While the exact physiological function of sleep remains unknown, there is mounting evidence that it plays an important role in the consolidation of long-term memories. In particular, it appears that sleep promotes the consolidation of declarative memories that require a functionally intact hippocampus, including memories of place. In rodents, place-dependent fear memory is promoted by sleep and disrupted by sleep deprivation. Sleep deprivation also disrupts a number biochemical and neurophysiological processes that are thought to be involved in memory consolidation. These studies have led many to suggest that sleep promotes long-term memory consolidation by modulating neural network dynamics and synaptic plasticity within the hippocampus. In experimental studies, the co-PIs have recently identified changes in hippocampal neural network dynamics during sleep that are induced by place-dependent fear learning. In computational modeling studies, the co-PIs have shown that acetylcholine, a modulatory chemical whose levels vary across sleep states, can change neural network dynamics in a similar way. The proposed projects take a multidisciplinary, multi-scale approach to bridge the gap between experimental and computational results, to identify how effects of acetylcholine on neurons lead to changes in neural network dynamics to promote learning, ultimately leading to learning and memory behavior. While the focus is on fear learning and memory consolidation, the fundamental knowledge of learning-related and sleep-related brain network dynamics gained by the proposed experiments and computations will provide valuable insights into mechanisms for all types of learning.
At present, it is unclear how sleep-related changes in hippocampal network dynamics might promote contextual fear memory consolidation. The team's recent experimental studies have shown that contextual fear conditioning produces long-lasting, sleep-dependent increases in the stability of hippocampal network functional connectivity patterns. These results, coupled with the team's recent computational studies describing a role for acetylcholine in network-wide activity and synaptic plasticity patterning, have led to the hypothesis that sleep promotes memory consolidation, at least in part, by dynamically shifting patterns in hippocampal neural network activity during naturally-occurring rapid eye movement and slow wave sleep brain states. Sleep-dependent acetylcholine has a primary role in driving these shifts in network activity through its effects on cellular excitability properties. The proposed projects use behavioral, physiological, and computational approaches to tackle the missing links that will show the hypothesized network mechanisms occur in brain hippocampal networks and participate in fear learning and memory. Hippocampal acetylcholine levels will be manipulated across wake and sleep states while recording multi-unit activity in hippocampus to quantify changes in spike timing dynamics in the context of fear and subsequent sleep or sleep deprivation. The team has developed a suite of quantitative measures to identify learning-related changes in network dynamics. In addition, acetylcholine-induced changes in cellular membrane properties that affect network dynamics will be measured in hippocampal pyramidal cell and inhibitory interneuron populations. The results will be used to inform details of biophysical neural network models to identify specific dynamical mechanisms by which acetylcholine-mediated changes in network activity dynamics promote network stability, structural changes and synaptic reorganization associated with learning and consolidation.
