Discusses assembling neural networks by defining space and populating it with neurons, emphasizing the challenges and strategies for accurate morphologies and volume information.
Covers spontaneous brain network activity, neural simulation, and validation, emphasizing the importance of in-vitro and in-vivo conditions for accurate network modeling.
Covers methods to restore conscious visual perception by projecting images directly onto the visual brain, bypassing the eyes, particularly for blind patients.
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.
Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.
