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Related Experiment Video

Updated: Jun 14, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

A Conversational Brain-Artificial Intelligence Interface.

Anja Meunier, Michal Robert Zak, Lucas Munz

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society

|June 12, 2026

Summary

This summary is machine-generated.

Brain-Artificial Intelligence Interfaces (BAIs) enable complex tasks by replacing neuro-cognitive processing with AI. This new approach allows individuals with cognitive impairments to communicate fluently using non-invasive technology.

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Published on: May 8, 2021

Area of Science:

Neuroscience
Artificial Intelligence
Biomedical Engineering

Background:

Conventional Brain-Computer Interfaces (BCIs) require intact cognitive functions.
Individuals with cognitive impairments are often excluded from BCI benefits.
There is a need for BCIs that accommodate cognitive deficits.

Purpose of the Study:

Introduce Brain-Artificial Intelligence Interfaces (BAIs) as a novel class of BCIs.
Demonstrate how AI can replace neuro-cognitive processing in BCIs.
Expand BCI accessibility to individuals with cognitive impairments.

Main Methods:

Defined BAIs as BCIs leveraging AI for neuro-cognitive pipeline replacement.
Developed a Conversational BAI (EEGChat) using electroencephalography (EEG).
Utilized a pre-trained AI agent to interpret high-level user intentions for low-level task execution.

Main Results:

BAIs enable users to achieve complex tasks via high-level intentions and AI-driven low-level processing.
EEGChat facilitated complex communication in simulated phone conversations.
The Conversational BAI enabled communication without requiring language generation capabilities.

Conclusions:

BAIs represent a significant advancement in Brain-Computer Interface technology.
This approach broadens the applicability of BCIs to populations with cognitive impairments.
Non-invasive BAIs can provide fluent communication in realistic scenarios, acting as speech neuroprostheses.