FINDING 3: So, what's the driving force behind this transformation? **Sleep**! Specifically, deep sleep (slow-wave sleep). We found that participants who got more slow-wave sleep after learning had stronger and more abstract successor representations. 🧠💤 7/9

FINDING 2: Even more interesting, using RSA with a deep neural network, we found the successor representation wasn't just a faint copy of the original image. It became more abstract and "high-level," shifting from simple visual features to the core concept of the image after learning. 6/9

FINDING 1: It worked! We found that even when the sequence was no longer relevant for the task at hand, when participants saw image A, we could decode the information for the successor image B from their brain activity. This confirms the existence of successor representations. 5/9

To find out, we designed an experiment: participants first learned image sequences. We then recorded their brain activity using high-density EEG, including throughout a 2-hr nap, to see if their brain would spontaneously activate a representation of the next image. 4/9