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Welcome to the Brain State Decoding Lab!

About the Brain State Decoding Lab


The Brain State Decoding Lab focuses on machine learning methods for the decoding of brain states in real-time. The Lab is headed by Dr. Michael Tangermann and embedded into both, the Dept. of Computer Science and the Cluster of Excellence BrainLinks-BrainTools.

Our research comprises:

1. Neurotechnological data analysis methods:
  • Single-trial data analysis with state-of-the-art machine learning methods
  • Adaptive unsupervised machine learning approaches to compensate non-stationarity of brain signals and to reduce calibration phases
  • Prediction of motor performance based on oscillatory feature   
  • Analysis of multimodal signals (e.g. neurophysiological, behavior, eye-tracking, heart rate variability, etc)
  • Classification and regression in the context of high-dimensional and noisy data
  • Protocols for adaptive stimulations
  • Automatic optimization of stimulus parameters
2. Application fields:
    • Foundations of Brain-computer interfaces (BCIs)
    • BCIs for communication and control
    • Closed-loop rehabilitation of motor deficits and of cognitive deficits (especially aphasia) after stroke (see the Projects section)
    • Online decoding of spatial auditory attention
    • Deep brain stimulation for Parkinsonian's disease (PD)
    • Optimization of human-machine interfaces

    Within the University of Freiburg there are several research groups, which are engaged in BCI and BMI research topics: