Sleep enhances memories, especially, if they are related to future rewards. Although dopamine has been shown to be a key determinant during reward learning, the role of dopaminergic neurotransmission for amplifying reward-related memories during sleep remains unclear. In the present study, we scrutinize the idea that dopamine is needed for the preferential consolidation of rewarded information. We blocked dopaminergic neurotransmission, thereby aiming to wipe out preferential sleep-dependent consolidation of high over low rewarded memories during sleep. Following a double-blind, balanced, crossover design 20 young healthy men received the dopamine d2-like receptor blocker Sulpiride (800 mg) or placebo, after learning a Motivated Learning Task. The task required participants to memorize 80 highly and 80 lowly rewarded pictures. Half of them were presented for a short (750 ms) and a long duration (1500 ms), respectively, which enabled to dissociate effects of reward on sleep-associated consolidation from those of mere encoding depth. Retrieval was tested after a retention interval of 20 h that included 8 h of nocturnal sleep. As expected, at retrieval, highly rewarded memories were remembered better than lowly rewarded memories, under placebo. However, there was no evidence for an effect of blocking dopaminergic neurotransmission with Sulpiride during sleep on this differential retention of rewarded information. This result indicates that dopaminergic activation is not required for the preferential consolidation of reward-associated memory. Rather it appears that dopaminergic activation only tags such memories at encoding for intensified reprocessing during sleep.

Much of our long-term knowledge is organised in complex networks. Sleep is thought to be critical for abstracting knowledge and enhancing important item memory for long-term retention. Thus, sleep should aid the development of memory for networks and the abstraction of their structure for efficient storage. However, this remains unknown because past sleep studies have focused on discrete items. Here we explored the impact of sleep (night-sleep/day-wake within-subject paradigm) on memory for graph-networks where some items were important due to dense local connections (degree centrality) or, independently, important due to greater global connections (closeness / betweenness centrality). A network of 27 planets (nodes) sparsely interconnected by 36 teleporters (edges) was learned via discrete associations without explicit indication of any network structure. Despite equivalent exposure to all connections in the network, we found that memory for the links between items with high local centrality or high global centrality were better retained after sleep. These results highlight that sleep has the capacity for strengthening both global and local structure from the world and abstracting over multiple experiences to efficiently form internal networks of knowledge.