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Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Explores neural signal processing, MRI techniques, and imaging validation, emphasizing structural and functional connectivity and clinical applications.
Explores the synergy between machine learning and neuroscience, showcasing how deep neural networks can predict neural responses and the challenges faced by AI in robotics.
Explores the integration of silicon membranes into deformable structures and the creation of neural implants with electronic components directly at the electrode array level.
