Abstract
There is growing evidence that mechanical factors affect brain functioning. However, brain components responsible for regulating the physiological mechanical environment are not completely understood. To determine the relationship between structure and stiffness of brain tissue, we performed high-resolution viscoelastic mapping by dynamic indentation of the hippocampus and the cerebellum of juvenile mice brains, and quantified relative area covered by neurons (NeuN-staining), axons (neurofilament NN18-staining), astrocytes (GFAP-staining), myelin (MBP-staining) and nuclei (Hoechst-staining) of juvenile and adult mouse brain slices. Results show that brain subregions have distinct viscoelastic parameters. In gray matter (GM) regions, the storage modulus correlates negatively with the relative area of nuclei and neurons, and positively with astrocytes. The storage modulus also correlates negatively with the relative area of myelin and axons (high cell density regions are excluded). Furthermore, adult brain regions are ∼ 20%–150% stiffer than the comparable juvenile regions which coincide with increase in astrocyte GFAP-staining. Several linear regression models are examined to predict the mechanical properties of the brain tissue based on (immuno)histochemical stainings.
Highlights
There is an increasing interest in the mechanical properties of the brain due to the emerging role of physiological mechanical environment in normal brain functioning and involvement of mechanics in disease progression (Barnes et al, 2017)
To characterize local mechanical properties of hippocampus and cerebellum, dynamic indentation mapping was performed on acute mouse brain slices at 50 μm resolution by indenting with an oscillating ramp at 5.6 Hz frequency up to 8% strain
The viscoelastic properties were quantified in terms of storage E′ and loss E′′ moduli, and damping factor tan(δ), which is the ratio between loss and storage modulus
Summary
There is an increasing interest in the mechanical properties of the brain due to the emerging role of physiological mechanical environment in normal brain functioning and involvement of mechanics in disease progression (Barnes et al, 2017). It is not surprising that the different brain regions have heterogeneous mechanical properties (Budday et al, 2015; Weickenmeier et al, 2016; van Dommelen et al, 2010; Kaster et al, 2011; Feng et al, 2013; Forte et al, 2017; Christ et al, 2010; Koser et al, 2015; Samadi-Dooki et al, 2017; Finan et al, 2012b; Elkin et al, 2011a; Elkin and Morrison, 2013; Elkin et al, 2010) and that there exists a relationship between some of the components and stiffness (Moeendarbary et al, 2017; Weickenmeier et al, 2016, 2017; Budday et al, 2020) Despite this body of work, how the mechanical properties and structural composition of the brain relate to each other remains elusive
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