Understanding The Roles Of Central And Autonomic Activity During Sleep in The Improvement Of Working Memory And Episodic Memory Part 1

The last decade has seen significant progress in identifying sleep mechanisms that support cognition. Most of these studies focus on the link between electrophysiological events of the central nervous system during sleep and improvements in different cognitive domains, while the dynamic shifts of the autonomic nervous system across sleep have been largely overlooked. 

Sleep and memory are closely related. While we sleep, our brains process and consolidate the information we learned during the day, helping us remember and learn. Therefore, a good sleep mechanism is very important for improving our memory.

There are two main stages of sleep: rapid eye movement (REM) and non-rapid eye movement (NREM). These two stages of sleep play different roles in different types of memories. During the NREM sleep stage, the brain will strengthen the processing of memories and inject important information into long-term memory to better preserve them. In the REM sleep stage, the brain will enhance our creativity and imagination by recalling and reorganizing information, and some memory fading may also occur.

To ensure good sleep quality, we should pay attention to developing good sleep habits. This includes regular sleep times, avoiding excessive use of electronic devices before bed, and maintaining a comfortable sleeping environment. In addition, maintaining physical health through exercise and diet control is also key to sleep quality.

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Recent studies, however, have identified significant contributions of autonomic inputs during sleep to cognition. Yet, there remain considerable gaps in understanding how central and autonomic systems work together during sleep to facilitate cognitive improvement. In this article, we examine the evidence for the independent and interactive roles of central and autonomic activities during sleep and wake in cognitive processing. We specifically focus on the prefrontal–subcortical structures supporting working memory and mechanisms underlying the formation of hippocampal-dependent episodic memory. 

Our Slow Oscillation Switch Model identifies separate and competing underlying mechanisms supporting the two memory domains at the synaptic, systems, and behavioral levels. We propose that sleep is a competitive arena in which both memory domains vie for limited resources, experimentally demonstrated when boosting one system leads to a functional trade-off in electrophysiological and behavioral outcomes. 

As these findings inevitably lead to further questions, we suggest areas of future research to better understand how the brain and body interact to support a wide range of cognitive domains during a single sleep episode.

The autonomic nervous system (ANS) is divided into two branches, with the sympathetic branch associated with energy mobilization during so-called fight–flight–freeze responses (1, 2) and the parasympathetic branch associated with vegetative and restorative functions during so-called rest–digest responses (3). These branches “work antagonistically, synergistically, and independently to gather information from sensory organs and coordinate responses to internal and external demands” (4). 

Both the sympathetic and parasympathetic nervous systems communicate with the central nervous system (CNS), forming a system named the central autonomic network. The central autonomic network is a set of CNS structures, including the locus coeruleus (LC), hypothalamus, amygdala, ventromedial prefrontal cortices, hippocampus, and thalamus, that, directly or indirectly, receive inputs from and modulate output to the ANS. 

The vagus nerve (the 10th cranial nerve) is comprised of ∼80% afferent connections (5) that communicate parasympathetic/vagal information from the periphery to the nucleus of the solitary tract in the brainstem and higher-order areas in the central autonomic network (6, 7). Additionally, descending projections from the central autonomic network allow for bidirectional communications between the brain and the peripheral regions (8, 9).

In humans, a noninvasive method to detect ANS activity is heart rate variability (HRV), which examines the variability between individual heartbeats (R–R intervals, reflecting ventricular depolarization) in the QRS complex of electrocardiogram (ECG) (10–12). 

HRV can be calculated in the time domain and the frequency domain. Time-domain measures of HRV include 1) the SD of all R–R intervals (SDNN), a general measure of variability in heart rate, and 2) the root mean square of successive differences (RMSSD), a measure of heart rate fluctuations mediated primarily by the vagus nerve. 

Frequency-domain measures of HRV include 1) the power of high-frequency HRV (HF-HRV: 0.15 to 0.40 Hz), an indicator of respiratory sinus arrhythmia and parasympathetic vagal activity, and 2) the power of low-frequency HRV (LF-HRV: 0.04 to 0.15 Hz), a mixed signal from both sympathetic and parasympathetic sources. Given the uncertainty in the contribution of signals comprising LF-HRV, relative to the known vagal origins of the HF-HRV signal, research on autonomic activity tends to focus on HF-HRV. 

For a recent review of the brain areas and neuromodulatory systems comprising the parasympathetic and sympathetic branches, as well as their inputs to brain areas devoted to cognitive processing, see Whitehurst et al. (4).

Our review focuses specifically on the evidence supporting the role of the ANS in cognitive processes across wake and sleep. We report on a robust set of findings linking parasympathetic/vagal activity during wake and sleep with the prefrontal–subcortical network regulating cognitive control, executive function, and working memory (WM). We also identify a significant dearth of evidence for autonomic activity facilitating sleep-dependent memory consolidation, a notable gap given the large body of research connecting sleep with the formation of long-term memories. Next, we summarize current knowledge about mechanisms supporting the formation of long-term memories during sleep. 

Upon this background, we develop the hypothesis that the brain networks and neuromodulatory systems during sleep that support increased efficiency in WM and the consolidation of hippocampal, episodic memories are separate and competing mechanisms. We introduce the Slow Oscillation Switch Model, which gives an outline of how these mechanisms interact during sleep, along with emergent testable hypotheses and new lines of inquiry for further research in this area.

Autonomic Inputs Modulate Cognition

Cognitive processes that rely on top-down inhibitory control in prefrontal–subcortical networks, such as emotional regulation, cognitive control, or executive function, have been associated with parasympathetic/vagal activity. Cognitive control or executive function, the coordination of mental processes and actions by current goals and plans is a primary function of the prefrontal cortex. 

The coordination of cognitive control is implemented by multiple functional circuits anchored in the prefrontal cortex, including the ventromedial prefrontal cortex, anterior cingulate cortex, and a wide range of subcortical regions (13). WM is an aspect of executive function that supports the maintenance and manipulation of a small quantity of information, usually lasts seconds to minutes (14), and shares similar neural mechanisms with cognitive control (15). The scope of this paper will focus on one aspect of executive function, namely WM (for more information on emotional regulation, see refs. 16–19). 

WM, unlike long-term memory (LTM), entails the transformation of memory representations or traces and is an information-general, online cognitive process, which has traditionally been considered an unmodifiable trait. Yet, WM training studies have demonstrated that executive function generally and WM specifically can be improved (20) and that these improvements are supported by increased prefrontal efficiency and automaticity of prefrontal–subcortical networks (21, 22).

Research on the role of the ANS in cognition has shown that parasympathetic/vagal activity may be an indicator of the degree to which the prefrontal–subcortical circuit regulates its component systems in response to internal and external demands. Specifically, activity in these inhibitory circuits has been positively associated with resting HF-HRV (9, 23), and optimal functioning of these circuits is hypothesized to predict flexible and adaptive responses to environmental changes (24). One prominent model aimed to explain how the bidirectional communication between CNS and ANS is a critical predictor of adaptive cognitive success is the Neurovisceral Integration Model, developed by Thayer and colleagues (9, 23) (SI Appendix, Fig. S1). 

This model proposes that HRV is an index of prefrontal–subcortical inhibitory influence over a wide range of brain areas supporting cognition, emotion, and physiological reactivity, including executive function, WM, expectation of future outcomes, emotional regulation, emotional response to stress, and peripheral functioning (24).

The Neurovisceral Integration Model gained empirical support from studies showing the relationship between HRV during wakefulness and executive function. Compared to individuals with low resting HF-HRV (reflecting poor parasympathetic vagal tone during awake rest), high–HF-HRV individuals show better WM performance [nback task (25); operation-span task (26)] and inhibitory control [i.e., Stroop task (27)]. 

In addition, training-induced changes in cognitive control are associated with improvements in parasympathetic activity, and the reversal is also true that training-induced increases in parasympathetic activity also promote cognitive enhancement. For example, cognitive training (vision-based speed of processing) has been shown to increase HF-HRV and enhance activation in the prefrontal–subcortical network (22). In this study, older adults with amnestic mild cognitive impairment underwent 6 wk of cognitive training. 

Compared to controls, older adults in the active training group demonstrated increased HF-HRV and decreased prefrontal–striatal connectivity during the task, suggesting an efficient prefrontal–subcortical autonomic regulation. Similar results were reported in healthy participants (28). Furthermore, increasing resting HF-HRV via aerobic training has been reported to parallel improvements in WM performance (27). 

In this study, participants were randomly assigned to an aerobic training group and a detraining group (reduced exercise condition), with resting HF-HRV and WM measured before and after the exercise intervention. Postintervention, the aerobic training group showed greater HF-HRV and WM performance compared to the detraining control group, suggesting a link between the strengthening of parasympathetic/ vagal functioning and WM networks via cardiac exercise.

One potential mechanism for how vagal/parasympathetic activity can benefit prefrontal function and WM is via the modulation of norepinephrine (NE). The last 20 years of research have demonstrated that along with the traditional story that the primary neuromodulator of vagal activity is acetylcholine (ACh), vagal afferents also modulate NE levels in the brain. The vagus nerve represents the main component of the parasympathetic nervous system, and activating ascending fibers of the vagus nerve mediate NE’s actions on the brain (29, 30). 

The terminals of the afferent vagal transmissions are directly within the nucleus of the solitary tract, which convey information to structures that regulate higher-order cognition such as the amygdala, hippocampus, and frontal cortex via a polysynaptic pathway from the LC. Although ACh is the primary neurotransmitter in the peripheral synapses of the vagus nerve, once the information propagates to the LC, NE becomes the primary neuromodulator mediating synaptic communication in the CNS.

The LC has two modes of firing, phasic and tonic, which influence prefrontal function. Tonic firing has been linked to stress or arousal, whereas phasic firing has been linked to responses to novelty and higher-order cognition (31). Phasic and tonic activations are independent, with phasic activity optimized at when moderate level of tonic activity (32), while elevated tonic discharge can impair phasic discharge (33). In primates, phasic activation of NE neurons of the LC in time with cognitive shifts could provoke or facilitate dynamic reorganization of target neural networks, permitting rapid behavioral adaptation to changing environmental imperatives (34). 

Furthermore, it has been recently shown that phasic optogenetic activation of LC protects against deleterious human rectangle tau effects and cognitive decline while stress-inducing tonic-LC activation worsens its effects (35, 36). Specifically, in the study conducted by Omoluabi et al. (36), mice were injected with tangled tau, and their LC neurons were activated in either phasic or tonic patterns. They found that phasic stimulation rescued mice from behavioral and LC deficits, while tonic stimulation led to worsened symptoms.

Furthermore, studies in rodents and monkeys have shown that optimal excitatory–inhibitory balance of prefrontal NE, maintained by different adrenergic receptors, (e.g., α1 and pre- and postsynaptic α2), has an important beneficial influence on WM performance (37, 38). Experimentally increasing NE concentrations in the prefrontal cortex improves response inhibition performance in rodents and humans (39, 40). 

This body of research emphasizes the role of increased inhibitory function during distracting conditions that serve to benefit WM specifically (41) while having no benefit for hippocampal memory (42). Interestingly, α2 adrenergic receptors preferentially increase prefrontal NE and maintain its optimal excitatory–inhibitory balance, which in turn improves prefrontal function (43–45), whereas α1 receptors override α2 receptor activity and impair WM function (38). 

The emerging picture is that different types of adrenergic receptors may play a role in optimizing the overall excitatory–inhibitory balance in the prefrontal cortex. Specifically, NE orchestrates physiological functions that switch the brain and body from a nonstressed state, in which phasic LC activity engages α2 receptors and increases prefrontal WM function, to a stressed state that stimulates tonic firing and α1 receptor activity, impairing WM while maintaining other functions, such as alertness and attention (46).

In humans, a causal link between vagal inputs modulating LC–NE activity and cognitive domains supported by the prefrontal cortex has been established by studies actively manipulating vagal tone using vagal nerve stimulation (VNS) or noninvasive transcutaneous vagus nerve stimulation (tVNS). VNS activates phasic neuron firings in the LC and increases NE levels in the prefrontal–subcortical networks, including the neocortex, hippocampus, amygdala, and other parts of the brain with afferent projections from LC (33, 47–49). 

In one study, patients treated with invasive VNS performed cognitive tasks with stimulation on or off. Patients demonstrated improved WM performance during the stimulation-on periods compared to the stimulation-off periods (50). More recently, tVNS has shown similar effects to cognitive control (51). In this study, healthy participants performed an inhibitory control (Go/NoGo) task with active tVNS or sham stimulation. 

In the NoGo condition which required cognitive inhibition, tVNS resulted in significantly reduced amplitude of frontal N2 event-related potentials, a biomarker for demanding cognitive control, suggesting that tVNS may lead to more efficient neural processing with fewer resources needed with successful frontal inhibitory control. Similar effects of tVNS have been demonstrated in another study (52) in which tVNS increased frontal midline theta activity, thought to reflect transient activation of the prefrontal cortex in situations requiring increased executive control of actions.

Given that vagal stimulation enhances phasic LC–NE, and that parasympathetic activity is naturally increased during nonrapid eye movement (NREM) sleep, it is tempting to hypothesize that increases in phasic LC–NE activity with the natural boost in vagal parasympathetic activity during sleep may be one mechanism whereby prefrontal function is regulated and WM capacity enhanced. 

Taken together, phasic LC–NE during sleep might contribute to increased WM capacity through several possible mechanisms, including reorganizing neural representations, the elimination of tau, and/or increasing phasic activity of LC–NE α2 receptors along with prefrontal function. At the same time, stress-induced tonic LC–NE is disruptive to sleep as well as prefrontal function. The next section will review findings on the relationship between sleep and ANS activity.

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