Whole adult fly brain connectome for FAFB (female adult fly brain) – last year in preprint form, today as an immersive feature in Nature.
140,000 neurons, over 50 million synapses – organised into over 8,000 cell types. (VNC not included.)
https://www.nature.com/immersive/d42859-024-00053-4/index.html
The whole connectome: Dorkenwald et al. 2024 (Seung, Murthy) https://www.nature.com/articles/s41586-024-07558-y
Cell types: Schlegel et al. 2024 (Jefferis) https://www.nature.com/articles/s41586-024-07686-5 by @uni_matrix
Network statistics: Lin et al. 2024 (Murthy) https://www.nature.com/articles/s41586-024-07968-y
Visual system: Garner et al. 2024 (Wernet, Kim) https://www.nature.com/articles/s41586-024-07967-z and Matsliah et al. (Murthy, Seung) https://www.nature.com/articles/s41586-024-07981-1
Seung also put out a solo paper on predicting visual function from the connectome: https://www.nature.com/articles/s41586-024-07953-5
Control of halting in walking: Sapkal et al. 2024 (Bidaye) https://www.nature.com/articles/s41586-024-07854-7
FAFB imaged by @davi 's group back in 2018: https://www.cell.com/cell/fulltext/S0092-8674(18)30787-6
@albertcardona @uni_matrix @davi
Is there a table format of different features, formats, usages, integrations, etc. Or intro readings for prime overview of such may connectomics software tools?
The closest thing I can think of is a paper from 2022: "A Survey of Visualization and Analysis in High-Resolution Connectomics" (PDF linked below) - you can browse an interactive version of it at https://connectomics-vis-survey.github.io/
The technological landscape is pretty complex - although it feels like we are starting to see some convergence when it comes to data backends.
Link to paper PDF: https://vcg.seas.harvard.edu/publications/connectomics-survey/paper
ps: also includes nice paragraph on #TrakEM2 by @albertcardona et al. w/ remark on alignments errors auto correction.
As for #catmaid collaborative annotation & neuronal structures skeletons approach!
@uni_matrix @albertcardona @davi
Oh many thanks P! for sharing this paper & repo, it is even more than I could expecting for!
Authors really did teaching explains for understanding the inners of all the bio structures together with all the tech involved in data acquisition, processing, classification, computing, visualization & exploration.
Also all paper tables & figures so crucial to learn, understand, & think about current #connectomics #omics tech tools!