Explores the intersection between neuroscience and machine learning, discussing deep learning, reinforcement learning, memory systems, and the future of bridging machine and human-level intelligence.
Delves into spatial memory usage in RL agents for maze navigation tasks, showing improved performance with visual landmarks but inconsistent results in path choosing.
Explores the use of FNES in understanding deafness and brain plasticity in cochlear implant patients, highlighting the correlation between FNES data and speech understanding.