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BRAIN DECODING: TOWARD REAL-TIME RECONSTRUCTION OF VISUAL PERCEPTION

Published by Meta Platforms

This paper discusses the use of AI and machine learning to decode and reconstruct visual perceptions from brain activity in real-time. By utilizing magnetoencephalography (MEG) and advanced AI models, the researchers aim to generate visual representations from brain signals. Their approach involves a three-module pipeline for aligning brain activity with pretrained image models and generating images from MEG data. This method shows significant improvements over traditional techniques and represents a crucial step toward real-time brain-computer interfaces and applications in both clinical and research settings.

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