or Lou Gehrig's disease can all be affected by this mechanism.
The study has been published in the journal
, which is a publication of the American Physical Society.
The importance of
this modeling study lies in the fact that it is the first attempt to link the
micro and macro level approaches. This encompasses the subtle interactions of
the molecules (micro level) to the whole brain (macro level) through brain
imaging. The study has the potential to open new vistas in the area of
computer-based brain modeling.
Weickenmeier, Professor of Mechanical Engineering at the Stevens Institute of
Technology and lead author of the study, says: "This is a first attempt to
bridge scales between the cellular level and the whole-organ level. The key is to
couple biochemistry to the biomechanics of the brain to better understand the
dynamics of these diseases."
Weickenmeier is known for pioneering a technique for the development of a 'digital
utilizing a 3D software to recreate the
complex structure of the brain. He used over 400,000 pyramid-shaped virtual
blocks to construct the highly convoluted structure, one block at a time.
Data generated by
diffusion tensor imaging, a technique that maps the direction of neuronal signal
transmission in the brain, was overlaid on Weickenmeier's digital model of the
brain. This digital model could be used to visualize the anatomical structures
of the brain, as well as detect the transmission pattern of the various
neuronal signals traversing through them.
his team, including collaborators from Stanford University and Oxford
University, utilized equations similar to those used for measuring the flow of
heat across solid materials to model the spread of toxic proteins through the
It is well
established that various types of neurodegenerative diseases exhibit different
biochemical features as well as different symptoms. However, the digital model
could reconstruct the distinct atrophy patterns of Alzheimer's
, Parkinson's disease and other neurodegenerative diseases,
simply by altering the point of origin of the toxic proteins in the brain.
Weickenmeier indicated that the atrophy patterns were inherently generated by
the digital model.
The study found
that the toxic proteins travel to various regions of the brain, where they
produce distinct symptoms that correspond with the type of neurodegenerative
The computer simulations indicated that the vast neuronal network throughout
the brain was crucial for the flow of the toxic proteins from one point to
another point in the brain. Therefore, the progression of neurodegenerative
diseases depends exclusively on this extensive neuronal connectivity.
modeling is still in its infancy. Currently, there is a dearth of imaging data
on which the model's predictions can be based for verifying its accuracy.
However, with the availability of more imaging data in the future, this digital
brain modeling approach could lead to the development of early diagnosis and
treatment strategies for various neurodegenerative diseases, including multiple
sclerosis, chronic traumatic encephalopathy, and others.
"These medically relevant diseases, such as Alzheimer's disease and other
neurodegenerative diseases are the motivation for our 'in silico' models." He
adds: "They allow us to strategically run different simulations to test
individual hypotheses of disease progression and see which new approaches seem
- Multiphysics of Prionlike Diseases: Progression and Atrophy - (https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.121.158101)