Michael Tangermann
Head of the Lab, Associate Professor, PI
Donders Institute for Brain, Cognition and Behaviour
Former positions
- 2013-2020 University of Freiburg, Germany: Head of Brain State Decoding Lab, Computer Science Dept.
- 2019-2020 University of Freiburg, Germany: Substitute professor for the Autonomous Intelligent Systems Lab, Computer Science Dept.
- 2007-2013 Technical University Berlin, Germany: Postdoc researcher at Machine Learning Lab (head: Klaus-Robert Müller), Computer Science Dept.
- 2005-2007 Fraunhofer Institute FIRST, Berlin, Germany: researcher at Intelligent Data Analysis Lab (head: Klaus-Robert Müller)
- 2000-2005 University of Tübingen, Germany: PhD student at Computer Engineering Lab (head: Wolfgang Rosenstiel), Wilhelm-Schickard-Institut for Informatics, in collaboration with the lab of Bernhard Schölkopf (now: Max-Planck Intitute for Empirical Inference, Tübingen) and the lab of Nils Bierbaumer, Institute for Medical Psychology, Tübingen)
Interests
- Artificial intelligence / machine learning
- Brain state decoding
- Brain-state modulation
- Domain-specific regularizations
- Embeddings, representation learning
- Translational research, neurotechnological applications
- Brain-computer interfacing
- Evoked potentials
- Oscillatory processes
- Deep brain stimulation
- Language processing, language rehabilitation
- Motor rehabilitation
- Motor performance prediction / decoding
Education
-
PhD Computer Science, 2007
University of Tübingen, Germany
-
Diploma Computer Science (Minor: Biology), 2000
University of Tübingen, Germany
Latest
- Identifying Good Donor Datasets for Transfer Learning Scenarios in Motor Imagery BCI
- Review of Deep Representation Learning Techniques for Brain-Computer Interfaces
- Open PhD Position
- Approximate UMAP allows for high-rate online visualization of high-dimensional data streams
- S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention
- Synthesizing EEG Signals from Event-Related Potential Paradigms with Conditional Diffusion Models
- Review of Deep Representation Learning Techniques for BCI
- Digital biomarkers for Parkinson's Disease
- Bringing deep learning decoding models to the lab
- Generative Models
- Two Open PhD Positions
- Approximate UMAP
- Kick-off European Doctoral Network for Neural Prostheses and Brain Research (EU MSCA program)
- Exploring new territory: Calibration-free decoding for c-VEP BCI
- Open PhD Position
- Transfer Learning between Motor Imagery Datasets Using Deep Learning - Validation of Framework and Comparison of Datasets
- Adaptation Strategies for Block-Toeplitz Regularized Linear Discriminant Analysis
- Language-training induced coherency effects in stroke patients with aphasia
- Influence of Artifacts upon Block-Toeplitz Regularized Covariance Matrices
- Influence of Tapering Strategies upon Block-Toeplitz LDA
- Influence of Dataset Size on Subclass-Aware Decoding of Word ERPs
- Language-training induced changes of ERPs (amplitude, peak delay, onset) in stroke patients with aphasia
- Language-training induced changes of peak frequencies in stroke patients with aphasia
- Unsupervised Mean-difference Maximization (UMM)
- EEG potentials evoked by deep brain stimulation in patients with treatment-resistant depression
- Neural network transfer learning with fast calibration for mental imagery decoding
- Platform for closed-loop deep brain stimulation research: DAREPLANE
- The influence of pitch modulation on the performance of a BCI-based language training system
- UMM: Unsupervised Classification of ERPs with Confidence
- An Embedding for EEG Signals Learned Using a Triplet Loss
- Project dareplane for closed-loop deep brain stimulation
- Electrophysiological footprint of slMFB-DBS in depression--study design and preliminary results
- Estimating person-specific neural correlates of mental rotation: A machine learning approach
- UMM: Unsupervised Mean-difference Maximization
- Learning to repair artifacts in brain signals
- Subclass-Aware Decoding of Word-Evoked Auditory Event-Related Potential Data
- Estimating ERP Classification Performance from Oscillations
- Language-training induced oscillatory effects in stroke patients with aphasia
- Introducing block-Toeplitz covariance matrices to remaster linear discriminant analysis for event-related potential brain–computer interfaces
- Decoding motor performance from non-neural data
- Decoding of hand force from EEG recordings
- Hand motor performance decoding using slow potentials
- Phonological scoring of non-standard speech
- Reinforcement learning under high noise and uncertainty
- Dutch Brain Interfaces Initiative DBI2
- Kick-off Dutch Brain Interface Initiative (NWO Gravitation Programme)
- Embedding Neurophysiological Signals
- BCI-supported language rehabilitation
- Looking for study participants
- Dareplane
- Adaptive deep brain stimulation of the superolateral medial forebrain bundle
- Deep representation learning
- Aphasia recovery by language training using a brain--computer interface: A proof-of-concept study
- Brain-Computer Interfaces: Novel applications and interactive technologies
- Introducing Block-Toeplitz Covariance Matrices to Remaster Linear Discriminant Analysis for Event-related Potential Brain-computer Interfaces
- Improving Covariance Matrices Derived from Tiny Training Datasets for the Classification of Event-Related Potentials with Linear Discriminant Analysis
- Manipulating single-trial motor performance in chronic stroke patients by closed-loop brain state interaction
- Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints
- Real-time data processing for brain-computer interfacing using optically pumped magnetometers.
- Recent advances in brain-computer interface research: A summary of the 2019 BCI Award and online BCI research activities
- A Robust Screen-Free Brain-Computer Interface for Robotic Object Selection
- A pilot study on data-driven adaptive deep brain stimulation in chronically implanted essential tremor patients
- Identifying controllable cortical neural markers with machine learning for adaptive deep brain stimulation in Parkinson’s disease
- Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback
- Unsupervised Learning in a BCI Chess Application Using Label Proportions and Expectation-Maximization
- A Simulated Environment for Studying Partial Observability in Novel Adaptive Deep Brain Stimulation
- Heterogeneity of Event-Related Potentials in a Screen-Free Brain-Computer Interface
- Learning User Preferences for Trajectories from Brain Signals
- Spatial filters for auditory evoked potentials transfer between different experimental conditions
- Learning User Preferences for Trajectories from Brain Signals
- Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filters
- A Simulated Environment for Early Development Stages of Reinforcement Learning Algorithms for Closed-Loop Deep Brain Stimulation
- An Easy-to-Use and Fast Assessment of Patient-Specific DBS-induced Changes in Hand Motor Control in Parkinson's Disease
- Extremely Reduced Data Sets Indicate Optimal Stimulation Parameters for Classification in Brain-Computer Interfaces
- Influence of User Tasks on EEG-Based Classification Performance in a Hazard Detection Paradigm
- Maschinelles Lernen
- Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Decoding Methods
- Rethinking BCI paradigm and machine learning algorithm as a symbiosis: zero calibration, guaranteed convergence and high decoding performance
- Two Player Online Brain-Controlled Chess
- Workshops of the seventh international brain-computer interface meeting: not getting lost in translation
- Eyes-Closed Increases the Usability of Brain-Computer Interfaces Based on Auditory Event-Related Potentials
- Characterizing Regularization Techniques for Spatial Filter Optimization in Oscillatory EEG Regression Problems
- 1-F-54 Post-hoc labeling of arbitrary EEG recordings for data-efficient evaluation of neural decoding methods
- 2-A-2 Adaptive deep brain stimulation: Optimization of treatment in essential tremor using electrocorticography data
- 2-D-25 BCI-based language training induces changes in ERP responses in chronic post-stroke aphasia patients
- 2-D-27 Closed-loop stimulus parameter optimization framework for event-related potential paradigms
- Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier]
- Guess What I Attend: Interface-free Object Selection Using Brain Signals
- Unsupervised learning for brain–computer interfaces based on event-related potentials
- Post-hoc labeling of arbitrary EEG recordings for data-efficient evaluation of neural decoding methods
- Decoding Hazardous Events in Driving Videos
- Tikhonov Regularization Enhances EEG-Based Spatial Filtering For Single-Trial Regression
- Deep Learning with Convolutional Neural Networks for EEG Decoding and Visualization
- Improving zero-training brain-computer interfaces by mixing model estimators
- Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG
- Challenging the assumption that auditory event-related potentials are independent and identically distributed
- Closed-Loop Deep Brain Stimulation System for an Animal Model of Parkinson's Disease: A Pilot Study
- Decoding Perceived Hazardousness from User's Brain States to Shape Human-Robot Interaction
- Designing and Understanding Convolutional Networks for Decoding Executed Movements from EEG
- Improving learning from label proportions by reducing the feature dimensionality
- Informative Oscillatory EEG Components and their Persistence in Time and Frequency
- Learning from Label Proportions in BCI -- a Symbiotic Design for Stimulus Preservation and Signal Decoding
- Learning from label proportions in brain-computer interfaces: online unsupervised learning with guarantees
- Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees
- Mixing two unsupervised estimators for event-related potential decoding: An online evaluation
- Subspace Decomposition in the Frequency Domain
- Time-Frequency Sensitivity Characterization of Single-Trial Oscillatory EEG Components
- Workshops of the Sixth International Brain--Computer Interface Meeting: brain--computer interfaces past, present, and future
- A novel BCI based rehabilitation approach for aphasia rehabilitation
- A User-Focused Study of Auditory P300 Brain-Computer Interface Design
- Abstracts der 24. Jahrestagung der DGSM -- P26 Versuchspersonenunabhängige Single-Trial-Erkennung von langsamen Wellen im Schlaf-EEG
- BCI-Approach for Cognitive Rehabilitation in Stroke: Pilot Data from Patient with Spatial Neglect
- EP 65. DBS-induced alpha desynchronization in the subthalamic nucleus of PD patients
- ERP Features Correlate with Reaction Time in a Covert-Attention Task
- ERP Responses of the Elderly for Bisyllabic Word Stimuli
- Hyperparameter Optimization for Machine Learning Problems in BCI
- Pre-Trial EEG-based Single-Trial Motor Performance Prediction to Enhance Neuroergonomics for a Hand Force Task
- Predicting Single-Trial Motor Performance from Oscillatory EEG in Chronic Stroke Patients
- Relevant Frequency Estimation in EEG Recordings for Source Power Co-Modulation
- Towards Non-Invasive Hybrid Brain-Computer Interfaces: Framework, Practice, Clinical Application and Beyond
- EEG Band Power Predicts Single-Trial Reaction Time in a Hand Motor Task
- Commonalities of Motor Performance Metrics are Revealed by Predictive Oscillatory EEG Components
- Improving our understanding of transfer-learning in ERP based BCI
- On the Influence of High-Pass Filtering on ICA-Based Artifact Reduction in EEG-ERP
- P186. Correlates to influence user performance in a hand motor rehabilitation task
- Probing Meaningfulness of Oscillatory EEG Components with Bootstrapping, Label Noise and Reduced Training Sets
- Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution
- True Zero-Training Brain-Computer Interfacing -- An Online Study
- Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller
- P374: Detecting spatial auditory attention in cocktail-party situations
- P827: Beyond P300: an auditory ERP paradigm with sequential stimulation
- Robust artifactual independent component classification for BCI practitioners
- Towards Aphasia Rehabilitation with BCI
- Towards User-friendly Spelling with an Auditory Brain-Computer Interface: The CharStreamer Paradigm
- Transferring Unsupervised Adaptive Classifiers Between Users of a Spatial Auditory Brain-Computer Interface
- Workshops of the fifth international brain-computer interface meeting: Defining the future
- Decoding cognitive brain states
- Brain-computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users
- Facing the challenge: Bringing brain-computer interfaces to end-users
- Optimizing ERP Based BCI - a Systematic Evaluation of Dynamic Stopping Methods
- The hybrid Brain-Computer Interface: a bridge to assistive technology?
- User-Centered Design in Brain-Computer Interfaces - a Case Study
- Zero Training for BCI -- Reality for BCI Systems Based on Event-Related Potentials
- Erste Ergebnisse wiederholter Brain-Computer Interface (BCI) Messungen bei einer langjährig vollständig gelähmten ALS-Patientin
- No surprise-fixed sequence event-related potentials for brain-computer interfaces
- Brain-Computer Interfaces and Visual Activity