Figure 7.

Generative neural replay underlying hypothesis testing over timescales of online computation

(A) We investigated the difference between sequences starting either from the stable or the present building blocks for different time intervals of the inference period, and we found a brief early predominance of replay starting from the stable building block followed by a predominance of replay starting from the present building blocks (260–1,660 ms) during inference.

(B) We assessed the individual contributions of the different types of neural replay to these differences and found an unspecific predominance of sequences from the present (180–1,620 ms), distant present (the present block that is unconnected to stable, 170–1,680 ms), and absent (190–1,580 ms) building blocks to the stable building block early during inference, as well as a specific effect from present to the stable building block late (1,590–3,500 ms) in inference shortly before subjects entered the decision phase of the task.

(C) We found a selective predominance of replay between present building blocks over replay between present and absent building blocks in a time window between 260 and 1,650 ms.

(D) We also tested for length-3 replay effects using this sliding window approach. This implies testing whether a specific transition between two building blocks predicts the transition to a third building block, while controlling for all possible length-2 and alternative length-3 transitions. Using this approach, we found significant effects for length-3 replay reflecting sequences from [present to present] to stable (100–1,650 ms), [distant present to present] to stable (110–1,800), and [present to distant present] to stable (130–1,590 and 2,080–3,420 ms).

Shaded colored areas reflect standard errors.

See also Figures S4, S6, and S7.