Our brains can splinter 10 times more easily than polystyrene foam

"It really is probably a lot softer than most people realize.”
Nergis Firtina
Illustration light brown organic glossy human brain.
Illustration light brown organic glossy human brain.


The human brain is one of our "completely" unsolved organs, with its physiology and biology. It still embodies many mysteries. Soft as cake but very strong at the same time. In light of a new study from Cardiff University, the brain breaks ten times more easily than polystyrene foam.

Published in the Journal of Royal Society Interface's 197th issue, Nicholas Bennion and his team developed a method to understand the brain's physical characteristics of living people better in the study.

As initially reported by New Scientist, they determined various material properties of the brain and tissues that connect it to the skull by combining a machine learning algorithm with MRI scans of patients lying face down and then facing up to move the placement of the brain in the skull. They measured the brain's ability to collapse under pressure, how it responds to being pushed in a lateral direction, and how bouncy the connective tissues are.

Our brains can splinter 10 times more easily than polystyrene foam
Brain MRI scan.

"If you take a brain, which hasn't been preserved in any way, its stiffness is incredibly low, and it breaks apart very easily. And it really is probably a lot softer than most people realize," says Bennion.

In addition to being softer than polystyrene foam, Bennion and his team also figured out brain is 1,000 times less resilient to sideways pressure than rubber would be, making it as pliable as a slab of gelatin. 

The study was carried out on 11 subjects

The MRI study was carried out in conjunction with Cardiff University Brain Imaging Research Centre on 11 subjects ( seven male, four female) aged between 22 and 30, as per the study. To make sure the brain had fully relaxed after 20 minutes of pre-conditioning face down, only one prone photograph was captured. Then, after being inverted to the typical supine position, the subjects were scanned again.

The prone and supine images were first aligned using affine registration of the skull alone to measure displacement across the cerebrum. A vector displacement field was then created over the full volume in individual subject space by deformable registration from the prone to supine images.

With the help of pre-operative MRI scans, the team wants to utilize their model to forecast brain changes that will happen during surgery for each unique patient. This may make operations less invasive by eliminating the need to repeatedly implant tools into the brain until they find the right location.

Study abstract:

Computational modelling of the brain requires accurate representation of the tissues concerned. Mechanical testing has numerous challenges, in particular for low strain rates, like neurosurgery, where redistribution of fluid is biomechanically important. A finite-element (FE) model was generated in FEBio, incorporating a spring element/fluid–structure interaction representation of the pia–arachnoid complex (PAC). The model was loaded to represent gravity in prone and supine positions. Material parameter identification and sensitivity analysis were performed using statistical software, comparing the FE results to human in vivo measurements. Results for the brain Ogden parameters µ, α and k yielded values of 670 Pa, −19 and 148 kPa, supporting values reported in the literature. Values of the order of 1.2 MPa and 7.7 kPa were obtained for stiffness of the pia mater and out-of-plane tensile stiffness of the PAC, respectively. Positional brain shift was found to be non-rigid and largely driven by redistribution of fluid within the tissue. To the best of our knowledge, this is the first study using in vivo human data and gravitational loading in order to estimate the material properties of intracranial tissues. This model could now be applied to reduce the impact of positional brain shift in stereotactic neurosurgery.

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