Drift in this scenario (left) ⬆️ memory most at long RIs (middle), including w/ fully scrambled temporal contexts (final data point). Thus, drift ⬆️ memory even w/o contextual support. As predicted, drift ⬆️ error between model predictions and outcomes, as shown in hippocampal area CA3 (right). 14/

We found temporal abstraction by training the model w/ a range of ISIs (increasing powers of 2). Increasing ISIs resulted in greater strengthening in slower-drifting pools from EC-CA3. This helps retain memory access for longer according to the temporal regularity of training. 15/