CRCNS: Acetylcholine and state-dependent neural network reorganization

Disrupted sleep is a major predictor of disordered cognition and affect, yet many questions regarding sleep's role in brain function remain unanswered. For example, why is sleep critical for memory consolidation? Why is there ubiquitous (presumably, evolutionarily conserved) wake-non-rapid eye movement (NREM)-REM sleep state ordering across species, and what are the differential roles of the two sleep states? How do brain circuit-wide dynamics change during these states, and how do those transitions affect the process of memory consolidation? Wake, NREM, and REM states generate distinct patterns of functional connectivity, which may help to reorganize brain networks in the context of memory storage. However, multiple mechanisms could play a role in this process, including state-driven structural (synaptic) changes, neuromodulatory processes, spike timing, or input alterations. This proposal advances the novel hypothesis that sequential in brain networks' acetylcholine (ACh) signaling and input properties, associated with wake->NREM->REM state transitions, are essential for memory storage In this framework, each state plays a distinct role, associated with state-specific network excitatory/inhibitory balance and neurons' input-response properties. Together, this leads to differential circuit activation and dynamic properties during wake, NREM, and REM. Our preliminary network modeling data suggest that the specific properties of NREM and REM allow for recruitment of neuronal populations into individual engrams (NREM), and generation of distinct, segregated engram representations (REM). These features become critical during consolidation of one or multiple memories, respectively. Here, we propose to apply computational modeling, in vivo experimentation and analytical tools to identify NREM (low ACh) and REM (high ACh)-associated dynamical states, and the specific contribution of these states to information storage in neural circuits. Specifically we will: 1) measure state-associated ACh effects on functional network connectivity and dynamics in highly reduced in silico neural network models, 2) test effects of state-targeted manipulations to hippocampal ACh inputs and excitatory-inhibitory balance during consolidation of one, or multiple, sleep-dependent memories, and 3) develop a predictive in silico model of the hippocampal circuit's reorganization during memory encoding and subsequent wake->NREM->REM transitions. These studies will also clarify state-specific mechanisms of memory storage in the brain, and how the wake-NREM-REM sequential ordering of these states (ubiquitous across vertebrate species) contributes to the process of memory consolidation. These studies will address Objective 1.1. of the NIMH Strategic Plan for Research, by identifying brain state-dependent neural circuit mechanisms underlying sleep's role in promoting healthy cognition and memory storage.