The Night's Watch: How Microglia Protect and Shape Our Brain as We Sleep

Post by Flora Moujaes 

What's the science? 

The brain is not just comprised of neurons: it contains many other types of cells, such as microglia and astrocytes, which play a fundamental role in the brain. Microglia are best known for their role in the immune response, yet they are also involved in a number of other key brain functions including plasticity: the process through which the brain changes and adapts to new experiences. Microglia interact closely with neurons at the synapse: the junction between two neurons. To date, research on microglia has focused on anesthetized animals, leaving open the possibility that microglial dynamics may be different during awake-states. It also remains unknown how neurotransmitters regulate microglial functioning. However, microglia have a higher expression of a specific type of receptor for the neurotransmitter norepinephrine compared to any other type of brain cell, suggesting norepinephrine may be a key modulator. This week in Nature Neuroscience, Stowell et al. use advanced imaging technology to show that microglial dynamics (1) differ between awake and anesthetized mice and (2) are modulated by norepinephrine.

How did they do it? 

To determine whether microglial behavior is affected by anesthesia, the researchers first imaged microglial dynamics in healthy adult mice while they were awake and after having been anesthetized with a fentanyl cocktail. Given the role of microglia in the immune response, they also imaged microglial dynamics in awake and anesthetized mice that had suffered an acute brain injury.

In order to uncover the underlying mechanisms responsible for the differences in microglia in awake and anesthetized mice, the researchers explored the role of norepinephrine in microglial functioning. Norepinephrine was of particular interest as (1) it is known to be a powerful mediator of wakefulness, and (2) microglia have a very high number of beta2 adrenergic receptors (which norepinephrine bind to). The researchers modulated the level of noradrenergic signalling in microglia, either by stimulating the microglia’s beta2 adrenergic receptors using the agonist clenbuterol to increase norepinephrine levels or by inhibiting the microglia’s beta2 adrenergic receptors using the antagonist ICI-118,551 to decrease norepinephrine levels. They examined whether this (1) affected microglial functioning in both anesthetized and awake mice, (2) affected microglial response to injury, or (3) impaired synaptic plasticity. 

What did they find?

Wakefulness vs. Anaesthesia: The researchers found that microglia in the awake brain differ from those in the anesthetized brain with regards to (1) surveillance monitoring and (2) their injury response. They showed that anesthesia rapidly increased microglial surveillance and increased the microglial response to injury compared to the awake condition. This suggests that wakefulness exerts a primary inhibitory effect on microglial dynamics.

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Norepinephrine Modulation: The researchers then replicated the findings from awake vs. anesthetized mice by pharmacologically modulating microglial noradrenergic signalling. They found high levels of norepinephrine in awake mice led to reduced microglial functioning, while low levels of norepinephrine in anesthetized mice led to increased microglial functioning. Increased norepinephrine levels also led to a significant reduction in microglial response to injury. Finally, they found that a chronic increase in microglial noradrenergic signalling impairs experience-dependent plasticity in the developing visual system of mice. 

What's the impact?

Overall this study suggests that wakefulness exerts a primarily inhibitory effect on microglial dynamics. It also shows that microglial roles in surveillance and synaptic plasticity in the healthy brain are modulated by norepinephrine. This suggests that the enhanced remodeling of the neural circuits that occurs during sleep may be mediated by the increase in the ability of microglia to dynamically interact with the brain. This is an especially interesting finding as it demonstrates that simply by modulating immune cells, it’s possible to alter synaptic plasticity

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Stowell et al. Noradrenergic signaling in the wakeful state inhibits microglial surveillance and synaptic plasticity in the mouse visual cortex. Nature Neuroscience (2019). Access the original scientific publication here.

Stress-Induced Lateral Habenula Changes and the Association with Depressive Behavior in Mice

Post by Lincoln Tracy

What's the science?

Chronic stress has been identified as a prominent risk factor for the development of depression in humans. Several animal models of depression exist that involve exposing the animals to chronic stressors, leading to behavioral changes that mimic a subset of core depression symptoms in humans. The problem with this approach is that while depression often presents in different ways in different people, patients are often grouped into one category. Recent studies have identified that the lateral habenula—a small section of the brain near the pineal gland—is hyperactive in depression. This week in Neuron, Cerniauskas and colleagues developed a novel approach to examine the molecular, synaptic, and circuit basis of unique chronic stress-induced behavioral characteristics in mice.

How did they do it?

First, the authors used a chronic mild stress model to induce depression-like symptoms in mice. This involved exposing the mice to a series of stressors over an eight-week period. The authors then used a series of behavioral tasks to assess anxiety-related behaviors (elevated plus maze), interest in rewarding stimuli (sucrose preference test), responses to being placed in an inescapable situation (tail suspension test), and deficits in sociability behavior (social interaction test). Second, they used receiver operating characteristic (ROC) curves to make an unbiased decision as to whether each individual mouse displayed a certain set of behavioral characteristics. Third, they used histology, microscopy, single-cell RNA sequencing, whole-brain input mapping, and electrophysiological techniques to analyze the molecular, synaptic, and circuit adaptions in the lateral habenula after chronic stress.

What did they find?

First, the authors found that mice exposed to chronic stress and the control mice both showed considerable variability in three of the four behavioral tasks. Second, the stress-induced hyperactivity in the lateral habenula was directly associated with connections to the ventral tegmental area and the rostromedial tegmental nucleus—two areas of the brain involved in dopaminergic (or reward) signalling in the brain—rather than the dorsal raphe nucleus, where the serotoninergic neurons are located. Specifically, lateral habenula excitability was associated with increased passive coping rather than anhedonia (an inability to feel pleasure) or anxiety, which are other common symptoms of depression in humans. The authors also identified a subset of genes that together can be used as biomarkers to identify mice that display increased passive coping and allow for the differentiation of lateral habenula neurons that project to the ventral tegmental area or the dorsal raphe nucleus.   

LHb = lateral habenula, EP = entopeduncular nucleus, DR = dorsal raphe, VTA = ventral tegmental area

LHb = lateral habenula, EP = entopeduncular nucleus, DR = dorsal raphe, VTA = ventral tegmental area

What's the impact?

This study demonstrated that mice, like humans, have considerable individual variability in how they respond to chronic stress. It is the first study to link a specific behavioral phenotype (reduced motivated behavior), which is commonly observed in depression in humans to specific molecular, cellular, and circuit changes in the lateral habenula. Even though the study was performed in mice, lateral habenula hyperactivity has also been observed in humans with depression, suggesting that there may be — at least in part — a translational aspect of these findings. This study may serve as a foundation for future research investigating symptom-specific therapeutic interventions as well as predictive biomarkers for depression. 

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Cerniauskas et al. Chronic Stress Induces Activity, Synaptic, and Transcriptional Remodeling of the Lateral Habenula Associated with Deficits in Motivated Behaviors. Neuron (2019). Access the original scientific publication here.

Brain Structure and Function are Coupled in a Region- and Behaviour-Specific Way

Post by Elisa Guma

What's the science?

Brain activity is naturally shaped by the anatomical structure underlying it. Whole-brain magnetic resonance imaging techniques have allowed us to identify how the brain is connected both structurally, based on white-matter pathways, as well as functionally, based on the correlated fluctuations of brain activity in different regions over time. A large body of work has focused on understanding the way in which these networks are organized in the context of evolution, development, and disease, but the degree to which brain structure limits brain function is hard to quantify. This week in Nature Communications, Preti and Van De Ville propose a method to quantify this relationship by creating an index to define the structure-function relationship and explore its spatial patterning and behavioral relationship

How did they do it?

The authors used diffusion-weighted magnetic resonance imaging (a measure of brain structure, sensitive to white matter tracts that connect different brain regions) and resting-state functional magnetic resonance imaging data (brain activity at rest) from 56 healthy volunteers from the Human Connectome Project, a publicly available resource. They aimed to define the way in which brain structure and function “couple”, or rather, the dependency of the functional signal on the structural signal. In order to do so, they created a “structural-decoupling index”, which allowed them to quantify the degree to which these signals were coupled (i.e. function depends heavily on structure) or decoupled (i.e. function is less dependent on structure). This was done by first building a structural-connectome of the brain, which allows the brain to be represented as a set of interconnected nodes. The building blocks of this connectome (structural harmonics) were then extracted using matrix decomposition by eigendecomposition of the graph Laplacian. The resting-state activity data was then projected onto the structural-connectome harmonics and the spatial pattern of activation at every time point was represented as a weighted linear combination of structural patterns. Based on the spatial frequency related to each harmonic, the functional signal was then split into two portions: one more coupled with the structure (related to low frequency harmonics), the other more decoupled (related to high frequencies). The amount of function/structure decoupling vs. coupling was quantified per brain region with the structural-decoupling index, to understand whether different brain structures have different degrees of coupling/decoupling. Next, they ranked regions based on the structural-decoupling index to explore the relationship of these regions to different behaviors, using a literature-based meta-analytic, public resource (Neurosynth). Finally, in order to validate these findings, the authors also generated two null models which they compared their model to.

What did they find?

They found that activity in the primary sensory regions, such as the visual, auditory, somatosensory, and motor cortex was more strongly coupled with brain structure. Conversely, the functional activity of higher-order regions such as the parietal lobe, which is part of the executive control network, the temporal lobe, including the amygdala and language areas, and orbitofrontal lobes were more decoupled from brain structure. The authors were also able to relate regions to behaviors based on the structural-decoupling index and found that regions with a low index, or rather, regions in which structure and function were highly coupled, were related to lower-order functions, such as sensory or motor functions. Regions with higher decoupling, in which function was less dependent on structure, were related to more complex functions such as memory, reward, or emotion

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What's the impact?

This study identified a novel method with which to quantify the relationship between functional brain activity and underlying brain structure. Further, the authors show that this coupling varies across structures related to different cognitive domains. This method can now be applied more broadly to understand inter- and intraindividual variability in structural and functional coupling and how this coupling might be altered psychiatric disorders.   

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Preti et al. Decoupling of brain function from structure reveals regional behavioral specialization in humans. Nature Communications (2019). Access the original scientific publication here.