> For the complete documentation index, see [llms.txt](https://library.xrguild.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://library.xrguild.org/current-peer-reviewed-immersive-technologies/towards-an-eye-brain-computer-interface-combining-gaze-with-the-stimulus-preceding-negativity.md). # Towards an Eye-Brain-Computer Interface: Combining Gaze with the Stimulus-Preceding Negativity ## Overview **Authors:** G S Rajshekar Reddy, Michael J Proulx, Leanne Hirshfield, Anthony Ries **Publication Date:** 11 May 2024 **Link:** [https://dl.acm.org/doi/full/10.1145/3613904.3641925]() **Keywords:** Human-centered computing, Virtual reality, Mixed / augmented reality, Accessibility technologies, Interaction techniques **Type:** Peer-Reviewed Journals/White Papers ## Summary Gaze-assisted interaction techniques enable intuitive selections without requiring manual pointing but can result in unintended selections, known as Midas touch. A confirmation trigger eliminates this issue but requires additional physical and conscious user effort. Brain-computer interfaces (BCIs), particularly passive BCIs harnessing anticipatory potentials such as the Stimulus-Preceding Negativity (SPN) - evoked when users anticipate a forthcoming stimulus - present an effortless implicit solution for selection confirmation. Within a VR context, our research uniquely demonstrates that SPN has the potential to decode intent towards the visually focused target. This work reinforce the scientific understanding of its mechanism by addressing a confounding factor - it demonstrates that the SPN is driven by the user’s intent to select the target, not by the stimulus feedback itself. Furthermore, it examines the effect of familiarly placed targets, finding that SPN may be evoked quicker as users acclimatize to target locations; a key insight for everyday BCIs. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://library.xrguild.org/current-peer-reviewed-immersive-technologies/towards-an-eye-brain-computer-interface-combining-gaze-with-the-stimulus-preceding-negativity.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.