This review article summarises recently proposed theories on how neural circuits in the brain could approximate the error back-propagation algorithm used by artificial neural networks. Computational models implementing these theories achieve learning as efficient as artificial neural networks, but they use simple synaptic plasticity rules based on activity of presynaptic and postsynaptic neurons. The models […]
Published on January 29, 2019
Sander C. J. Verfaillie, Tessa Timmers, Rosalinde E. R. Slot, Chris W. J. van der Weijden, Linda M. P. Wesselman, Niels D. Prins, Sietske A. M. Sikkes, Maqsood Yaqub, Annemiek Dols, Adriaan A. Lammertsma, Philip Scheltens, Rik Ossenkoppele, Bart N. M. van Berckel, Wiesje M. van der Flier Read Full Article (External Site) Dr. David […]
Published on January 25, 2019
Emily Witek, Debra Hickman, Debomoy K. Lahiri, Mythily Srinivasan Read Full Article (External Site) Dr. David LowemannDr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped […]
Published on January 25, 2019