Astrocytes Detect Changes in Intracranial Pressure and Maintain the Homeostatic Control of Brain Blood Flow

Post by Amanda McFarlan 

What's the science?

Cerebral perfusion pressure, determined by the difference between mean arterial blood pressure and intracranial pressure (pressure inside the skull), is responsible for driving blood flow and delivering oxygen to brain tissue. Cerebral blood vessels within the brain are wrapped with the endfeet of astrocytes, a type of glial cell important for the metabolic and structural support of neurons. Blood vessels respond to changes in intracranial pressure by dilating or constricting, which likely causes structural changes to the astrocyte endfeet, and thus makes astrocytes ideally located to act as pressure sensors in the brain. This week in Nature Communications, Marina and colleagues tested the hypothesis that astrocytes in the brain act as physiological sensors that detect changes in blood flow. 

How did they do it?

The authors investigated how decreasing cerebral perfusion pressure affects cerebral blood flow. To induce acute decreases in cerebral perfusion pressure, the authors increased intracranial pressure in adult rats by infusing saline into the lateral cerebral ventricle. Then, they recorded changes in calcium levels from cortical astrocytes in response to increased intracranial pressure using in vivo 2-photon imaging. Next, the authors studied how astrocytes in the brainstem (close to the sympathetic nervous system control circuits) respond to changes in cerebral perfusion pressure. To do this, they used confocal microprobe imaging to record the frequency and duration of calcium signals from astrocytes of the ventrolateral medulla oblongata (part of the brainstem) in response to changes in cerebral perfusion pressure. Finally, the authors investigated the role of brainstem astrocytes in mediating homeostatic mechanisms that are initiated with increased intracranial pressure. To accomplish this, they interrupted the signalling between astrocytes and sympathetic nervous system neurons by virally expressing either the light chain of tetanus toxin (TeLC), the dominant negative SNARE (dnSNARE), or an ATP-degrading enzyme transmembrane prostatic acid phosphatase (TMPAP) in astrocytes of the ventrolateral medulla oblongata. They then measured arterial blood pressure, heart rate and sympathetic nerve activity in response to increased intracranial pressure.

What did they find?

The authors found that increasing the intracranial pressure by 10-15 mmHg (i.e. what would be expected to occur in response to an acute change in posture) caused a reduction in cerebral blood flow in the brain by 40% as well as increased systemic arterial blood pressure and heart rate, which facilitated oxygen delivery to the brain. Then, using 2-photon imaging, they revealed that cortical astrocytes had robust calcium signals in response to increased intracranial pressure, suggesting that the astrocyte activity was elevated. They also showed that the dilation of cortical blood vessels (that are wrapped by astrocyte endfeet) in response to increased intracranial pressure preceded the increased calcium signals in astrocytes. This suggests that astrocytes may play a role in mediating blood vessel dilation. Next, the authors found that, similar to astrocytes in the cortex, the frequency and duration of astrocyte calcium signals in the ventrolateral medulla oblongata (a region of the brainstem) was increased. Finally, they determined that control rats with intact astrocyte signalling showed increased levels of arterial blood pressure, heart rate and sympathetic nerve activity in response to increased intracranial pressure, while rats expressing either TeLC, dnSNARE or TMPAP in brainstem astrocytes did not show any change. Together, these findings suggest that brainstem astrocytes may use calcium-dependent signalling to activate sympathetic control circuits in response to changes in intracranial pressure.

What’s the impact?

This is the first study to show that both cortical and brainstem astrocytes sense changes in cerebral perfusion pressure in the brain. Moreover, brainstem astrocytes use calcium-dependent signalling to activate compensatory mechanisms that maintain blood flow and oxygen delivery to the brain. Together, these findings suggest that astrocytes may be important physiological sensors in the brain, responding to changes in pressure and activating sympathetic control circuits that help to maintain homeostatic control of cerebral blood flow. 

Marina et al. Astrocytes monitor cerebral perfusion and control systemic circulation to maintain brain blood flow. Nature Communications (2020). Access the original scientific publication here.

Pain Prediction Can Bias Pain Sensation

Post by Elisa Guma 

What's the science?

Pain is necessary for survival, both for quickly responding to aversive stimuli and for predicting potential harm from objects or situations. It is generally known that the experience of pain is related to nociception: the activation of special nerve endings in the body by potentially harmful stimuli such as mechanical (e.g. a sharp nail) or thermal (e.g. high heat). However, our experience of pain often deviates from nociception. Previously, it was shown that pain is influenced by our predictions of how painful the stimulus will be by using simple-Pavlovian cues. This week in the Journal of Neuroscience, Lim and colleagues show that pain can be strongly influenced by predictions from a conceptual schema. 

How did they do it?

The authors recruited 42 healthy adults and administered a series of tests in order to investigate how pain ratings are affected by a mismatch in pain prediction (top-down cognition; from the brain) and sensation due to nociception (bottom-up; from the body/nerves). First, a baseline pain rating was recorded for two heat stimuli used as the pain stimuli: 45°C (low) or 47°C (high). Next, all participants underwent functional magnetic resonance imaging while the pain tests were administered. This allowed the authors to make associations between neural responses to a) pain prediction and b) prediction errors. In the matched condition, participants learned a schema: when the value shown in the visual cue increased the pain produced by the heat stimulus also increased. Thus, visual cues stated “The incoming heat stimulus is at x% intensity”. The x value was a number between 0-100, and was increased linearly, with a 10-point increase corresponding to a 0.4 degree increase in stimulus temperature. 

In a second task set (mismatch level 1), the authors gradually introduced prediction errors where initially the cues continued to vary between 1-100, but the heat was held at either 45 ° C for cue values  0-40 or at 47 ° C for cue values from 61-100. Subsequently, the mismatch level was increased over a third and fourth task set (mismatch level 2) where the cues kept changing between 1-100, but the stimulus was always at 47°C . Participants were not given information on the mismatch and made their own decision on how much pain they felt after experiencing each cue-heat stimulus pairing. Finally, to better understand the factors that might mediate perceptual biases, a pain catastrophizing scale was administered, as well as a mindfulness questionnaire.

What did they find?

First, the authors established that participants were able to successfully detect a linear pattern between pain (heat) stimuli and cued (visual) stimulus intensities. Interestingly, the authors observed a bias in pain perception driven by the cue, such that the cue value had a greater influence on pain perception than the sensory stimulus. For the majority (5/8) of mismatched conditions for mismatch level 2, and (to a lesser degree) for mismatch level 1, participants partially updated their pain ratings with the change in heat stimulus, but the predictions had a stronger influence on perception than the prediction errors from the heat stimulus. 

The authors observed that areas typically involved in pain perception were responsive to increases in cued threat (cue stimulus increases), such as somatosensory regions, posterior insula and periaqueductal gray area (corrected, FLAME1). When prediction errors were high, more cognitive cortical areas became active. Finally, the authors investigated individual differences in pain perception and found that people who had higher catastrophizing behaviours and lower mindfulness or sensory awareness (as measured by a self-report scale) tended to be more affected by the cues or threat predictions. These behaviors involved the ventral and dorsal striatal circuitry, which are implicated in value-based vs. model-free or habitual decisions respectively.   

What’s the impact?

This study demonstrates that predictions that arise from learning concepts have a strong impact on pain perception even if there are prediction errors arising from sensory inputs. In other words, our prediction of pain based on a reported upcoming stimulus intensity impacts our pain even if the level of stimulus intensity eventually administered is not the same as the reported intensity. Further, changes in the levels of cued-threats altered activity in cognitive and sensory networks in an opposite manner, which underscores the role of these top-down and bottom-up networks in biasing pain perception. Finally, the authors were able to attribute behavioural patterns with perception, showing that individuals with higher mindful awareness and less fear of pain are better able to update their pain perception.

Lim et al. Threat prediction from schemas as a source of bias in pain perception. Journal of Neuroscience (2020). Access the original scientific publication here.

50 Years of Neuroscience: Progress and a Look Into the Future

Post by Stephanie Williams

What’s the science?

In honor of the 50th anniversary of the Society for Neuroscience, a group of scientists comment on the progress made in neuroscience over the previous 50 years. This week in The Journal of Neuroscience, Altimus, Marlin and colleagues review neuroscience research advancements and express a vision for the impact of future research.

What do we already know?

The authors review research in four major categories: 1) cellular and molecular neuroscience 2) developmental neuroscience 3) systems neuroscience and 4) disease. In the cellular section, the authors highlight technological innovation (patch-clamp electrophysiology, PCR, genomic sequencing), and progress made in the connectome project and in the creation of a cellular atlas of the mammalian brain. While acknowledging the reductive approach of some of these advancements, the authors argue that they will serve as a stepping stone to more detailed knowledge and will allow for novel cellular targeting strategies. In the development section, the authors highlight progress in understanding gene expression (i.e. the transcriptome) of neurons, whole-genome sequencing, the development of brain organoids and Brainbow, a fluorescent imaging approach in which individual neurons can be imaged using different colors. They review the debate over the existence of adult neurogenesis (production of new neurons) and cite recent evidence suggesting that adult hippocampal neurogenesis is indeed robust in healthy humans. In systems neuroscience, the authors focus on the potential of virally mediated gene-editing to study ensembles of neurons. They also point out the lack of precision in many behavioral measurements, which limits our ability to correlate behavior with neural activity. The authors list several brain-computer interface (BCI) advancements including BCI-mediated limb movement and visual imagery in the blind. In the disease section, the authors highlight the importance of collaborative research initiatives (eg. BRAIN, dementia research led by the United Kingdom), in accelerating research progress. They praise the progress made in psychiatric research, including the recent FDA approved treatments for major depressive disorder (esketamine), brexanolone (postpartum depression), siponimod (multiple sclerosis).

What’s next?

In cellular and molecular neuroscience, the authors predict that advancements in microscopy will allow us to visualize subcellular machinery at an unprecedented resolution. They predict that new tools will allow us to measure and manipulate epigenetic endpoints to better understand how the genome, transcriptome, and proteome relate to behavior. In the developmental neuroscience section, the authors call for the development of new technologies that can label neurons in vivo and be imaged non invasively, as well as tools that may be able to control neurogenesis across the lifespan. The authors predict that characterizing the transcriptome of neurons will lead to a new understanding of cell types. They also speculate that technological advances will resolve the difficulties that currently limit the establishment of brain organoids; brain organoids could one day act as a tool for screening potential therapies or replacing damaged brain tissue. In the systems neuroscience section, the authors predict that more precise behavioral measurements will allow for a better understanding of the corresponding neural activity. They suggest implementing new methods, such as computer vision, to automate and improve behavioral measurement and analysis. The authors predict that new imaging methods will be developed, such as cellular-resolution functional neuroimaging in humans, and hope that the imaging methods will be used to record from and interact with neural circuits in real-time. In the disease section, the authors predict we will enter an age of neurotherapeutics, characterized by an increase in the number of specific therapies for nervous system disorders. They foresee the use of technology—activity trackers and automated analysis tools—to improve diagnostics. They hope to see a shift towards preventative measures.

As a community, the authors call for scientists to prioritize addressing the lack of diversity in neuroscience, both in how research is conducted and the topics of research themselves. The authors criticize previous research for asymmetrically focusing on right-handed males, and previous clinical trials and genetic studies for asymmetrically focusing individuals of European descent. The authors also highlight the impact of neuroscience on education and recommend using neurodevelopmental and cognitive neuroscience to implement widespread changes in educational curricula so that students with disorders such as dyslexia or attention deficit hyperactivity disorder, can learn more effectively.  

Finally, the authors make several predictions about areas that will become more prominent in the next fifty years. They predict the rapid expansion of using neuroscience to explain criminal behavior, inform business practices, and advance wearable neurotechnology to customize marketing strategies.

What's the bottom line? 

Neuroscience has come a long way in the past 50 years, and it’s an exciting time to pursue promising new avenues for research. In all pursuits, the authors call for caution and strict adherence to ethical principles as the field continues to accelerate, and emphasize the importance of international collaboration and the coordination of research internationally and across disciplines.

Altimus et al. The Next 50 Years of Neuroscience. The Journal of Neuroscience. (2019). Access the original scientific publication here.