Towards a Conceptual Framework for Cognitive Probing

  • Laurens R. KrolEmail author
  • Thorsten O. Zander
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10727)


Cognitive probing combines the ability of computers to interpret ongoing measures of arbitrary brain activity, with the ability of those same computers to actively elicit cognitive responses from their users. Purposefully elicited responses can be interpreted in order to learn about the user, enable symbiotic and implicit interaction, and support neuroadaptive technology. We propose a working definition of cognitive probing that allows it to be generalised across different applications and disciplines.


Cognitive probing Brain-computer interface Neuroadaptive technology Implicit interaction Human-computer interaction 



Part of this work was supported by the Deutsche Forschungsgemeinschaft (ZA 821/3-1).


  1. 1.
    Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., Perelmouter, J., Taub, E., Flor, H.: A spelling device for the paralysed. Nature 398(6725), 297–298 (1999)CrossRefGoogle Scholar
  2. 2.
    Chavarriaga, R., Sobolewski, A., Millán, J.D.R.: Errare machinale est: the use of error-related potentials in brain-machine interfaces. Front. Neurosci. 8, 208 (2014).
  3. 3.
    Falkenstein, M., Hoormann, J., Christ, S., Hohnsbein, J.: ERP components on reaction errors and their functional significance: a tutorial. Biol. Psychol. 51(2–3), 87–107 (2000)CrossRefGoogle Scholar
  4. 4.
    Iturrate, I., Chavarriaga, R., Montesano, L., Minguez, J., Millán, J.D.R.: Teaching brain-machine interfaces as an alternative paradigm to neuroprosthetics control. Sci. Rep. 5, 13893 (2015).
  5. 5.
    Krol, L.R., Andreessen, L.M., Zander, T.O.: Passive brain-computer interfaces: a perspective on increased interactivity. In: Nam, C.S., Nijholt, A., Lotte, F. (eds.) Brain-Computer Interfaces Handbook: Technological and Theoretical Advances, pp. 69–86. CRC Press, Boca Raton (2018)Google Scholar
  6. 6.
    Krol, L.R., Zander, T.O.: Passive BCI-based neuroadaptive systems. In: Proceedings of the 7th Graz Brain-Computer Interface Conference 2017, pp. 248–253 (2017)Google Scholar
  7. 7.
    Müller-Putz, G.R., Pfurtscheller, G.: Control of an electrical prosthesis with an SSVEP-based BCI. IEEE Trans. Biomed. Eng. 55(1), 361–364 (2008)CrossRefGoogle Scholar
  8. 8.
    Parra, L.C., Spence, C.D., Gerson, A.D., Sajda, P.: Response error correction–a demonstration of improved human-machine performance using real-time EEG monitoring. IEEE Trans. Neural Syst. Rehabil. Eng. 11(2), 173–177 (2003)CrossRefGoogle Scholar
  9. 9.
    Wolpaw, J.R., Wolpaw, E.W.: Brain-computer interfaces: something new under the sun. In: Wolpaw, J.R., Wolpaw, E.W. (eds.) Brain-Computer Interfaces: Principles and Practice, pp. 3–12. Oxford University Press, Oxford (2012). Scholar
  10. 10.
    Zander, T.O., Andreessen, L.M., Berg, A., Bleuel, M., Pawlitzki, J., Zawallich, L., Krol, L.R., Gramann, K.: Evaluation of a dry EEG system for application of passive brain-computer interfaces in autonomous driving. Front. Hum. Neurosci. 11, 78 (2017). Scholar
  11. 11.
    Zander, T.O., Brönstrup, J., Lorenz, R., Krol, L.R.: Towards BCI-based implicit control in human–computer interaction. In: Fairclough, S.H., Gilleade, K. (eds.) Advances in Physiological Computing. HIS, pp. 67–90. Springer, London (2014). Scholar
  12. 12.
    Zander, T.O., Kothe, C.A.: Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general. J. Neural Eng. 8(2), 025005 (2011). Scholar
  13. 13.
    Zander, T.O., Kothe, C.A., Jatzev, S., Dashuber, R., Welke, S., De Filippis, M., Rötting, M.: Team PhyPA: developing applications for brain-computer interaction. In: Proceedings of the Brain-Computer Interfaces for HCI and Games Workshop at the SIGCHI Conference on Human Factors in Computing Systems (CHI) (2008)Google Scholar
  14. 14.
    Zander, T.O., Kothe, C.A., Welke, S., Rötting, M.: Enhancing human-machine systems with secondary input from passive brain-computer interfaces. In: Proceedings of the 4th International Brain-Computer Interface Workshop & Training Course, pp. 144–149. Verlag der Technischen Universität Graz, Graz (2008)Google Scholar
  15. 15.
    Zander, T.O., Krol, L.R., Birbaumer, N.P., Gramann, K.: Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity. Proc. Natl. Acad. Sci. 113(52), 14898–14903 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Biological Psychology and NeuroergonomicsTechnische Universität BerlinBerlinGermany

Personalised recommendations