Lmst

@plaidtron3000 @uni_matrix

Good question. Surely all the bug reports and interface and workflow improvements contributed immensely, as did the drive to improve the CNNs doing the segmentation. The actual training data I doubt it: the nature of the images is dramatically different.

First, the retina EM volume was stained for extracellular contrast, and synapses or intracellular organelles weren't visible.

Second, the resolution and imaging modality are vastly different, with the retina imaged with SBEM at about 12x12x25 nm per pixel, whereas the female adult #Drosophila brain (#FAFB) was imaged at 4x4x40 nm per pixel with ssTEM. Both are anisotropic but rather very differently so.

@perlman @davi

And then led to #FAFB and to this:
https://mathstodon.xyz/@albertcardona/113238565283630500

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

#neuroscience #Drosophila #connectomics #FAFB

a, All neuron morphologies reconstructed with FlyWire. All neurons in the central brain and both optic lobes were segmented and proofread. Note that image and dataset are mirror inverted relative to the native fly brain. b, An overview of many of the FlyWire resources that are being made available. FlyWire leverages existing resources for electron microscopy imagery by Zheng et al., synapse predictions by Buhmann et al. and Heinrich et al., and neurotransmitter predictions by Eckstein et al.. Annotations of the FlyWire brain dataset such as hemilineages, nerves and hierarchical classes are established in the accompanying paper. c, FlyWire uses CAVE50 for proofreading, data management and analysis back end. The data can be accessed programmatically through CAVEclient, navis, fafbseg and natverse, and through the browser in Codex, Catmaid Spaces and braincircuits.io. Static exports of the data are also available. d, The Drosophila brain can be divided into spatially defined regions based on neuropils80 (Extended Data Fig. 1). Neuropils for the lamina are not shown. D, dorsal; L, lateral; P, posterior. e, Synaptic boutons in the fly brain are often polyadic such that there are multiple postsynaptic partners per presynaptic bouton. Each link between a pre- and a postsynaptic location is a synapse. f, Neuron tracts, trachea, neuropil and cell bodies can be readily identified from the electron microscopy data acquired by Zheng et al.. Scale bar, 10 μm.

The connectome of the adult female fly brain, Drosophila melanogaster:

“Neuronal wiring diagram of an adult brain” by Dorkenwald et al. 2023 https://www.biorxiv.org/content/10.1101/2023.06.27.546656v1

A project that started with Davi Bock and Wei Lee developing the TEMCA for the mouse visual cortex in Clay Reid’s lab (Bock et al. 2011 https://www.nature.com/articles/nature09802), then Bock moving to #HHMIJanelia and developing the instrument much further to deliver the #FAFB volume (Zheng et al. 2018 https://www.sciencedirect.com/science/article/pii/S0092867418307876 ), and then the Seung, Murthy and Jefferis labs automatically re-registering, segmenting and annotating the whole volume via #FlyWire and more.

Extraordinary!

#Drosophila #connectomics #neuroscience #brain

Figure 1. A connectomic reconstruction of a whole fly brain. (a) All neuron morphologies reconstructed with FlyWire. All neurons in the central brain and both optic lobes were segmented and proofread. Note: image and dataset are mirror inverted relative to the native fly brain. (b) An overview of many of the FlyWire resources which are being made available. FlyWire leverages existing resources for EM imagery by (Zheng et al. 2018), synapse predictions by (Buhmann et al. 2021; Heinrich et al. 2018) and neurotransmitter predictions by (Eckstein et al. 2023). Annotations of the FlyWire dataset such as hemilineages, nerves, and hierarchical classes are established in our companion paper by Schlegel et al. (c) FlyWire uses CAVE for proofreading, data management, and analysis backend. The data can be accessed programmatically through the CAVEclient, navis and natverse (Bates et al. 2020), and through the browser in Codex, Catmaid Spaces and braincircuits.io. Static exports of the data are also available. (d) The Drosophila brain can be divided into spatially defined regions based on neuropils (Ito et al. 2014) (Ext. Data Fig. 1-1). (e) Synaptic boutons in the fly brain are often polyadic such that there are multiple postsynaptic partners per presynaptic bouton. Each link between a pre- and a postsynaptic location is a synapse. (f) Neuron tracts, trachea, neuropil, cell bodies can be readily identified from the EM data which was acquired by Zheng et al. 2018. Scale bar: 10 μm

"A leaky integrate-and-fire computational model based on the connectome of the entire adult Drosophila brain reveals insights into sensorimotor processing", by Shiu et al. 2023, from Kristin Scott's lab https://www.biorxiv.org/content/10.1101/2023.05.02.539144v1.full

"Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations."

#connectomics #Drosophila #FAFB #neuroscience

#FAFB

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