Explores Brain-Computer Interfaces for restoring gait function after spinal cord injury and stroke, showcasing promising results and future possibilities.
Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.
Explores the use of FNES in understanding deafness and brain plasticity in cochlear implant patients, highlighting the correlation between FNES data and speech understanding.
Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.
Covers methods to restore conscious visual perception by projecting images directly onto the visual brain, bypassing the eyes, particularly for blind patients.
Covers auditory and vestibular neuroprostheses, focusing on their principles, applications, and the impact on quality of life for individuals with sensory impairments.
Explores the integration of brain structure and function using Graph Signal Processing techniques, including functional MRI and structural connectome analysis.