By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores the application of computational neuroscience in neuroprosthetics, focusing on predicting intended arm movements based on spike times and the importance of systematic parameter optimization.
Explores memory aid for the human brain, focusing on opportunities to study human memory, single cell recordings, and the representation of space, time, and objects.
Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.
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.
By Tatjana Tchumatchenko explores dynamical response functions in neuroscience, emphasizing the role of linear response functions in understanding neural activity.
