Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity

Zander, TO; Krol, LR; Birbaumer, NP; Gramann, K

Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity

Zander, TO Krol, LR Birbaumer, NP Gramann, K

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Publication Type:: Journal Article
Citation:: Proceedings of the National Academy of Sciences of the United States of America, 2016, 113 (52), pp. 14898 - 14903
Issue Date:: 2016-12-27

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Field	Value	Language
dc.contributor.author	Zander, TO	en_US
dc.contributor.author	Krol, LR	en_US
dc.contributor.author	Birbaumer, NP	en_US
dc.contributor.author	Gramann, K https://orcid.org/0000-0003-2673-1832	en_US
dc.date.issued	2016-12-27	en_US
dc.identifier.citation	Proceedings of the National Academy of Sciences of the United States of America, 2016, 113 (52), pp. 14898 - 14903	en_US
dc.identifier.issn	0027-8424	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130166
dc.description.abstract	The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator'smindset. Neuroadaptive technology significantlywidens the communication bottleneck and has the potential to fundamentally change the way we interact with technology.	en_US
dc.relation.ispartof	Proceedings of the National Academy of Sciences of the United States of America	en_US
dc.relation.isbasedon	10.1073/pnas.1605155114	en_US
dc.subject.mesh	Brain	en_US
dc.subject.mesh	Prefrontal Cortex	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Electroencephalography	en_US
dc.subject.mesh	Evoked Potentials	en_US
dc.subject.mesh	Computer Systems	en_US
dc.subject.mesh	Computers	en_US
dc.subject.mesh	User-Computer Interface	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Machine Learning	en_US
dc.title	Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity	en_US
dc.type	Journal Article
utslib.citation.volume	52	en_US
utslib.citation.volume	113	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access
pubs.issue	52	en_US
pubs.publication-status	Published	en_US
pubs.volume	113	en_US

Abstract:

The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator'smindset. Neuroadaptive technology significantlywidens the communication bottleneck and has the potential to fundamentally change the way we interact with technology.

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http://hdl.handle.net/10453/130166