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Department of Psychology

Enya Weidner

Support with experimental work in our neurophysiology labs

Target audience 

  • Researchers with interest in conducting studies/ experiments in one of the neuropsychological labs of the various work groups (AEs) and the respective data analysis
  • Graduate and undergraduate students (in particular for Bachelor/ Master/ Doctoral thesis and experimental hands-on courses) 

Open consultation hours

Tue 11 - 13 Uhr in UHG T4-134 

Contact

Dipl.-Inform. Andrea Finke
Email: neurolabs-psy@uni-bielefeld.de

  

Consultation topics


Measurement technology

  • EEG
  • EMG
  • Eye-tracking
  • Additional/ peripheral physiological signals (e.g., Galvanic Skin Response - GSR, heart rate, etc.)

Setup of experiments 

  • Stimulus presentations on a screen (e.g., with Psychopy)
  • Virtual Reality (VR), Augmented Reality (AR)
  • Temporal synchronization of different modalities / sensors (e.g., EEG and eye-tracking)
  • Hyperscanning (simultaneous measurement of two or more subjects)

 

Data processing and analysis
 

Tools:

  • Matlab, Python, R
  • For all tools: Usage of specific tool boxes/ packages (e.g., EEGLAB, mne) and/ or programming of individual functions and scripts 

Methods:

  • Synchronization of different modalities and their joint analysis
  • Data visualization (incl. high-dimensional data), generation of plots and other visuals for publications and thesis
  • Event-related potentials (ERP)
  • Temporal filters (bandpass and notch)
  • Spectral analysis/ frequency transforms (e.g., Multi Taper, wavelets, parametric spectral analysis with autoregressive models, etc.)
  • Spatial filters (z.B. Laplacian, Current Source Density - CSD)
  • Mapping from sensor space to source space
  • Coherence and und Phase Locking (also in hyperscanning setups)
  • Graph-based network models

Machine Learning methods:

  • Classification (e.g., Fisher Discriminant - FDA, Support Vector Machines - SVM)
  • Datamining: Clustering (e.g., k-means, Gaussian Mixture Models - GMM), Principal Component Analysis - PCA, Independent Component Analysis - ICA, etc. 
  • Neural Networks and Deep Learning

Closed-loop systems with online (real-time) data analysis:

  • EEG-based and multi-modal Brain-Computer Interfaces (BCI)
  • Wearable BCI
  • Gaze-controlled (i.e., eye-tracking based) interfaces
  • Neurofeedback systems
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