Topic: oblique dynamics

Trained artificial neural networks have become essential models in neuroscience. However, the robustness of these models to -- seemingly arbitrary -- design or initialization choices is currently debated. Some studies reported universality, others variability between solutions found by training. One choice, the magnitude of output weights, has recently received a lot of attention in machine learning, as it induces two very different classes of solutions in feed-forward networks. How this parameter affects solutions in recurrent neural networks (RNNs) trained on neuroscience tasks is not well