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We then tried a challenging test. Third-order ‘LHNs’ integrate stereotyped combinations of 5+ input glomeruli.
#BAcTrace revealed 12/16 connections expected from EM#connectomics data with a 10 synapse threshold. The top partner had >400 outputs onto the donor cells. 6/11pic.twitter.com/aeSGhvrzLf
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The
@janeliaflyem@HHMIJanelia@stephenplaza HemiBrain dataset is preprinted! An impressive project, I did a bit of reconstruction for it in the LH. But intrepid fly network-anatomists pay attention to its brain region completion rates: https://twitter.com/fly_papers/status/1219893344060358656 …pic.twitter.com/crO19Ev8B1
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Our work here
@flyconnectome may be one of the last big beasts of the manual reconstruction era. See a spike in productivity when@Chinasaurli made his partial neuron auto-segmentation available to us? (essential@catmaid plumbing from@perlman@tomkazimiers) https://twitter.com/fly_papers/status/1219368255157985280 …pic.twitter.com/3TYt9tmLQR
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We see clear parallels in circuit logic across 4 different olfactory areas. But there are noticeable differences: the lateral horn has extensive modulation of both incoming axons and output neurons. This may allow state / memory to gate innate behavioural pathways. 11/12pic.twitter.com/jbnKowZdah
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The other more unexpected class are 10 ‘centrifugal’ neurons. They collect their input from the mushroom body MBONs and project axons to the lateral horn. It seems most memory read-out neurons can strongly influence ‘innate’ processing in the lateral horn. 10/12pic.twitter.com/PQ9bSaJcOO
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Two other classes of neuron also give prominent input to the LH. The first are putative wind-sensitive PNs. Fascinatingly they get input from olfactory memory read-out neurons of the mushroom body (MBONs), a new motif integrating learned and innate information. 9/12pic.twitter.com/OuyInr0hZN
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Only 1/3 of input onto lateral horn dendrites comes from incoming excitatory PNs – local interneurons provide a similar amount. The LH looks particularly integrative – elsewhere the main output neurons receive most of their input from the main input neurons. 8/12pic.twitter.com/PFdxnZIvZc
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Odour channel inputs onto lateral horn (LH) neurons weren’t really known. We built 66 LH neurons and found that all neurons (even local interneurons) could be split into axon and dendrite (using
@csdashm’s algorithm). Dendrites are almost always closer to the soma. 7/12pic.twitter.com/06KfhPUowr
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A bit belated - but my supervisor
@gsxej (@MRC_LMB ,@CamZoology) gave a brilliant public lecture yesterday to a ~300 strong audience, on receipt of his Francis Crick Medal from@royalsociety. The video is going to be useful for years: https://royalsociety.org/grants-schemes-awards/awards/francis-crick-lecture/ … .... next stop, FRS?pic.twitter.com/X13hsd6SvG
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We want the community to improve the natverse! Just merged a PR from
@RFranconville to read Neuprint ROIs. Future: reading from more online databases, analysis of neurons as 3d meshes and support for other languages, e.g. to play nicely with@HCuntz ‘s MATLAB TREES toolbox 10/10pic.twitter.com/76Rb6oom9D
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This is super powerful because it allows us to repeatably find the same morphological cell types between different datasets, e.g. linking neurons sparse genetic lines (confocal microscopy) to manual/auto segmentations (flood-filling EM data,
@Chinasaurli and@stardazed0) 9/10pic.twitter.com/CwddDyBLiP
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This works if you have registered data. An important outcome is that
@gsxej and@martamcosta2 registered hundreds of fly brain images to standard template brains, made available at@virtualflybrain. Here’s@SebaCachero ‘s clones (IS2) matched with Chiang lab neurons (FCWB) 8/10pic.twitter.com/Xr2WWYT09d
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@jamesdmanton developed ‘bridging registrations’ to unify the standard templates in fly neuroscience, so you don’t need to waste time and energy re-registering different datasets. There is also support for the latest templates from@BogovicJohn and@herrsaalfeld 7/10pic.twitter.com/gk1ySsEzPt
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One of the things that set the natverse apart is that it geared to consider neurons registered to whole-brain / sub-region standard templates. This is critical in large-scale mapping projects inc connectomics. You must move data between them to compare datasets 6/10pic.twitter.com/aGZFKGAtDc
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You can look at a lot, including NeuroMorpho, http://insectbrainDB.org (
@stanley_heinze), FlyCircuit (Ann-Shyn Chiang), MouseLight (@realMouseLight), CATMAID (@tomkazimiers,@clbarnes91,@aschampion), DVID, NeuPrint (@stephenplaza, W. Katz) and NeuroGlancer (@GoogleAI) 5/10pic.twitter.com/1ulCeJWzX5
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Since ~2003,
@gsxej has been developing tools in#rstats to work with neuron data (meanwhile, I was in primary school). Today, thanks to@uni_matrix and@i_am_shri_ you can also interoperate with python 4/10pic.twitter.com/PzT8Dnp4dY
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You should also be able to install the natverse with one line of code from R (http://natverse.org/install/ ) and we have a responsive help group: https://groups.google.com/forum/#!forum/nat-user … 3/10pic.twitter.com/m65RkvtYmP
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The natverse allows you to easily plot neurons and neuroanatomical volumes, measure features and implement interesting algorithms, e.g. flow centrality
@csdashm and NBLAST@martamcosta2 http://natverse.org/gallery/ . We give lots of examples: https://github.com/natverse/nat.examples … 2/10pic.twitter.com/shSyBoRov9
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#neurotwitter
welcome to the #natverse - we’ve got tools for brains!
Open software to analyse neurons, connections, brains #bioRxiv http://www.biorxiv.org/content/10.1101/006353v3 … Others are using it, why should you? http://natverse.org :@gsxej lab@MRC_LMB@flyconnectome@CamZoology#rstats 1/10pic.twitter.com/gjAaP76E5W
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Bailey’s Drosophila-vial lab ‘shots’ at
@gsxej’s lab party.pic.twitter.com/6czleNSZpL
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