Fig. 6.

Results of experiment 3. All error bars depict SEM across independent runs. (A) Experiment 3a (cardinal boundary): mean performance of the CNN on independent test data, calculated after the first and second half of training, separately for the first and second task and blocked vs. interleaved training. Interleaved training resulted quickly in ceiling performance. In contrast, the network trained with a blocked regime performed at ceiling for the first task, but dropped back to chance level after it had been trained on the second task, on which it did also achieve ceiling performance. (B) Experiment 3b (diagonal boundary): mean test performance. Similar patterns as for the cardinal boundary were found: Blocked training resulted in catastrophic interference, whereas interleaved training allowed the network to learn both tasks equally well. Interestingly, the CNNs performed slightly worse on the diagonal boundary, as did our human participants. (C) Experiment 2a, blocked training. Layer-wise RDM correlations between RDMs were obtained from activity patterns and model RDMs. The correlation with the pixel dissimilarity model decreases with depth, whereas the correlation with the catastrophic interference model increases. Neither the factorized nor the linear model explain the data well, indicating that blocked training did not result in task factorization or convergence toward a single linear boundary. (D) Experiment 2b, blocked training. Again, correlations with the pixel model decrease and correlations with the interference model increase with network depth.