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On the interpretation of weight vectors of linear models in multivariate neuroimaging

NeuroImage (Orlando, Fla.), 2014-02, Vol.87, p.96-110

2014

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The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

Frontiers in neuroscience, 2016-11, Vol.10, p.530-530

2016

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The point of no return in vetoing self-initiated movements

Proceedings of the National Academy of Sciences - PNAS, 2016-01, Vol.113 (4), p.1080-1085

2016

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Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli

PloS one, 2015-10, Vol.10 (10), p.e0141281-e0141281

2015

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SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters

NeuroImage (Orlando, Fla.), 2014-02, Vol.86, p.111-122

2014

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EEG predictors of covert vigilant attention

Journal of neural engineering, 2014-06, Vol.11 (3), p.035009-11

2014

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Unsupervised classification of operator workload from brain signals

Journal of neural engineering, 2016-06, Vol.13 (3), p.036008-036008

2016

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Slow feature analysis on retinal waves leads to V1 complex cells

PLoS computational biology, 2014-05, Vol.10 (5), p.e1003564-e1003564

2014

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Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces

Proceedings of the IEEE, 2015-06, Vol.103 (6), p.891-906

2015

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The (Un)reliability of Saliency Methods

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, p.267-280

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Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control

IEEE transactions on neural systems and rehabilitation engineering, 2015-07, Vol.23 (4), p.618-627

2015

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Involving motor capabilities in the formation of sensory space representations

PloS one, 2010-04, Vol.5 (4), p.e10377-e10377

2010

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Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience

Frontiers in neuroscience, 2010-01, Vol.4, p.179-179

2010

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Dimensionality reduction for the analysis of brain oscillations

NeuroImage (Orlando, Fla.), 2014-11, Vol.101, p.583-597

2014

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Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data

Proceedings of the IEEE, 2015-09, Vol.103 (9), p.1507-1530

2015

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Learning complex cell units from simulated prenatal retinal waves with slow feature analysis

BMC neuroscience, 2009-07, Vol.10 (S1), p.P129-P129, Article P129

2009

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Effect of higher frequency on the classification of steady-state visual evoked potentials

Journal of neural engineering, 2016-02, Vol.13 (1), p.016014-016014

2016

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User-centered design in brain–computer interfaces—A case study

Artificial intelligence in medicine, 2013-10, Vol.59 (2), p.71-80

2013

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Correction to "Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control" [Jul 15 618-627]

IEEE transactions on neural systems and rehabilitation engineering, 2015-11, Vol.23 (6), p.1128-1128

2015

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Slow Feature Analysis on Retinal Waves Leads to V1 Complex Cells: e1003564

PLoS computational biology, 2014-05, Vol.10 (5)

2014

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Natural stimuli improve auditory BCIs with respect to ergonomics and performance

Journal of neural engineering, 2012-08, Vol.9 (4), p.045003-045003

2012

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Finding brain oscillations with power dependencies in neuroimaging data

NeuroImage (Orlando, Fla.), 2014-08, Vol.96, p.334-348

2014

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Decoding of top-down cognitive processing for SSVEP-controlled BMI

Scientific reports, 2016-11, Vol.6 (1), p.36267-36267, Article 36267

2016

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Identifying Granger causal relationships between neural power dynamics and variables of interest

NeuroImage (Orlando, Fla.), 2015-05, Vol.111, p.489-504

2015

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Wyrm: A Brain-Computer Interface Toolbox in Python

Neuroinformatics (Totowa, N.J.), 2015-10, Vol.13 (4), p.471-486

2015

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On the interpretation of weight vectors of linear models in multivariate neuroimaging

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

The point of no return in vetoing self-initiated movements

Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli

SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters

EEG predictors of covert vigilant attention

Unsupervised classification of operator workload from brain signals

Slow feature analysis on retinal waves leads to V1 complex cells

Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces

The (Un)reliability of Saliency Methods

Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control

Involving motor capabilities in the formation of sensory space representations

Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience

Dimensionality reduction for the analysis of brain oscillations

Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data

Learning complex cell units from simulated prenatal retinal waves with slow feature analysis

Effect of higher frequency on the classification of steady-state visual evoked potentials

User-centered design in brain–computer interfaces—A case study

Correction to "Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control" [Jul 15 618-627]

Slow Feature Analysis on Retinal Waves Leads to V1 Complex Cells: e1003564

Natural stimuli improve auditory BCIs with respect to ergonomics and performance

Finding brain oscillations with power dependencies in neuroimaging data

Decoding of top-down cognitive processing for SSVEP-controlled BMI

Identifying Granger causal relationships between neural power dynamics and variables of interest

Wyrm: A Brain-Computer Interface Toolbox in Python

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