The Reality and Limitations of Implicit Control based on Passive Brain-Computer Interfacing
Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
Human Cognitive and Systems Neuroscience
Final Report Abstract
This project explored the possibilities and limitations of implicit interaction based on passive brain-computer interfaces (pBCIs). Implicit interaction refers to interaction that takes place between a human and a computer without that human being aware of it. pBCIs are devices that measure and decode human brain activity in order to detect naturally-occurring mental states. For example, a pBCI may detect from your brain activity when you are feeling tired, happy, stressed, or when you are confused about something. In implicit interaction based on pBCI, such decoded mental states are used to control a computer. In this project we emphasised the serious ethical, legal, and societal implications of such neu- roadaptive technology. For example, human beings have very little control over their emotional states: they cannot choose when to feel them, and cannot prevent a computer from detecting and using them. Because of these and other issues, we need a thorough understanding of what implicit interaction exactly is, and how it can be used—for good and bad. This project contributed to the field in three ways. 1) It established conceptual and the- oretical frameworks to interpret and discuss neuroadaptive technology. 2) It produced new analysis tools to help researchers develop and evaluate neuroadaptive technology. 3) It produced experimental results providing important insights. Conceptually, the project provided a categorisation of different possible neuroadaptive sys- tems, highlighting that these systems are increasingly autonomous. This potentially threatens human agency. Furthermore, cognitive probing was identified and defined as a specific method that computers can use to increase their autonomy even further. Methodologically, the project resulted in an open-source toolbox, called SEREEGA, that allows researchers to simulate brain activity. This allows analysis techniques to be evaluated in a way that is not possible using real-world data. It also allowed us to develop and evaluate a new pBCI analysis method. This project resulted in a method that can be used to visualise which brain areas a computer uses for implicit interaction. Experimentally, this project demonstrated that subjective value judgements can be decoded from brain activity without the human being aware of this happening. Using the method de- scribed above, we could identify the separate brain areas involved in these judgements. This demonstrated and emphasised the privacy-sensitive nature of neuroadaptive technology. The project resulted in the establishment of a conference series as well as a number of papers demonstrating and discussing all of the above.
Publications
- (2018). Passive Brain-Computer Interfaces: A Perspective on Increased Interactivity. In C. S. Nam, A. Nijholt, & F. Lotte (Eds.), Brain-Computer Interfaces Handbook: Technological and Theoretical Advances (pp. 69-86). Boca Raton, FL, USA: CRC Press. ISBN: 9781498773430
Krol, L. R., Andreessen, L. M., & Zander, T. O.
(See online at https://doi.org/10.1201/9781351231954) - (2018). SEREEGA: Simulating Event-Related EEG Activity. Journal of Neuroscience Methods, 309, 13-24
rol, L. R., Pawlitzki, J., Lotte, F., Gramann, K., & Zander, T. O.
(See online at https://doi.org/10.1016/j.jneumeth.2018.08.001) - (2018). Towards Classifier Visualisation in 3D Source Space. In 2018 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 71–76)
Krol, L. R., Mousavi, M., de Sa, V. R., & Zander, T. O.
(See online at https://doi.org/10.1109/SMC.2018.00022) - (2019). Salience versus Valence in Implicit Cursor Control: First Indications of Separate Cortical Processes. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 3913–3918)
Krol, L. R., Pawlitzki, J., Mousavi, M., Andreessen, L. M., & Zander, T. O.
(See online at https://doi.org/10.1109/SMC.2019.8913936) - (2020). Cognitive and affective probing: a tutorial and review of active learning for neuroadaptive technology. Journal of Neural Engineering, 17 (1), 012001
Krol, L. R., Haselager, P., & Zander, T. O.
(See online at https://doi.org/10.1088/1741-2552/ab5bb5)
