cues

Saleh, M., Reimer, J., Penn, R., Ojakangas, C. L., & Hatsopoulos, N. G. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.001 · Cited by 281 · see citing works

Mental Training as a Tool in the Neuroscientific Study of Brain and Cognitive Plasticity

Slagter, H. A., Davidson, R. J., & Lutz, A. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00017 · Cited by 288 · see citing works

Negative covariation between task-related responses in alpha/beta-band activity and BOLD in human sensorimotor cortex: An EEG and fMRI study of motor imagery and movements

Yuan, H., Liu, T., Szarkowski, R., Rios, C., Ashe, J., & He, B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.028 · Cited by 274 · see citing works

A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers

Zhang, X., Yao, L., Wang, X., Monaghan, J., McAlpine, D., & Zhang, Y. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc902 · Cited by 296 · see citing works

Beta and Gamma Rhythms in Human Auditory Cortex during Musical Beat Processing

Fujioka, T., Trainor, L. J., Large, E. W., & Ross, B. (2009) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2009.04779.x · Cited by 262 · see citing works

Psychological predictors of SMR-BCI performance

Hammer, E. M., Halder, S., Blankertz, B., Sannelli, C., Dickhaus, T., Kleih, S., Müller, K.-R., & Kübler, A. (2012) · Biological Psychology · doi:10.1016/j.biopsycho.2011.09.006 · Cited by 267 · see citing works

Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials

Waytowich, N., Lawhern, V. J., Garcia, J. O., Cummings, J., Faller, J., Sajda, P., & Vettel, J. M. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aae5d8 · Cited by 262 · see citing works

Emotion Recognition from Brain Signals Using Hybrid Adaptive Filtering and Higher Order Crossings Analysis

Petrantonakis, P. C., & Hadjileontiadis, L. J. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.7 · Cited by 260 · see citing works

Early Anticipation Lies behind the Speed of Response in Conversation

Magyari, L., Bastiaansen, M. C. M., de Ruiter, J. P., & Levinson, S. C. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00673 · Cited by 247 · see citing works

Electroencephalography (EEG)-based brain–computer interface (BCI): a 2-d virtual wheelchair control based on event-related desynchronization/synchronization and state control

Huang, D., Qian, K., Fei, D.-Y., Jia, W., Chen, X., & Bai, O. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2190299 · Cited by 237 · see citing works

eConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity

He, B., Dai, Y., Astolfi, L., Babiloni, F., Yuan, H., & Yang, L. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2010.11.015 · Cited by 229 · see citing works

Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms

He, B., Baxter, B., Edelman, B. J., Cline, C. C., & Ye, W. W. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2407272 · Cited by 233 · see citing works

Learning to modulate one’s own brain activity: The effect of spontaneous mental strategies

Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00695 · Cited by 225 · see citing works

Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery

Fujioka, T., Ross, B., & Trainor, L. J. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2397-15.2015 · Cited by 230 · see citing works

Attentional Modulation of Alpha/Beta and Gamma Oscillations Reflect Functionally Distinct Processes

Bauer, M., Stenner, M.-P., Friston, K. J., & Dolan, R. J. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.3474-13.2014 · Cited by 224 · see citing works

Enhanced Low-Latency Detection of Motor Intention From EEG for Closed-Loop Brain-Computer Interface Applications

Xu, R., Jiang, N., Lin, C., Mrachacz-Kersting, N., Dremstrup, K., & Farina, D. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2013.2294203 · Cited by 219 · see citing works

Functional connectivity of frontal cortex in healthy and ADHD children reflected in EEG coherence

Murias, M., Swanson, J. M., & Srinivasan, R. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl089 · Cited by 190 · see citing works

Human Brain Networks in Cognitive Decline: A Graph Theoretical Analysis of Cortical Connectivity from EEG Data

Vecchio, F., Miraglia, F., Marra, C., Quaranta, D., Vita, M. G., Bramanti, P., & Rossini, P. M. (2014) · Journal of Alzheimer's Disease · doi:10.3233/jad-132087 · Cited by 182 · see citing works

Autocalibration and recurrent adaptation: Towards a plug and play online ERD-BCI

Faller, J., Vidaurre, C., Solis-Escalante, T., Neuper, C., & Scherer, R. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2189584 · Cited by 180 · see citing works

A tool for functional brain imaging with lifespan compliance

Hill, R. M., Boto, E., Holmes, N., Hartley, C., Seedat, Z. A., Leggett, J., Roberts, G., Shah, V., Tierney, T. M., Woolrich, M. W., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12486-x · Cited by 180 · see citing works

FORCe: Fully online and automated artifact removal for brain-computer interfacing

Daly, I., Scherer, R., Billinger, M., & Muller-Putz, G. (2015) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2014.2346621 · Cited by 174 · see citing works

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography

Farzan, F., Vernet, M., Shafi, M. M. D., Rotenberg, A., Daskalakis, Z. J., & Pascual-Leone, A. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00073 · Cited by 173 · see citing works

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Murta, T., Leite, M., Carmichael, D. W., Figueiredo, P., & Lemieux, L. (2015) · Human Brain Mapping · doi:10.1002/hbm.22623 · Cited by 165 · see citing works

The role of brain oscillations as functional correlates of cognitive systems: a study of frontal inhibitory control in alcoholism

Kamarajan, C., Porjesz, B., Jones, K. A., Choi, K., Chorlian, D. B., Padmanabhapillai, A., Rangaswamy, M., Stimus, A. T., & Begleiter, H. (2004) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2003.09.004 · Cited by 167 · see citing works

Transferring brain-computer interfaces beyond the laboratory: Successful application control for motor-disabled users

Leeb, R., Perdikis, S., Tonin, L., Biasiucci, A., Tavella, M., Creatura, M., Molina, A., Al-Khodairy, A., Carlson, T., & Millán, J. D. R. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.08.004 · Cited by 166 · see citing works

On the classification of emotional biosignals evoked while viewing affective pictures: An integrated data-mining-based approach for healthcare applications

Frantzidis, C. A., Bratsas, C., Klados, M. A., Konstantinidis, E., Lithari, C. D., Vivas, A. B., Papadelis, C. L., Kaldoudi, E., Pappas, C., & Bamidis, P. D. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2038481 · Cited by 166 · see citing works

Neuroimaging-based approaches in the brain–computer interface

Min, B.-K., Marzelli, M. J., & Yoo, S.-S. (2010) · Trends in Biotechnology · doi:10.1016/j.tibtech.2010.08.002 · Cited by 150 · see citing works

The influence of leads on cognitive load and learning in a hypertext environment

Antonenko, P. D., & Niederhauser, D. S. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2009.10.014 · Cited by 154 · see citing works

Brains “in concert”: frontal oscillatory alpha rhythms and empathy in professional musicians

Babiloni, C., Buffo, P., Vecchio, F., Marzano, N., Del Percio, C., Spada, D., Rossi, S., Bruni, I., Rossini, P. M., & Perani, D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.008 · Cited by 136 · see citing works

Dynamic causal modelling of induced responses

Chen, C. C., Kiebel, S. J., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.026 · Cited by 136 · see citing works

Establishing a right frontal beta signature for stopping action in scalp EEG: Implications for testing inhibitory control in other task contexts

Wagner, J., Wessel, J. R., Ghahremani, A., & Aron, A. R. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01183 · Cited by 112 · see citing works

Paired Associative Stimulation Enforces the Communication between Interconnected Areas

Veniero, D., Ponzo, V., & Koch, G. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1777-13.2013 · Cited by 131 · see citing works

Data augmentation for motor imagery signal classification based on a hybrid neural network.

Zhang, K., Xu, G., Han, Z., Ma, K., Zheng, X., Chen, L., Duan, N., & Zhang, S. (2020) · Sensors · doi:10.3390/s20164485 · Cited by 130 · see citing works

Event-Related Potential, Time-frequency, and Functional Connectivity Facets of Local and Global Auditory Novelty Processing: An Intracranial Study in Humans

El Karoui, I., King, J.-R., Sitt, J., Meyniel, F., Van Gaal, S., Hasboun, D., Adam, C., Navarro, V., Baulac, M., Dehaene, S., et al. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu143 · Cited by 114 · see citing works

Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition

Faivre, N., Filevich, E., Solovey, G., Kühn, S., & Blanke, O. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.0322-17.2017 · Cited by 129 · see citing works

Cortical imaging of event-related (de)synchronization during online control of brain-computer interface using minimum-norm estimates in frequency domain

Yuan, H., Doud, A., Gururajan, A., & He, B. (2008) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2008.2003384 · Cited by 120 · see citing works

A phenomenology of meditation-induced light experiences: traditional buddhist and neurobiological perspectives

Lindahl, J. R., Kaplan, C. T., Winget, E. M., & Britton, W. B. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00973 · Cited by 120 · see citing works

Multimodal BCIs: Target Detection, Multidimensional Control, and Awareness Evaluation in Patients With Disorder of Consciousness

Li, Y., Pan, J., Long, J., Yu, T., Wang, F., Yu, Z., & Wu, W. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2469106 · Cited by 117 · see citing works

Brain-computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users

Holz, E. M., Höhne, J., Staiger-Sälzer, P., Tangermann, M., & Kübler, A. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.08.001 · Cited by 111 · see citing works

Now you'll feel it, now you won't: EEG rhythms predict the effectiveness of perceptual masking

Schubert, R., Haufe, S., Blankenburg, F., Villringer, A., & Curio, G. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.21174 · Cited by 100 · see citing works

Premotor cortex mediates perceptual performance

Callan, D., Callan, A., Gamez, M., Sato, M.-A., & Kawato, M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.027 · Cited by 104 · see citing works

Anticipatory cortical responses during the expectancy of a predictable painful stimulation. A high-resolution electroencephalography study

Babiloni, C., Brancucci, A., Babiloni, F., Capotosto, P., Carducci, F., Cincotti, F., Arendt‐Nielsen, L., Chen, A. C. N., & Rossini, P. M. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02851.x · Cited by 103 · see citing works

Progressive Training for Motor Imagery Brain-Computer Interfaces Using Gamification and Virtual Reality Embodiment

Škola, F., Tinková, S., & Liarokapis, F. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00329 · Cited by 102 · see citing works

Beta- and gamma-band activity reflect predictive coding in the processing of causal events

van Pelt, S., Heil, L., Kwisthout, J., Ondobaka, S., van Rooij, I., & Bekkering, H. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw017 · Cited by 98 · see citing works

Real-time EEG-based brain-computer interface to a virtual avatar enhances cortical involvement in human treadmill walking

Luu, T. P., Nakagome, S., He, Y., & Contreras-Vidal, J. L. (2017) · Scientific Reports · doi:10.1038/s41598-017-09187-0 · Cited by 101 · see citing works

The role of imitation in the observed heterogeneity in EEG mu rhythm in autism and typical development

Bernier, R., Aaronson, B., & McPartland, J. (2013) · Brain and Cognition · doi:10.1016/j.bandc.2013.02.008 · Cited by 98 · see citing works

Discrimination of motor imagery-induced EEG patterns in patients with complete spinal cord injury

Pfurtscheller, G., Linortner, P., Winkler, R., Korisek, G., & Müller-Putz, G. (2009) · Computational Intelligence and Neuroscience · doi:10.1155/2009/104180 · Cited by 88 · see citing works

The importance of cursive handwriting over typewriting for learning in the classroom: a high-density EEG study of 12-year-old children and young adults.

Ose Askvik, E., van der Weel, F. R. (., & van der Meer, A. L. H. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01810 · Cited by 86 · see citing works

Reciprocity and alignment: quantifying coupling in dynamic interactions

Dumas, G., & Fairhurst, M. T. (2021) · Royal Society Open Science · doi:10.1098/rsos.210138 · Cited by 88 · see citing works

Reorganization of cortical oscillatory dynamics underlying disinhibition in frontotemporal dementia

Hughes, L. E., Rittman, T., Robbins, T. W., & Rowe, J. B. (2018) · Brain · doi:10.1093/brain/awy176 · Cited by 81 · see citing works

Towards a user-friendly brain-computer interface: initial tests in ALS and PLS patients

Bai, O., Lin, P., Huang, D., Fei, D.-Y., & Floeter, M. K. (2010) · Clinical Neurophysiology · doi:10.1016/j.clinph.2010.02.157 · Cited by 80 · see citing works

Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom

Van der Weel, F. R. (., & Van der Meer, A. L. H. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1219945 · Cited by 85 · see citing works

Laminar dynamics of high amplitude beta bursts in human motor cortex

Bonaiuto, J. J., Little, S., Neymotin, S. A., Jones, S. R., Barnes, G. R., & Bestmann, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118479 · Cited by 76 · see citing works

Consistent spectral predictors for dynamic causal models of steady-state responses

Moran, R. J., Stephan, K. E., Dolan, R. J., & Friston, K. J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.012 · Cited by 75 · see citing works

Sleepwalking episodes are preceded by arousal-related activation in the cingulate motor area: EEG current density imaging

Januszko, P., Niemcewicz, S., Gajda, T., Wołyńczyk-Gmaj, D., Piotrowska, A. J., Gmaj, B., Piotrowski, T., & Szelenberger, W. (2016) · Clinical Neurophysiology · doi:10.1016/j.clinph.2015.01.014 · Cited by 74 · see citing works

Localization of electrophysiological responses to semantic and syntactic anomalies in language comprehension with MEG

Kielar, A., Panamsky, L., Links, K. A., & Meltzer, J. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.016 · Cited by 64 · see citing works

A New Generation of Brain-Computer Interface Based on Riemannian Geometry

Congedo, M., Barachant, A., & Andreev, A. (2013) · arXiv · doi:10.48550/arxiv.1310.8115 · Cited by 69 · see citing works

Only three fingers write, but the whole brain works: a high-density EEG study showing advantages of drawing over typing for learning.

van der Meer, A. L. H., & van der Weel, F. R. (. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00706 · Cited by 62 · see citing works

A motor association area in the depths of the central sulcus

Jensen, M. A., Huang, H., Valencia, G. O., Klassen, B. T., van den Boom, M. A., Kaufmann, T. J., Schalk, G., Brunner, P., Worrell, G. A., Hermes, D., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01346-z · Cited by 61 · see citing works

Prediction of gait intention from pre-movement EEG signals: a feasibility study

Shafiul Hasan, S. M., Siddiquee, M. R., Atri, R., Ramon, R., Marquez, J. S., & Bai, O. (2020) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-020-00675-5 · Cited by 63 · see citing works

Motor-commands decoding using peripheral nerve signals: a review

Hong, K.-S., Aziz, N., & Ghafoor, U. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aab383 · Cited by 63 · see citing works

Cognitive and Neural Correlates of Loneliness and Wisdom during Emotional Bias

Grennan, G., Balasubramani, P. P., Alim, F., Zafar-Khan, M., Lee, E. E., Jeste, D. V., & Mishra, J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab012 · Cited by 57 · see citing works