Sign in
NeuroscienceNature Communications
Peer-reviewed journal article

Generating brain-wide connectome using synthetic axonal morphologies

Rémy PetkantchiniD, Adrien BerchetiD, Hanchuan PengiD, Henry MarkramiD, Lida KanariiD

Abstract

Recent experimental advancements, including electron microscopy reconstructions, have produced detailed connectivity data for local brain regions. On the other hand, for inter-regional connectivity, large-scale imaging techniques such as MRI are best suited to provide insights. However, understanding the relationship between local and long-range connectivity is essential for studying both healthy and pathological conditions of the brain. Leveraging a novel dataset of whole-brain axonal reconstructions, we present a technique to predict whole-brain connectivity at single cell level by generating detailed whole-brain axonal morphologies from sparse experimental data. The computationally generated axons accurately reproduce the local and global morphological properties of experimental reconstructions. Furthermore, the computationally synthesized axons generate large-scale inter-regional connectivity, defining the projectome and the connectome of the brain, thereby enabling the in silico experimentation of large brain regions.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
4
FWCI
1.72
Field percentile
top 17%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBerchet '25Kanari '22Reimann '19Shen '19Drenkow '20Torres '24
77% semantic matchNeuroscience
Adrien Berchet, Rémy Petkantchin, Henry Markram+1 more·Neuroinformatics·Jan 10, 2025· 3 citations