401 citations · 411 across the 5 of their papers we have counts for
3 papers · 1 filter
The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions
Gal Haspel, Ben Baker, Isabel Beets +34
Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand…
Biological learning in key-value memory networks
Danil Tyulmankov, Ching Fang, Annapurna Vadaparty +1
In neuroscience, classical Hopfield networks are the standard biologically plausible model of long-term memory, relying on Hebbian plasticity for storage and attractor dynamics for…
Artificial neural networks for neuroscientists: A primer
Guangyu Robert Yang, Xiao-Jing Wang
Artificial neural networks (ANNs) are essential tools in machine learning that have drawn increasing attention in neuroscience. Besides offering powerful techniques for data analys…