Using EBRAINS modelling tools to investigate the relationship between brain structure and function
Every human brain is different. But even with structural differences, individual brains function in a similar way. In other words, there are functional brains based on completely different configurations. At the same time, a structural change may cause loss of function in one brain, but have no consequences in another individual. Or a drug cocktail may be efficient for one patient, and have no effects for another.
This phenomenon of multiple configurations leading to the same result is called “degeneracy” and represents a key obstacle in neuroscience, as it makes it harder to know the correspondence between brain activity and brain function.
This research demonstrates how cutting-edge datasets on structural variability can be used to build whole-brain models that can help us understand the brain and its functional variability. It establishes a link between the EBRAINS Multilevel Human Brain Atlas and The Virtual Brain (TVB) simulator – a platform for constructing and simulating personalised brain network models.
The starting point of this work was the creation of a virtual cohort of ageing brains, from the large database of the 1000BRAINS study of the Jülich Research Centre in Germany. In this population-based cohort study, more than 1,000 people with ages between 55 and 85 have been examined by magnetic resonance imaging (MRI), which generated an unprecedented amount of data.
In order to create this virtual cohort, the researchers extracted the structural data from the 1000BRAINS and systematically characterised the connectome information for every single subject’s brain.
The researchers are doing exactly that: taking a model-based approach in order to disentangle ageing mechanisms, which are difficult to be figured out due to neurodegeneracy.
In order to understand how variability might work in the brain, the researchers hypothesize ageing mechanisms, then integrate the detailed data on ageing into virtual brain models, and simulate the functional brain imaging data of individual brains. Then, they can compare the output of these data-driven models to their experimental data. This way they can test whether the hypotheses of how the brain changes are confirmed.
The scientists expect that, ultimately, a better understanding of brain variability will assist in the effort to deliver personalised brain medicine, for instance, for patients with disorders such as Parkinson’s disease or dementia.
Degeneracy is a fundamental question of neuroscience that had not yet been approached in this way. The scientists are going through uncharted territory, and while the outcomes of these efforts are still open, they will definitely represent significant advances on brain simulations.
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