Neural Interfaces: Biocompatibility and Neuroregeneration
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Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Explores the integration of silicon membranes into deformable structures and the creation of neural implants with electronic components directly at the electrode array level.
Focuses on the development of 'eSee-Shells', chronic multimodal neural interface devices using transparent, inkjet-printed electrocorticography (ECoG) arrays.
