Topic: clipped-threshold-linear activation function

Memories are thought to be stored in synapses and retrieved through the reactivation of neural ensembles. However, neural representations exhibit significant dynamics even in stable environments, a phenomenon called representational drift. Theoretical studies suggest that multiple neural representations can correspond to a memory, with post-learning exploration of these representation solutions driving drift. However, the functional implications of drift-explored representations versus those initially learned remain poorly understood. Here we show that drift uncovers robust, sparsely engaged r