In:
Nature Computational Science, Springer Science and Business Media LLC, Vol. 3, No. 3 ( 2023-03-23), p. 264-276
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
2662-8457
DOI:
10.1038/s43588-023-00417-2
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2023
detail.hit.zdb_id:
3029424-1
