AI predicts behavior based on brain activity. #NeuroscienceAI

AI Predicts Behavior From Brain Activity

Neuroscience, behavioral science, and medical research are benefiting from the predictive power of artificial intelligence (AI) machine learning, as demonstrated by a new study published in PLoS Computational Biology. The study showcases an AI deep learning model that can predict behavior with 95% accuracy in nearly real-time. This technology has potential applications in brain-computer interfaces, allowing individuals with disabilities to operate external devices and communicate. Deep learning, a subset of machine learning, involves algorithms learning from training data to make predictions. The AI model developed by researchers at Kobe University School of Medicine utilizes a convolutional neural network (CNN) for image data analysis and a recurrent neural network (RNN) for time-variable data processing. This “end-to-end” deep learning approach does not require data preprocessing and has high accuracy in behavioral classification tasks. By systematically eliminating portions of imaging data, researchers were able to identify critical areas that contributed to the AI model’s performance. This research provides a proof-of-concept for combining AI deep learning algorithms to decode neural activity quickly and accurately, potentially advancing human brain-computer interface technology.

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