  Artificial neural networks (ANNs) suffer from catastrophic forgetting when
trained on a sequence of tasks. While this phenomenon was studied in the past,
there is only very limited recent research on this phenomenon. We propose a
method for determining the contribution of individual parameters in an ANN to
catastrophic forgetting. The method is used to analyze an ANNs response to
three different continual learning scenarios.
