It is clear that sleep and wake states have a profound influence on cortical plasticity and they are necessary for many forms of functional learning and memory; they also represent distinct brain states, during which sensory drive, neuromodulation, and activity patterns are dramatically different. Given that neuromodulators are strong regulators of many forms of plasticity and cortical activity patterns, this suggests that sleep or wake, via specific neuromodulators, may select for distinct plasticity mechanisms. This state- specific selection of plasticity mechanisms has significant potential benefits; for example, it is critical that Hebbian (positive feedback-mediated) and homeostatic (negative feedback-mediated) plasticity mechanisms work together efficiently to keep complex brain circuits plastic and stable, and to avoid cataleptic or epileptic states. The fact that the two types of plasticity have some of the same molecular effectors implies they could interfere with each other if not appropriately segregated. Indeed, many studies have observed roles for sleep and wake states in the efficacy of different forms of plasticity, but the results lack any explanation for how state-specific plasticity selection may be occurring. Our lab has developed a robust way to study this fundamental question by continuously collecting behavioral data and tracking single units from the visual cortex (V1) of freely behaving rats during the well-established monocular deprivation (MD) paradigm. MD causes a strong suppression of V1 firing via Hebbian LTD-like mechanisms over the first two days (MD1-2), which induce homeostatic mechanisms that bring firing rates back to baseline levels over the next two days (MD3-4) despite continued MD. Using this paradigm, we have already shown that this rebound, termed firing rate homeostasis (FRH), occurs exclusively during active wake (AW; Hengen et al., 2016). Here, I will investigate how AW specifically enables upward FRH. The major differences in V1 between AW (when upward FRH is enabled) and both sleep and quiet wake (QW) states (when it is suppressed), are levels of cholinergic (ACh) and noradrenergic (NE) input. ACh and NE contribute strongly to AW specific cortical activity patterns, are key regulators of multiple forms of learning, and are known to cause a variety of modulatory effects in V1, allowing for broad changes in synaptic efficacy. Further, my preliminary data confirms that inhibition of ACh neurons in the basal forebrain (BF), which are the main source of ACh to neocortex, makes V1 LFP activity during AW more like slow-wave-sleep. Therefore, I will test the hypothesis that upward FRH in V1 is gated by AW- specific neuromodulatory inputs. I will test the role of BF ACh and LC NE neurons in enabling upward FRH during AW using both chronic, global manipulations (DREADDs) and acute, local manipulations (optogenetic approaches). Regardless of the outcome, these experiments will provide important insight into how behavioral states can selectively coordinate distinct plasticity mechanisms in vivo and inform future hypotheses regarding molecular targets and mechanisms of action for state-specific control of plasticity.
Understanding the regulation of neuroplasticity is critical for identifying and improving treatment of learning and memory related disabilities, such as Alzheimers and dementia. It is clear that sleep and wake states are a critical part of this regulation, and a better understanding of this relationship could also help improve treatment of sleep disorders. While many studies have either examined the effects of neuromodulators on cellular plasticity or examined the role of sleep and wake states on behavioral plasticity, I will integrate these two important questions to investigate how sleep-wake states gate an important form of neocortical plasticity.
