By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
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.
Explores the development of a mathematical model of the brain, focusing on brain organization and dynamics, including neuronal activity patterns and emergent phenomena.
Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.
Delves into sensory, short-term, and long-term memory processes, including iconic and echoic memories, rehearsal techniques, and the working memory model.
