Intersecting Neuroscience and Game Design with Brain-Computer Interfaces: Exploring Player Decision-Making and Enhancing Player Experience Using Generative Artificial Intelligence

Abstract

This thesis proposes a novel integration of brain-computer interfaces (BCIs) with video game design, using non-invasive EEG technology to enhance player immersion by dynamically adapting the game environment based on real-time emotional feedback. Leveraging advancements in deep learning, this interdisciplinary approach seeks to refine neural signals associated with emotions such as stress, fear, and joy, and employ these signals to modify a player’s 2D platformer environment using generative artificial intelligence (AI). With the video game industry facing a stagnation in innovation, this research aims to revitalize player engagement through a deeper, personalized gaming experience. The paper will discuss the potential and challenges of BCIs in gaming, outline a design for a user-friendly EEG-based BCI, and explore its implications. By integrating neuroscience, cognitive science, engineering, and game design, this thesis aims to not only advance the field of interactive entertainment but also contribute to the broader understanding of human decision-making and human-computer interactions.