Background:
At first glance, physical phenomena might seem mostly unimportant when it comes to studying the functional activity of neuronal networks. Yet with aging, traumatic brain injury, or neurodegeneration comes the perturbation of the intrinsic mechanical properties and extrinsic mechanical environment of brain tissue, which begs the question:
“How are our neuronal networks impacted when the physics of the hardware changes?”
Biology is also physics
First we have to ask: What are mechanical properties when it comes to cells and tissues?
Our cells do not live in a vacuum, but are embedded in a physical universe and thus susceptible to many physical forces. By one definition, the way how our cells and tissues interact with these physical forces can be understood as their mechanical properties.
Mechanical properties can be measured by applying tensile, compression and shear forces. They describe the internal resistance of a material to distortion by an external force. - Hall CM. et al., European Journal of Neuroscience, 2020
Furthermore, we (and arguably most lifeforms) have evolved organs and molecular mechanisms that can sense physical forces, which is a big help in navigating our environment through behavioral adaptation to physical perturbations.
Mechanosensation is a somewhat understood phenomenon when it comes to sensory neurons which specialize in transducing mechanical stimuli that underlie e.g hearing, mechanical sensation, and pain (Marshall & Lumpkin, Advances in Experimental Medicine and Biology, 2012).
However, mechanosensation is not limited to sensory neurons
Studies of tactile sensation show, for example by investigating Meissner’s corpuscles which are located in the skin and are sensitive to light touch, and Pacinian corpuscles that are located deeper in the skin and are sensitive to pressure and vibration, that R-type voltage gated calcium channels in non-neuronal mechanosensors can also create action potentials (Nikolaev YA et al., ScienceAdvances, 2020). You read that right. Proximal (lamellar) non-neuronal cells can produce an action potential with distinct electrophysiological profile by themselves, a clear indication that the mechanoenvironment of afferent neurons shapes neuronal output.
In general, mechanically activated cation channel activities have been reported for many different cell types (Coste B. et al., Science, 2010), often mediated by Piezo1 and Piezo2 transmembrane proteins and other ion channel proteins.
While not the only molecular mediators, a widespread role has been ascribed to Piezo proteins for example in translating sheer stress into electrochemical signal that in turn shape physiology & performance in athletes (Passini FS et al., Nat Biomed Eng., 2021). The adaptation benefit is clear.
Interestingly, much of the wider molecular machinery that is involved in mechanosensation can be found beyond our sensing organs, including in different human brain areas and cell types as well (Hall CM. et al., European Journal of Neuroscience, 2020), and this is where physics might hit our neuronal networks, literally.
Hitting the soft spot is not smart
When thinking about mechanical perturbation of the brain, the most visceral pictures of football or hockey players, or professional boxers getting their heads punched comes to mind. What happens to our cognitive function when our brain, and it’s embedded neuronal networks, have to pack a punch? Or even get a concussion?
Well, as most could guess, nothing good. Correlations of blast or impact head injuries with a range of neuropathologies have been known for almost a century, it is so common place that recent discussions are more about how to classify, organize and manage sport injuries (Mcrory P et al., BMJ Sport medicine, 2013) rather than establishing whether they do long term harm.
What is more surprising is that a comprehensive recent study by Tagge et al, using post-mortem brains of athletes and an impact concussion mouse model, finds that these injury-related pathologies:
[…] were also accompanied by early, persistent, and bilateral impairment in axonal conduction velocity in the hippocampus and defective long-term potentiation of synaptic neurotransmission in the medial prefrontal cortex, brain regions distant from acute brain injury. - (Tagge CA. et al., Brain, 2018)
Tagge et al.’s long and comprehensive study to better understand the mechanisms underpinning concussion, traumatic brain injury, and chronic traumatic encephalopathy is certainly worth reading in full, but for our purposes, there is one interesting picture emerging. Their observations suggest that repeat head injuries (i.e physical/mechanical perturbations), even in the absence of concussion, may induce late-onset brain pathologies through altering the long-term function of neuronal networks even when no acute structural damage was incurred.
[…] our results point to a disturbance of brain function (as opposed to structural lesions) as the aetiological origin of the concussion-like neurobehavioural deficits that we observed after impact injury. Our findings indicate that, while impact injury and blast exposure elicit similar long-term neuropathology and sequelae, these insults starkly differentiate the concussion-like syndrome produced by the former (impact), but not the latter (blast)
This is a curious finding and justifies looking deeper into the interplay between mechanical forces, physical properties of cells and tissues, and their impact on neuronal networks.
The mechanics of a soft organ
Outside of traumatic injury, there is a growing interest in how physiological mechanical forces and properties of tissues shape our brain throughout life.
For example, the physical properties of the developing brain have been determined as one of the major driving forces of gyrification, the folding of cortical surface (Budday S. et al., Front Cell Neurosci., 2015).
So right from our humble beginnings, physical forces shape the larger cytoarchitecture that our neuronal networks are embedded in
But do physical properties also define what connections and circuits our neurons form?
While axon guidance (and neurite projection) is often explained through chemotaxis and gradients of chemotactic molecules such as netrin or semaphorin (Xu Z. et al., Nature Communications, 2018), comparative studies in frogs showed that e.g. retinal ganglion cell axons appear to migrate along local stiffness gradients, with growth cones becoming more exploratory and terminating in softer optic tectum brain tissue (Koser et al., Nature Neuroscience, 2016). How much of neurite projection and circuit formation is influenced by the physical diversity in human brain regions is at this moment quite unexplored. Without getting a detailed understanding of the physical complexity of our brain, researchers are at risk of missing an important factor contributing to the brain’s complexity barrier.
In recent years, many researchers have contributed to charting a map of different stiffness gradients (see below) throughout the brain, which might also help explain some neuronal wiring behavior and network formation beyond biological signals.
However, studying mechanotransduction pathway at physiological force range is still immensely difficult with current methods, given that relevant molecular forces (outside of trauma) are typically in the picoNewton (pN) range (Jurchenko C. et al., Biophysical Journal, 2014)
Several methods have been developed to apply mechanical forces to living cells. Experimental strategies, such as shear stress or substrate stretch stress, have been the golden standard in the field of mechanobiology; however, these techniques apply forces at multiple points in the cell, hiding the identification of mechanoreceptors and cellular components involved in the transduction process. To overcome this apparent limitation, other techniques of local mechanics on a specific region of the cell are needed [...] which are capable of exerting localized low picoNewton (pN) vertical indentation of the order of 10-50 pN applied to cell membranes & may provide a valuable experimental tool to study neuronal mechanobiology at the physiological level. — Fabio Falleroni, PhD (personal communication)
New techniques like oscillatory optical tweezers (Falleroni F. et al., iScience, 2022) or ferrule-top micro-indentation (Marrese M et al., Front Neurosci., 2019) might help with instigating physiologically appropriate physical perturbation. Furthermore, high resolution methods to record, track and analyze these subtle changes in functional network activity from model systems like brain slices (Mapelli L. et al, biorxiv, 2022) are likely needed as well.
Complex mechanobiological interactions is a field ripe for new discoveries.
We are now beginning to understand how neuronal and glial cell mechanics and brain tissue mechanobiology are intimately linked with neurophysiology and cognition — Hall CM. et al., European Journal of Neuroscience, 2020
Conclusion
Mechanobiology is an fascinating area of research and has seen renewed interest in recent decades with the identification of many mechanosensitive mechanisms and cell types spread throughout the body, including the brain.
Neuroscientists might be hesitant to consider adding yet another layer of complexity when studying brain function, but some of these biophysical interactions might also hold the key to understand the altered neuronal activity of various widespread pathology phenotypes, from Alzheimer’s disease to aging to traumatic brain injury.
Time will tell.
What we can say today with certainty is that for neuronal networks, in addition to the usual electrical and chemical signaling, mechanical signaling is part of the bigger picture.
We live in a physical universe that even the most intricate biology can not hope to escape from. But what we can reasonably hope for is to gain a more comprehensive scientific understanding of the world and the forces shaping it.
References
Coste B. et al., Science, 2010
Mcrory P et al., BMJ Sport medicine, 2013
Jurchenko C. et al., Biophysical Journal, 2014
Budday S. et al., Front Cell Neurosci., 2015
Koser et al., Nature Neuroscience, 2016
Xu Z. et al., Nature Communications, 2018
Marrese M et al., Front Neurosci., 2019
Nikolaev YA et al., Science Advances, 2020
Hall CM. et al., European Journal of Neuroscience, 2020
Passini FS et al., Nat Biomed Eng., 2021
Falleroni F. et al., iScience, 2022
Mapelli L. et al, bioarxiv, 2022
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Declaration of interest:
The author is an employee at 3Brain.
