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The Role of Generative Artificial Intelligence in the NeuroIS Research Process: Applications and Opportunities

In: Information Systems and Neuroscience

Author

Listed:
  • Leonardo Banh

    (University of Duisburg-Essen, Rhine-Ruhr Institute of Information Systems)

  • Fabian J. Stangl

    (University of Applied Sciences Upper Austria, Digital Business Institute, School of Business and Management)

  • Gero Strobel

    (University of Duisburg-Essen, Rhine-Ruhr Institute of Information Systems)

  • René Riedl

    (University of Applied Sciences Upper Austria, Digital Business Institute, School of Business and Management
    Johannes Kepler University Linz, Institute of Business Informatics—Information Engineering)

Abstract

Research in Neuro-Information Systems (NeuroIS) integrates neuroscience methods with Information Systems (IS) research to advance our understanding of human-technology interactions. As neurophysiological data collection methods evolve, the analysis of large and complex data sets remains a significant challenge. Generative Artificial Intelligence (GenAI) offers new opportunities for NeuroIS by improving data analysis, experimental design, and interpretation of neural patterns. This paper systematically reviews 56 studies applying GenAI in NeuroIS and identifies five main research themes: (1) GenAI for Autonomic Nervous System Measurements, (2) GenAI for Brain Research, (3) GenAI for General Applications, (4) GenAI for Genetics, and (5) GenAI for Multimodal Approaches. Our findings highlight how GenAI improves data interpretation, integration, and processing while streamlining the use of research methods. Overall, this review underscores the transformative potential of GenAI in NeuroIS, paving the way for scalable, precise, and dynamic research methodologies in the field.

Suggested Citation

  • Leonardo Banh & Fabian J. Stangl & Gero Strobel & René Riedl, 2025. "The Role of Generative Artificial Intelligence in the NeuroIS Research Process: Applications and Opportunities," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 27-43, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-00815-2_3
    DOI: 10.1007/978-3-032-00815-2_3
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