Towards hippocampal navigation for brain–computer interfaces

Jeremy Saal*, Maarten Christiaan Ottenhoff, Pieter L. Kubben, Albert J. Colon, Sophocles Goulis, Johannes P. van Dijk, Dean J. Krusienski, Christian Herff*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Automatic wheelchairs directly controlled by brain activity could provide autonomy to severely paralyzed individuals. Current approaches mostly rely on non-invasive measures of brain activity and translate individual commands into wheelchair movements. For example, an imagined movement of the right hand would steer the wheelchair to the right. No research has investigated decoding higher-order cognitive processes to accomplish wheelchair control. We envision an invasive neural prosthetic that could provide input for wheelchair control by decoding navigational intent from hippocampal signals. Navigation has been extensively investigated in hippocampal recordings, but not for the development of neural prostheses. Here we show that it is possible to train a decoder to classify virtual-movement speeds from hippocampal signals recorded during a virtual-navigation task. These results represent the first step toward exploring the feasibility of an invasive hippocampal BCI for wheelchair control.
Original languageEnglish
Article number14021
Number of pages7
JournalScientific Reports
Issue number1
Publication statusPublished - 1 Dec 2023


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