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A Conversational Brain-Artificial Intelligence Interface

delete2026-01-01
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PRE
AI
M
Meunier, Anja
Z
Zak, Michal Robert
M
Munz, Lucas
S
Sofiya Garkot
M
Manuel Eder
J
Jiachen Xu
M
Moritz Grosse‐Wentrup *
DOI:10.1109/tnsre.2026.3703091delete
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Abstract

Abstract

En 中文
We introduce Brain-Artificial Intelligence Interfaces (BAIs) as a new class of Brain-Computer Interfaces (BCIs). Unlike conventional BCIs, which rely on intact cognitive capabilities, BAIs leverage the power of artificial intelligence to replace parts of the neuro-cognitive processing pipeline. BAIs allow users to accomplish complex tasks by providing high-level intentions, while a pre-trained AI agent determines low-level details. This approach enlarges the target audience of BCIs to individuals with cognitive impairments, a population often excluded from the benefits of conventional BCIs. We present the general concept of BAIs and illustrate the potential of this new approach with a Conversational BAI based on electroencephalography (EEG), termed EEGChat. In particular, we show in an experiment with simulated phone conversations that the Conversational BAI enables complex communication without the need to be able to generate language. Our work thus demonstrates the ability of a speech neuroprosthesis to enable fluent communication in realistic scenarios with non-invasive technologies.
Keywords:
Brain-computer interfaces
Modeling
Decoding
Computers
Artificial intelligence
Training
Speech
Timing
Electroencephalography
Tuning
Aphasia
assistive technologies
brain-AI interface
brain-computer interfaces
human computer interaction

Journal

IEEE Transactions on Neural Systems and Rehabilitation Engineering cover
IEEE Transactions on Neural Systems and Rehabilitation Engineering
IF:
5.2
Papers:
562
Citations:
1.6W

Organization

U
University of Vienna
Scholars:
523
Papers: 241
Citations: 0
Cited Papers

Cited Papers

No cited papers available