Model behavior for long sequences of associations.

(A) Illustration of non-specific potentiation following dopamine neuron activity (compare with Fig 1C). (B) Example sequence of positive and negative associations between two odors CS+ and CS2+ and US. Neutral gray odors (CS-) are also presented randomly. (C) Histogram of synaptic weights after a long sequence of CS and US presentations for networks with (black) and without (red) non-specific potentiation. Weights are normalized to their maximum value. The means of the distributions across 18 network realizations for each condition were significantly different (p −7, Mann-Whitney U-test). (D) Left: dopamine neuron responses for the sequence of CS and US presentations. Right: same as left, but for a network without non-specific potentiation. (E) Error rate (defined as a difference between reported and target valence with magnitude greater than 0.5 during a CS presentation; we used a higher threshold than Fig 3 due to the increased difficulty of the continual learning task) for networks with (black) and without (red) non-specific potentiation. Error rates for each network realization are evaluated over 20 test trials and used to generate p-values with a Mann-Whitney U-test over 18 network realizations.