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Welcome to the Brain State Decoding Lab!

About the Brain State Decoding Lab

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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:

    http://www.bmi.uni-freiburg.de