Active neurons consume vast amounts of energy, yet they have no reservoir to store fuel for when it is needed. This poses an interesting engineering problem:
How can the brain provide adequate energy supply to a diverse neuronal network based on ever-changing firing activity?
To address this question, scientists have been investigating the unique relationship between brain cells and cerebral vasculature, a system conceptually understood as a “neurovascular unit” or even “neurovascular complex”, where different cell types act together to fulfill critical cooperative functions. To grasp the profound implications of understanding multiple disparate cell types as an interconnected unit, we have to focus on one of its most prototypical functions: Neurovascular coupling
The plumber hears you, but who gave the call?
Neurovascular coupling describes the phenomenon that cerebral blood flow (CBF), and with it oxygen and glucose supply (among other metabolites), is increased surrounding neurons who are actively firing. While this coupling of the vasculature response to neuronal activity has been well observed for decades and provides the basis for blood oxygenation level-dependent (BOLD) imaging (a key method in functional MRI studies) the regulation of this process is not fully understood.
Active neurons consume a lot of energy in the form of glucose and oxygen, causing a rapid depletion and need for resupply of these metabolites, so a metabolite-driven regulation of blood vessel responses became the rationale for interpreting BOLD signals. This is intuitive, fMRI utilizes the fact that de-oxygenated hemoglobin is paramagnetic, thereby decreasing magnetic resonance in an MRI scanner. When oxygenated hemoglobin gets re-supplied through increased CBF a few seconds later, the BOLD signal spikes, offering an indirect readout of oxygen consumption by neurons.
While it generally holds true that all areas of the brain can increase CBF in response to neuronal activity, scientists discovered with the help of BOLD imaging that neurovascular coupling is not equally strong in all areas. Brain areas where neurovascular coupling is decreased are more susceptible to damage through lack of oxygenation (Shaw K. et al., Nature communications, 2021). So how exactly is neurovascular coupling regulated?
There is no question that metabolite feedback loops play a crucial role in regulating the behavior of multiple cell types involved in the function of the neurovascular unit.
Brain areas where neurovascular coupling is decreased are more susceptible to damage through lack of oxygenation
However, a purely metabolite-based regulation hypothesis does not clearly explain how blood flow is matched to neural activity in both time and space. Today, several observations where CBF was not directly linked to changes in oxygen or glucose concentration further challenge the validity or completeness of any such hypothesis. For example, one study found increased blood flow despite the presence of experimentally induced high levels of oxygen (Lindauer et al. 2010). Another study by Devor et al. (2008) found decreased blood flow in regions with high neural activity and correspondingly high glucose uptake. Complicating the issue is the fact that neurovascular units can be quite diverse, depending on the brain regions, cytoarchitecture, vascularization pattern, and cell types involved. Mechanisms that might be determinant in one neurovascular unit might only play a minor role in a different unit. It is a mess. So neuroscientists needed to chart a map.
Mapping the mediators
The fundamental problem, as often in neuroscience, is the inherent complexity of the brain’s cytoarchitecture: Different areas of the brain are organized differently, made up of different cell types and performing different functions.
Vascular units are no exception. Depending on which region of the brain is studied, heterogeneous vascularization density, cell types, and metabolic signals are involved in regulating the neurovascular coupling for the unit.
(For a great review on the many complex interactions: Constantin Iadecola, Neuron, 2017).
Just to give a small (and incomplete) overview:
Canonically for neurons, activation of postsynaptic glutamate receptors (mainly NMDA and AMPA) leads to increases in intracellular Ca2+ and activation of Ca2+-dependent enzymes such as neuronal NO synthase (nNOS) and cyclooxygenase 2 (COX-2), two enzymes which produce the potent vasodilators nitric oxide (NO) and prostanoids (e.g. PGE2), respectively. However, scientists have identified many other contributing mechanisms, for example, adenosine, produced from ADP by ectonucleotidases, ATP acting on purinergic receptors, or intracellular potassium concentration can also serve as potent vasodilators (Constantin Iadecola, Neuron, 2017).
Astrocytes get innervated from the glutamate released by neurons, which acts on metabotropic glutamate receptors, triggering Ca2+ increases in these cells and the production of vasoactive agents. They might influence the vasculature by serving as potassium sinks or by the release of arachidonic acid, and production of PGE2 and epoxyeicosatrienoic acids (EETs). D-serine produced by astrocytes might also stimulate NO production in endothelial cells.
Endothelial cells have been known for some time to contain powerful vasoactive agents (NO, prostanoids, endothelin, etc.) that regulate CBF in response to chemical and mechanical signals (J. Andresen et al., J. Appl. Physiol., 2006). As with the wider vasculature, acetylcholine and catecholamines also play an important function.
Smooth muscle cells & pericytes implement neurovascular coupling by responding to signals generated by neurons, astrocytes, and endothelial cells. Smooth muscle cells also ultimately engage the vasomotor apparatus to induce vasodilatation, reduce vascular resistance, and increase blood flow.
Additionally to cell-based mechanism, many systemic factors can influence CBF, for example circulating glucose, hormones, peptides, the concentration of CO2 or oxygen in the blood, or physical changes in arterial pressure through cold shock or body position. While these factors impact CBF at all different layers of the cerebrovascular system, they can have varied impacts depending on the neurovascular segment. The sum total of all interactions produces the nuanced regulatory feat of coordinating the vascular response with neuronal energy needs.
So everything is connected, huh?
Our brains and bodies are complex biological systems. Given all the mechanistic complexity and possible contributors, it is not easy to derive practical models of neurovascular coupling. There are seemingly countless factors, feedback loops, and tradeoffs being balanced by our biology to make sure the lights do not go out, quite literally (Stellpflug SJ. et al., International Journal of Neuroscience, 2019).
This does not mean that there are no useful insights to be gained and nothing new to be learned. Quite the opposite, gaining more knowledge about these interconnected behaviors is crucial for developing new interventions, from stroke to neurological diseases to crossing the blood-brain barrier with drugs (Biswas S. et al., Development, 2020).
Furthermore, the fact that the neurovascular complex is an interconnected and dynamic complex system does not imply that all cell types have an equal say in the matter. There might still be a clear boss or at least a critical decision maker.
So let us look a bit deeper into the role of neurons because they are the main actors, the one cell type that we can influence with directing our attention to specific tasks, and ultimately the energy-hungry consumers that the rest of the body has to satisfy for our survival.
Neuronal activity prompts proportional, but non-linear vascular action
A recent study by Gagliano et al. investigated the relationship between stimulation frequency and neurovascular response using electrically activated mossy fibers in the granular layer of the cerebellum.
While making up only 10% of the brain in volume, the cerebellum houses over 50% of all its neurons.
Interestingly, in this neurovascular unit, vasodilation is almost exclusively mediated via the metabolite Nitric oxide (NO), which is produced by the Ca2+-dependent neuronal isoform of NO synthase (nNOS) in response to NMDA receptor (NMDAR)-mediated Ca2+ inflow (Attwell D. et al., Nature. 2010).
Vasoconstriction is mediated via the metabotropic glutamate receptors (mGluRs) activation-dependent production of 20-hydroxyeicosatetraenoic acid (20-HETE), a metabolite released by astrocytes (Mapelli L. et al., Jneurosci, 2017).
Intuitively one might expect vasodilation and corresponding CBF (which are dependent on a single metabolic pathway) to increase with the neuronal activity: The more neurons fire, the more energy supply they need. A mostly linear relationship (at least up to the point of maximum blood flow… there is a physical limit, after all) that can be approximated by models quite easily (Hewson-Stoate N. et al., Neuroimage, 2005).
Gagliano et al. could however show that there is a stimulation frequency where the linearity breaks (see figure below), leading to a partial uncoupling of neuronal activity from NVC at the physiological 50–100 Hz frequency range.
Our data showed that NVC is probably more complex than previously thought, adjusting to the input frequency in a region-specific manner. To the best of our knowledge, this was the first report of this effect in the cerebellar cortex. Interestingly, our results suggested that the force/BOLD non-linearity recorded from the cerebellum during motor task executiocould, at least in part, be due to local non-linear NVC properties. — Gagliano G. et al., Cells, 2022
This is a beautiful example of a key characteristic of complex systems: Feedback to help coordination.
Mossy fibers are central to the cerebellum’s function (each mossy fiber innervates hundreds of granule cells which send axons up toward the cortical surface) and are thought to integrate signals from proprioceptors, somatosensory receptors, and several brain regions, most prominently the motor cortex. Movement requires the coordinated action of many muscles in precise temporal sequence.
While speculative at this point, some evidence suggests that the large divergence of input from the mossy fibers to the granule cells and to the parallel fibers is believed to create complex representations of the entire sensory context at present and the desired motor output (Bengtsson F. and Jörntell H., PNAS, 2008, Powell K. et al., elife, 2015).
Gagliano et al. identifying a non-linear dynamic in the 50–100Hz frequency range might suggest a biological preference for low and high, but not intermediate, frequency firing patterns and gives power to the notion of “complex representations” for desired motor output.
Some have even suggested that the cerebellum acts as a feedforward control system to implement coordinated action of movement, where the combined stimulation of mossy fibers need to reach a certain threshold (firing frequency?) to signal to a forward effector (for signal processing in electronics, the mossy fibers might serve analogous to a band-pass filter).
While intriguing, our scientific understanding is not there yet.
"Neurovascular coupling investigations tell a story far beyond a simple “linear” adjustment of energy supply to active neurons. For instance, the communication is bidirectional and complex properties might emerge depending on the network activity state. Indeed, we are far from fully understanding these mechanisms and their impact on brain processing. Elucidating neurovascular coupling mechanisms might be vital to reaching a new level of knowledge of brain functioning in physiological and pathological conditions." - Lisa Mapelli (direct communication)
What can be said for now is that in complex systems, identifying critical parameters and self-contained submodules like frequency-dependent metabolic feedback loops help scientists build toward better models and a more apt description of the reality of our human condition.
Science is ever-moving, most likely, even the concept of a “vascular unit” has to be expanded to a “neurovascular complex” (Shaeffer S. et. al., Nature neuroscience, 2021) to accommodate the seemingly ever-increasing complexity of our brain. Today, it is not clear if we will ever be able to completely model the brain in its complexity, but I believe that should not deter us from trying, especially when our biological tools and computational powers continue to grow (that might however be the topic of another blog post).
Our brain is rightly called one of the most complex structures in the universe. Reductionist scientific approaches make it difficult to elucidate accurate causal inferences when studying complex systems, even from cells that are part of the whole organ. There is a need for tools that can capture complexity at the network scale, as well as experimentally informed models that allow us to make causal inferences and de-tangle the relative contribution of individual contributing factors and submodules. That is of course nothing new to neuroscientists, system biologists, and other branches of science dealing with non-linearity.
In these systems there exists no proportionality and no simple causality between the magnitude of responses and the strength of their stimuli: small changes can have striking and unanticipated effects, whereas great stimuli will not always lead to drastic changes in a system’s behavior. — Willy C. et al., European Journal of Trauma, 2003
For better or worse, there is no great workaround, complex systems require scientists to study them as a whole, with all the caveats, limitations, and uncertainties attached to them.
For me, the fact that our thoughts can alter our biology, even in as tiny a way as changing cerebral blood flow, is fascinating. Seeing neurovasculature, cytoarchitecture and varied brain cells as a singular, connected & non-linear complex system (or system of systems) is not only a useful framework, but it also comes with new exciting questions. Maybe even philosophical ones.
If the patterns of our thinking can alter our cerebral blood flow, to what extent can alterations in our cerebral blood flow also influence the patterns of our thinking?
I don’t know about you, but I can’t wait for scientists to find out.
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Declaration of interest:
The author is an employee at 3Brain.