The convergence of Artificial Intelligence (AI), Large Language Models (LLMs), and Industry 4.0 is reshaping the landscape of Brain-Computer Interfaces (BCIs), Human-Machine Interaction (HMI), and neuroscience research. BCIs, which integrate data acquisition, signal processing, AI, and Cyber-Physical Systems (CPS), are pivotal in enhancing human-machine interactions, particularly in industrial and healthcare sectors. The incorporation of advanced AI algorithms, such as machine and deep learning, has significantly improved the performance of BCI systems, facilitating precise assessments and optimization of neuroergonomic systems, human-robot interactions, and robotic-assisted surgeries. LLMs, with their advanced natural language processing capabilities, empower researchers to analyze extensive neuroscience literature, uncover patterns, and generate hypotheses. They also aid in interpreting neuroimaging data by extracting contextual information, offering new avenues for exploration and understanding. However, despite these advancements, BCIs encounter challenges in real-world applications, such as accurately recognizing human mental states and emotions. Addressing these challenges necessitates the development of novel machine or deep learning models, intelligent hardware, software, and devices with human-like intelligence, fostering an AI-focused industrial ecosystem.
This Research Topic aims to explore the intersection of AI, LLMs, and Industry 4.0 in enhancing BCI, HMI, and neuroscience research. The primary objectives include investigating the psychological, cognitive, and behavioral impacts of AI and LLM interactions with humans, analyzing AI applications in neuroscience and brain imaging, and addressing ethical considerations in AI and LLM use in neuroscience. Additionally, the research seeks to advance intelligent brain signal processing, explore industrial BCI applications, and develop affective BCI for emotion and mental state recognition.
To gather further insights into the integration of AI, LLMs, and Industry 4.0 with BCIs and neuroscience, we welcome articles addressing, but not limited to, the following themes:
– Psychological, cognitive, and behavioral impacts of AI and LLM interactions with humans.
– AI applications in analyzing neuroscience, brain imaging, and therapeutics literature.
– Ethical considerations in AI and LLM use in neuroscience, including privacy and fairness.
– Intelligent brain signal processing and reinforcement learning in BCI.
– Industrial BCI applications and novel paradigms in Industry 4.0.
– Affective BCI in emotion and mental state recognition.
– Neuroergonomics and mutual learning in human-machine interaction.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
- Brief Research Report
- Case Report
- Clinical Trial
- Conceptual Analysis
- Data Report
- Editorial
- General Commentary
- Hypothesis and Theory
- Methods
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Keywords: Large Language Models, Artificial Intelligent, Natural Language Processing
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.