Full-scale scaffold model of the human hippocampus CA1 area.
Daniela GandolfiJonathan MapelliSergio M G SolinasPaul TriebkornEgidio D'AngeloViktor JirsaMichele MigliorePublished in: Nature computational science (2023)
The increasing availability of quantitative data on the human brain is opening new avenues to study neural function and dysfunction, thus bringing us closer and closer to the implementation of digital twin applications for personalized medicine. Here we provide a resource to the neuroscience community: a computational method to generate full-scale scaffold model of human brain regions starting from microscopy images. We have benchmarked the method to reconstruct the CA1 region of a right human hippocampus, which accounts for about half of the entire right hippocampal formation. Together with 3D soma positioning we provide a connectivity matrix generated using a morpho-anatomical connection strategy based on axonal and dendritic probability density functions accounting for morphological properties of hippocampal neurons. The data and algorithms are supplied in a ready-to-use format, suited to implement computational models at different scales and detail.
Keyphrases
- endothelial cells
- cerebral ischemia
- healthcare
- high resolution
- induced pluripotent stem cells
- deep learning
- pluripotent stem cells
- electronic health record
- machine learning
- big data
- optical coherence tomography
- primary care
- mental health
- spinal cord
- oxidative stress
- cognitive impairment
- mass spectrometry
- tissue engineering
- single molecule
- high throughput
- white matter
- high speed
- temporal lobe epilepsy
- blood brain barrier