Experiment Shows External Memory Can Restore Learned Behavior After Full Brain Reset

A developer built a small recurrent neural network paired with an external memory system to test whether learned experience could survive a complete substrate reset. The experiment used a fixed cue-response task where the network had to map specific inputs to correct actions, with chance performance at 33%. Results showed that external memory alone achieved near-perfect accuracy, while plasticity alone underperformed at roughly 47%, and combining both yielded 88%. Crucially, the memory system was constrained to only bias internal network states rather than directly select actions, preserving the integrity of the test. The key finding was that externally stored experience could reinstate correct behavior in a reset network that had never independently learned the task.