Neurotechnology in Mental Health

Disorders of mental health are amongst the most pressing medical problem that our society faces. Phenomena such as cognitive deficits, depression or chronic pain are caused by disorders of the nervous system, but the mechanisms remain unclear. The TUM Innovation Network for Neurotechnology in Mental Health (NEUROTECH) develops new approaches and technologies to improve the precision of clinical diagnoses and the success of treatments for mental dysfunction.

The team uses electrophysiological methods to record and modulate brain activity at an extraordinary level of detail and combines them with cutting-edge tools from data science. The aim is not only to better understand and differentiate mental disorders, but also to create new, individualized treatment strategies for patients. The researchers are following strict ethical guidelines in all steps of their work and also investigate the ethical implications of disruptive technological innovations in mental health for the individual and entire societies.

Our Team

Prof. Dr. Simon Jacob (Translational Neurotechnology)

Doctoral theses

  • Implantable neuroelectronic interfaces (Fulvia Del Duca)
  • The neuronal mechanisms underlying syntactic processing in aphasia (Paolo Favero)
  • Modulating sleep, circadian rhythm and cognition in health and disease through sensory stimulation (Laura Hainke)
  • Cellular and circuit mechanisms of right hemispheric language functions in aphasia (Lisa Held)
  • Embedded ethics and social science for responsible neurotechnology (Franziska Schönweitz)
  • Analysis of correlates of pain and EEG signals (Özgün Turgut)
  • Neuronal Recordings from an Aphasic Patient: A Computational Model of Cortical Language Circuits (Felix Waitzmann)


  1. Ploner M, Buyx A, Gempt J, Gjorgijeva J, Müller R, Priller J, Rückert D, Wolfrum B, Jacob SN. "Reengineering neurotechnology: placing patients first", Nat Ment Health 1:5-7 (2023)
  2. Eisenkolb VM, Held LM, Utzschmid A, Lin XX, Krieg SM, Meyer B, Gempt J, Jacob SN. "Human acute microelectrode array recordings with broad cortical access, single-unit resolution, and parallel behavioral monitoring", Cell Rep 2;42(5):112467 (2023)
  3. Hiendlmeier L, Zurita F, Vogel J, Del Duca F, Al Boustani G, Peng H, Kopic I, Nikić M, Teshima TF, Wolfrum B. "4D-Printed Soft and Stretchable Self-Folding Cuff Electrodes for Small-Nerve Interfacing", Advanced Materials 35 (12), 2210206 (2023)
  4. Zurita F, Grob L, Erben A, Del Duca F, Clausen-Schaumann H, Sudhop S, Hayden O, Wolfrum B. "Fully 3D-Printed Cuff Electrode for Small Nerve Interfacing", Advanced Materials Technologies, 8 (3), 2200989 (2023)
  5. Zurita F, Del Duca F, Teshima T, Hiendlmeier L, Gebhardt M, Luksch H, Wolfrum B. "In vivo closed-loop control of a locust’s leg using nerve stimulation". Sci Rep 12, 10864 (2022)
  6. Gil Avila C, Bott FS, Tiemann L, Hohn VD, May ES, Nickel MM, Zebhauser PT, Gross J, Ploner M. "DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neurosciences", bioRxiv (2023)
  7. Bott FS, Nickel MM, Hohn VD, May ES, Gil Avila C, Tiemann L, Gross J, Ploner M. "Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain", Sci Adv 9:eadd7572 (2023)
  8. Zebhauser PT, Hohn VD, Ploner M. "Resting state EEG and MEG as biomarkers of chronic pain: a systematic review". Pain (in press, 2023).
  9. Hohn VD, Bott FS, May ES, Tiemann L, Fritzen C, Nickel MM, Gil Ávila C, Ploner M. "How do alpha oscillations shape the perception of pain? - An EEG-based neurofeedback study". PLoS Biol, Registered Report, in-principle accepted (2022)
  10. Müller R, Ruess AK, Schönweitz FB, Buyx A, Gil Avila C, Ploner M. “Minimizing Racial and Ethnic Bias in Neuroscience – Next steps for Global Collaboration”. Nat Neurosci (in press)