Trump’s NIH Axed Research Grants Even After a Judge Blocked the Cuts, Internal Records Show
—

A lawsuit led by the Washington state attorney general offers an unprecedented view of the termination of more than 600 NIH grants, including transgender research grants threatened by Trump’s executive orders.
https://www.propublica.org/article/trump-nih-cuts-transgender-research-grants?utm_source=mastodon&utm_medium=social&utm_campaign=mastodon-post

#News #NIH #Science #Research #Funding #Trump #Law #Transgender

Do you want to promote an inclusive and diverse @CosyneMeeting? Join the 2025 Cosyne DEIA Committee!

We need students, postdocs, and faculty to help! For questions, contact @lukesjulson or @denisejcai. Please RT!

http://cosyne.org/#DEIA

I am thrilled to have participated in this work by Alison Comrie et al. investigating how hippocampal theta sequences support adaptive decision making in a patch foraging task.

Alison is an extremely thoughtful scientist and I think it shows in the deep thinking in this work.

I should note that this is the second product of a great three lab collaboration between the Frank, Daw, and Berke Labs (the first from Tim Krause here: https://x.com/TimAmosK/status/1694059025586102380)

Please check it out!
https://www.biorxiv.org/content/10.1101/2024.09.23.613567v1

Our team at the Berkeley Institute for Data Science (+ collaborators) is exploring ways of improving the statistical Python ecosystem. If you know statisticians / educators / researchers who use (or, especially, who cannot use) Python to do their work, I'd love to talk to them to find out what their needs are, and what can be improved! Please ask your colleagues if they would reach out—stefanv at berkeley. #python #statistics

Join us for the first Bonsai Conference, a week-long event for neuroscience researchers, computational scientists & software engineers developing and using Bonsai.

📅2-6 Dec
📍SWC, London

Register ⬇️

https://conference.bonsai-rx.org/2024/

@bonsai @GatsbyUCL

Funding for the development of open-source tools is on the rise, but support for their maintenance and dissemination, both crucial for their meaningful uptake, remains a major challenge.

By @Daharoni

https://www.thetransmitter.org/open-neuroscience-and-data-sharing/designing-an-open-source-microscope/?utm_source=mastodon&utm_medium=org-social&utm_campaign=20240617-open-source-microscope

Closed-loop modulation of remote hippocampal representations with neurofeedback https://www.biorxiv.org/content/10.1101/2024.05.08.593085v1?med=mas

RealtimeDecoder: A fast software module for online clusterless decoding https://www.biorxiv.org/content/10.1101/2024.05.03.592417v1?med=mas

What neuroscientists should know—and what they can do—about changes to BRAIN initiative funding.

By Angie Voyles Askham

https://www.thetransmitter.org/funding/what-neuroscientists-should-know-and-what-they-can-do-about-changes-to-brain-initiative-funding/?utm_source=mastodon&utm_medium=org-social&utm_campaign=20240502-what-neuroscientists

Study (N=163) finds women professors did 75% of internal service work; men 25%. Women viewed it as compliance or an investment; men dodged with evasiveness or used barter. Yet men did 50% of external service work, which was more career-enhancing. https://kifinfo.no/en/2024/03/women-end-doing-academic-housework

Amazon kills “Just Walk Out” shopping tech—it never really worked

"AI" checkout was actually powered by 1,000 human video reviewers in India.

https://arstechnica.com/gadgets/2024/04/amazon-ends-ai-powered-store-checkout-which-needed-1000-video-reviewers/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social

I was interviewed by The Economist's Babbage podcast on their series, "The science that built AI" last month. My hour long conversation was edited to about six minutes!

I am glad they edited/fit my conversation as taking the perspective that this big data, big compute driven deep-net approach is orthogonal to human/biological vision. And that, without incorporating biological principles (in this case, vision), autonomous visual navigation systems (i.e., self-driving cars) are unlikely and/or limited.

Unfortunately, the podcast requires a subscription to The Economist (I too had to access it from my university account!). But if you do have access, let me know what you think!

https://open.spotify.com/episode/4adN2gVRkQctA55Q0xswiO

#Neuroscience #History #AI #Deepnets #BiologicalIntelligence #BiologicalVision #HumanVision #MachineVision #TheEconomist #Babbage #MachineLearning

Anyone here working on #PoseEstimation #animalbehavior #neuroethology ?

You may be interested in the free and open-source Python 🐍 package I’m currently working on, together with @adamltyson @bd_peri and others.

It’s called movement, and it’s made for analysing the pose tracks produced by pose estimation frameworks, like #DeepLabCut and #SLEAP.

Website: https://movement.neuroinformatics.dev
GitHub: https://github.com/neuroinformatics-unit/movement

It’s still in early development 🏗️ but we appreciate feedback/feature requests.

Check out the detailed thread on our team’s mastodon account: @neuroinformatics

Wondering about the current state of affairs of data science and data management in neuroscience collaborations? Wondering where your tax dollars go? Well, wonder no more! Edgar Walker, Guoqiang Yu and myself collected some data! And opinions :-) https://www.biorxiv.org/content/10.1101/2024.03.20.585936v1

We'd like to introduce movement, a free and open-source Python 🐍 package for analysing body movements, designed to aid the study of animal behaviour in neuroscience.

Website: https://movement.neuroinformatics.dev

Examples: https://movement.neuroinformatics.dev/examples/index.html

GitHub: https://github.com/neuroinformatics-unit/movement

Chat with us on Zulip: https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement

Hi all, we would like to introduce you to Spyglass (https://github.com/LorenFrankLab/spyglass) - our software framework for creating reproducible data analysis and data sharing for neuroscience research (spearheaded by Kyu Hyun Lee and myself, but really a group effort by the Frank lab).

Try it for yourself without any setup at https://spyglass.hhmi.2i2c.cloud/ thanks to support from @2i2c_org, @RapidScience, @HHMINEWS. Note that there might be a slight wait for things to load.

We all know how hard it is to keep track of all the parameters and code that go into processing neuroscience data. These choices fundamentally affect the outcomes of a paper, but we have few reliable ways of recording what those choices are.

One reason for this is neuroscience data is complex and writing good code that keeps track of these choices is hard. Researchers typically create ad-hoc pipelines to existing tools for themselves, but this is time consuming and potentially error prone.

We built Spyglass to make it easy for researchers to process and track their data. We make it possible for users to spikesort and curate their data using different spike sorters via @spikeinterface, track the pose of animals via @DeepLabCut, or more complex analyses like decoding

We make all this possible using the @NeurodataWB format. We believe that starting with data in NWB and keeping analyses within this format unlocks huge potential to take advantage of tools that rely on this standard. This makes it easy to share your data on @DANDIarchive.

We realized that simply processing data is not enough. You have to visualize your data to know processing worked, but there can be a lot of data with many data types. We make this easy using figurl - an interactive web-based visualization tool by Jeremy Magland (@FlatironInst).

For example, you can visualize spike sorting curation: https://figurl.org/f?v=gs://figurl/spikesortingview-10&d=sha1://1fa0b4a1663323b49b6f1934d79ca9f67779bda8&s=%7B%22initialSortingCuration%22:%22sha1://51b950cad7d97f26aaf807ba234e4b41ffade4ef%22,%22sortingCuration%22:%22gh://LorenFrankLab/sorting-curations/main/mcoulter/molly20220316_.nwb_r1_r2/15/curation.json%22%7D&label=molly20220316_.nwb_r1_r2_15_franklab_tetrode_hippocampus%20molly20220316_.nwb_r1_r2_15_franklab_tetrode_hippocampus_13f7a6a2_spikesorting

or visualize ripple detection: https://figurl.org/f?v=gs://figurl/spikesortingview-10&d=sha1://f94ea807087b446aa0ff7f1993fbafe7a9066f79&label=Ripple%20Detection&zone=franklab.default

or even visualize decoding of hippocampal mental representations: https://figurl.org/f?v=gs://figurl/spikesortingview-10&d=sha1://3990d47cfcfbe426fae203659479e55d7b08980f&label=j1620210710_clusterless_decode&zone=franklab.default

Finally, neuroscience research is becoming more collaborative within and across labs, but sharing data is still difficult. Spyglass makes it easy for you to share data by allowing collaborators to access the database and seamlessly download data via the cloud.

If you want to find out more, please read our preprint: https://www.biorxiv.org/content/10.1101/2024.01.25.577295v2

or view our documentation and tutorials: https://lorenfranklab.github.io/spyglass/latest/

Study finds that we could lose science if publishers go bankrupt

A scan of archives shows that lots of scientific papers aren't backed up.

https://arstechnica.com/science/2024/03/study-finds-that-we-could-lose-science-if-publishers-go-bankrupt/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social

So yesterday night I wrote down my thoughts of #cosyne24 . In case you are interested, you can find them here: https://victorseven.github.io/2024/03/cosyne2024

If the post it's too long for you, the short version would be: it was great but I want better sandwiches at the lunch break and stronger philosophy in the panel discussion :)

@adredish @brembs @ScholarNexus yes, I was exaggerating a tiny bit for effect. 😉 I agree that in some cases we get some credit for the code that we write, but it's also true that it's vastly undervalued relative to its importance to science.

Let me give you an anecdote from my scientific career. In my first postdoc my supervisor and I wrote "Brian" a simulator package for spiking neural networks that has gone on to become one of the most well used in computational neuroscience. (Incidentally, we made sure to write those up as papers and they have collectively been cited thousands of times, which has been great for my career.) I was actually funded on a grant from someone more senior than my supervisor, and I had an end of year review with him. I talked all about Brian and how valuable people were already finding it, and after quietly listening he asked me "that's nice, but what work have you been doing?" He cut my funding directly after that meeting, only a few weeks before the renewal date. I wish this were just an isolated example, but my experience in science has been that very few senior people in decision-making positions have any respect for the work and importance of writing software, and that in almost all cases a junior academic would be very ill advised to spend a significant amount of their time writing and making available high quality code. I was fortunate enough to have a supervisor who finds this important, and managed to find alternative funding for me for another 3 years (partly thanks to getting an ERC). My scientific career could easily have ended right there without that luck.

GitHub is struggling to contain an ongoing attack that’s flooding the site with millions of code repositories. These repositories contain obfuscated malware that steals passwords and cryptocurrency from developer devices, researchers said.

The malicious repositories are clones of legitimate ones, making them hard to distinguish to the casual eye. An unknown party has automated a process that forks legitimate repositories, meaning the source code is copied so developers can use it in an independent project that builds on the original one. The result is millions of forks with names identical to the original one that add a payload that’s wrapped under seven layers of obfuscation. To make matters worse, some people, unaware of the malice of these imitators, are forking the forks, which adds to the flood.

“Most of the forked repos are quickly removed by GitHub, which identifies the automation,” Matan Giladi and Gil David, researchers at security firm Apiiro, wrote Wednesday. “However, the automation detection seems to miss many repos, and the ones that were uploaded manually survive. Because the whole attack chain seems to be mostly automated on a large scale, the 1% that survive still amount to thousands of malicious repos.”

https://arstechnica.com/security/2024/02/github-besieged-by-millions-of-malicious-repositories-in-ongoing-attack/