Stefan Haufe

Summary

Country: Germany

Publications

  1. doi request reprint On the interpretation of weight vectors of linear models in multivariate neuroimaging
    Stefan Haufe
    Fachgebiet Maschinelles Lernen, Technische Universitat Berlin, Germany Bernstein Focus Neurotechnology, Berlin, Germany Electronic address
    Neuroimage 87:96-110. 2014
  2. doi request reprint A critical assessment of connectivity measures for EEG data: a simulation study
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Franklinstr 28 29, 10587 Berlin, Germany
    Neuroimage 64:120-33. 2013
  3. pmc Open database of epileptic EEG with MRI and postoperational assessment of foci--a real world verification for the EEG inverse solutions
    Piotr Zwoliński
    Memorial Child Hospital, Warsaw, Poland
    Neuroinformatics 8:285-99. 2010
  4. doi request reprint EEG potentials predict upcoming emergency brakings during simulated driving
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Franklinstraße 28 29, D 10587 Berlin, Germany
    J Neural Eng 8:056001. 2011
  5. doi request reprint Large-scale EEG/MEG source localization with spatial flexibility
    Stefan Haufe
    Department of Computer Science, Berlin Institute of Technology, Berlin, Germany
    Neuroimage 54:851-9. 2011
  6. doi request reprint Optimizing event-related potential based brain-computer interfaces: a systematic evaluation of dynamic stopping methods
    Martijn Schreuder
    Machine Learning Laboratory, Berlin Institute of Technology, Marchstrasse 23, 10537, Berlin, Germany
    J Neural Eng 10:036025. 2013
  7. doi request reprint Combining sparsity and rotational invariance in EEG/MEG source reconstruction
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, TU Berlin, Franklinstr 28 29, D 10587 Berlin, Germany
    Neuroimage 42:726-38. 2008
  8. ncbi request reprint Modeling sparse connectivity between underlying brain sources for EEG/MEG
    Stefan Haufe
    Berlin Institute of Technology, Berlin 10623, Germany
    IEEE Trans Biomed Eng 57:1954-63. 2010
  9. doi request reprint Localization of class-related mu-rhythm desynchronization in motor imagery based brain-computer interface sessions
    Stefan Haufe
    Berlin Institute of Technology, Franklinstr 28 29, D 10587, Germany
    Conf Proc IEEE Eng Med Biol Soc 2010:5137-40. 2010
  10. doi request reprint Single-trial analysis and classification of ERP components--a tutorial
    Benjamin Blankertz
    Berlin Institute of Technology, Machine Learning Laboratory, Berlin, Germany
    Neuroimage 56:814-25. 2011

Collaborators

Detail Information

Publications16

  1. doi request reprint On the interpretation of weight vectors of linear models in multivariate neuroimaging
    Stefan Haufe
    Fachgebiet Maschinelles Lernen, Technische Universitat Berlin, Germany Bernstein Focus Neurotechnology, Berlin, Germany Electronic address
    Neuroimage 87:96-110. 2014
    ..We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses...
  2. doi request reprint A critical assessment of connectivity measures for EEG data: a simulation study
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Franklinstr 28 29, 10587 Berlin, Germany
    Neuroimage 64:120-33. 2013
    ..Integrating the insights of our study, we provide a guidance for measuring brain interaction from EEG data. Software for generating benchmark data is made available...
  3. pmc Open database of epileptic EEG with MRI and postoperational assessment of foci--a real world verification for the EEG inverse solutions
    Piotr Zwoliński
    Memorial Child Hospital, Warsaw, Poland
    Neuroinformatics 8:285-99. 2010
    ..It seems to offer a possibility of tracing the spatial evolution of seizures in time...
  4. doi request reprint EEG potentials predict upcoming emergency brakings during simulated driving
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Franklinstraße 28 29, D 10587 Berlin, Germany
    J Neural Eng 8:056001. 2011
    ....
  5. doi request reprint Large-scale EEG/MEG source localization with spatial flexibility
    Stefan Haufe
    Department of Computer Science, Berlin Institute of Technology, Berlin, Germany
    Neuroimage 54:851-9. 2011
    ..Our approach based on single-trial localization of complex Fourier coefficients yields class-specific focal sources in the sensorimotor cortices...
  6. doi request reprint Optimizing event-related potential based brain-computer interfaces: a systematic evaluation of dynamic stopping methods
    Martijn Schreuder
    Machine Learning Laboratory, Berlin Institute of Technology, Marchstrasse 23, 10537, Berlin, Germany
    J Neural Eng 10:036025. 2013
    ..Despite their high potential for BCI systems at the patient's bedside, those methods are typically ignored in current BCI literature. The goal of the current study is to assess the benefit of these methods...
  7. doi request reprint Combining sparsity and rotational invariance in EEG/MEG source reconstruction
    Stefan Haufe
    Machine Learning Group, Department of Computer Science, TU Berlin, Franklinstr 28 29, D 10587 Berlin, Germany
    Neuroimage 42:726-38. 2008
    ..Compared to its peers FVR was the only method that delivered correct location of the source in the somatosensory area of each hemisphere in accordance with neurophysiological prior knowledge...
  8. ncbi request reprint Modeling sparse connectivity between underlying brain sources for EEG/MEG
    Stefan Haufe
    Berlin Institute of Technology, Berlin 10623, Germany
    IEEE Trans Biomed Eng 57:1954-63. 2010
    ..We demonstrate the usefulness of SCSA with simulated data and compare it to a number of existing algorithms with excellent results...
  9. doi request reprint Localization of class-related mu-rhythm desynchronization in motor imagery based brain-computer interface sessions
    Stefan Haufe
    Berlin Institute of Technology, Franklinstr 28 29, D 10587, Germany
    Conf Proc IEEE Eng Med Biol Soc 2010:5137-40. 2010
    ..As a technical contribution, we extend S-FLEX to the multiple measurement case in a way that the activity of different frequency bins within the mu-band is coherently localized...
  10. doi request reprint Single-trial analysis and classification of ERP components--a tutorial
    Benjamin Blankertz
    Berlin Institute of Technology, Machine Learning Laboratory, Berlin, Germany
    Neuroimage 56:814-25. 2011
    ....
  11. doi request reprint SPoC: a novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters
    Sven Dähne
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Marchstr 23, 10587 Berlin, Germany Bernstein Center for Computational Neuroscience, Berlin, Germany Electronic address
    Neuroimage 86:111-22. 2014
    ....
  12. ncbi request reprint Now you'll feel it, now you won't: EEG rhythms predict the effectiveness of perceptual masking
    Ruth Schubert
    Neurophysics Group, Department of Neurology and Clinical Neurophysiology, Charite University Medicine Berlin, Berlin, Germany
    J Cogn Neurosci 21:2407-19. 2009
    ....
  13. ncbi request reprint Finding brain oscillations with power dependencies in neuroimaging data
    Sven Dähne
    Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany Bernstein Center for Computational Neuroscience, Berlin, Germany Electronic address
    Neuroimage 96:334-48. 2014
    ..In the analysis of real EEG recordings, we demonstrate excellent unsupervised discovery of meaningful power-to-power couplings, within as well as across subjects and frequency bands. ..
  14. ncbi request reprint Pre-stimulus sensorimotor rhythms influence brain-computer interface classification performance
    Cecilia L Maeder
    Berlin Institute of Technology, Machine Learning Laboratory, Germany
    IEEE Trans Neural Syst Rehabil Eng 20:653-62. 2012
    ..Our findings support the idea that exploiting information about the ongoing SMR might be the key to boosting performance in future SMR-BCI experiments and motor related tasks in general...
  15. pmc Automatic classification of artifactual ICA-components for artifact removal in EEG signals
    Irene Winkler
    Machine Learning Laboratory, Berlin Institute of Technology, Franklinstr, 28 29, 10587 Berlin, Germany
    Behav Brain Funct 7:30. 2011
    ..Existing ICA-based removal strategies depend on explicit recordings of an individual's artifacts or have not been shown to reliably identify muscle artifacts...
  16. doi request reprint Telemedical Interventional Monitoring in Heart Failure (TIM-HF), a randomized, controlled intervention trial investigating the impact of telemedicine on mortality in ambulatory patients with heart failure: study design
    Friedrich Koehler
    Department of Cardiology and Angiology, Centre for Cardiovascular Telemedicine, Charite Universitatsmedizin Berlin, Campus Mitte, Berlin, Germany
    Eur J Heart Fail 12:1354-62. 2010
    ..The mean follow-up was 21.5±7.2 months, with a minimum of 12 months. Perspective The study will provide important prospective outcome data on the impact of telemedical management in patients with CHF...