Avoiding Catastrophic Forgetting.

Journal: Trends in cognitive sciences
Published Date:

Abstract

Humans regularly perform new learning without losing memory for previous information, but neural network models suffer from the phenomenon of catastrophic forgetting in which new learning impairs prior function. A recent article presents an algorithm that spares learning at synapses important for previously learned function, reducing catastrophic forgetting.

Authors

  • Michael E Hasselmo
    Center for Memory and Brain and Graduate Program for Neuroscience, Boston University, 2 Cummington Mall, Boston, MA 02215, USA.