This research explores the groundbreaking integration of Brain-Computer Interfaces (BCIs) with Generative AI to transform neural signals into meaningful outputs for communication and computation.

• Leverages non-invasive EEG technology to decode brain activity into images, text, and other modalities
• Employs advanced deep learning techniques including GANs and Transformer-based models for neural representation learning
• Enables new possibilities for assistive communication and multimodal integration between human thought and digital systems
• Creates foundation for medical applications that could help patients with neurological conditions express needs and communicate effectively

This convergence of neuroscience and AI promises to transform how people with communication limitations interact with technology, potentially unlocking new capabilities for medical diagnostics, treatment, and assistive care.

A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond