Dr Tibor Auer

Research Fellow

Academic and research departments

School of Psychology.


In the media

Automatic analysis (aa): efficient and transparent multimodal neuroimaging
NeuroInformatics 2016


Research interests

My publications


  1. Auer, T., & Frahm, J. (2011). Confounding factors in neurofeedback training based on fMRI of motor imagery. Neuroscience Letters, 500(500), e32. doi:10.1016/j.neulet.2011.05.160
  2. Dewiputri, W. I., & Auer, T. (2013). Functional magnetic resonance imaging (FMRI) neurofeedback: implementations and applications. Malays J Med Sci, 20(5), 5-15.
  3. Gevensleben, H., Albrecht, B., Lutcke, H., Auer, T., Dewiputri, W. I., Schweizer, R., . . . Rothenberger, A. (2014). Neurofeedback of slow cortical potentials: neural mechanisms and feasibility of a placebo-controlled design in healthy adults. Front Hum Neurosci, 8, 990. doi:10.3389/fnhum.2014.00990
  4. Auer, T., Schweizer, R., & Frahm, J. (2015). Training Efficiency and Transfer Success in an Extended Real-Time Functional MRI Neurofeedback Training of the Somatomotor Cortex of Healthy Subjects. Front Hum Neurosci, 9, 547. doi:10.3389/fnhum.2015.00547
  5. Auer, T., Dewiputri, W. I., Frahm, J., & Schweizer, R. (2018). Higher-order Brain Areas Associated with Real-time Functional MRI Neurofeedback Training of the Somato-motor Cortex. Neuroscience, 378, 22-33. doi:10.1016/j.neuroscience.2016.04.034
  6. Bazanova, O. M., Auer, T., & Sapina, E. A. (2018). On the Efficiency of Individualized Theta/Beta Ratio Neurofeedback Combined with Forehead EMG Training in ADHD Children. Front Hum Neurosci, 12, 3. doi:10.3389/fnhum.2018.00003
  7. Reiner, M., Gruzelier, J., Bamidis, P. D., & Auer, T. (2018). The Science of Neurofeedback: Learnability and Effects. Neuroscience, 378, 1-10. doi:10.1016/j.neuroscience.2018.04.024
  8. Ros, T., Enriquez-Gepper, S., Zotev, V., …, Thibault, R. (2019). Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). PsyArXiv, doi: 10.31234/osf.io/nyx84
  9. Haugg, A., Sladky, R., Skouras, S., …, Scharnowski, F. (2020). Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity? bioRxiv, doi: 10.1101/2020.01.15.906388