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Story time! Single neurons in the brain can’t be depended on for reliable information. Here are some neurons from our recent study, recorded twice in response to the same visual stimuli. Different neurons are active at different times!
biorxiv.org/content/10.110…
biorxiv.org/content/10.110…
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Carsen Stringer @Computingnature@neuromatch.social retweeted
The first preprint of my postdoc with @jtdudman
is now online! Here we wanted to understand the algorithms mice use when learning to forage in large environments with many potential resources. 1/n biorxiv.org/content/10.110…
is now online! Here we wanted to understand the algorithms mice use when learning to forage in large environments with many potential resources. 1/n biorxiv.org/content/10.110…
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Did you vote today!?!?!?
Polls were busy in #virginia this morning! FYI #virginia has same day voter registration! elections.virginia.gov/registration/s…
Polls were busy in #virginia this morning! FYI #virginia has same day voter registration! elections.virginia.gov/registration/s…
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Carsen Stringer @Computingnature@neuromatch.social retweeted
Amazing talk about imaging and discovering C. elegans embryogenesis by Hari Shroff from @HHMIJanelia presenting at #I2K2024
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Carsen Stringer @Computingnature@neuromatch.social retweeted
🖥️ Rastermap, a new visualization tool developed by the Stringer (@computingnature) & Pachitariu (@marius10p) labs, helps scientists uncover activity patterns in large-scale neural recordings. 🧠
🔗janelia.org/news/new-tool-…
🔗janelia.org/news/new-tool-…
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Carsen Stringer @Computingnature@neuromatch.social retweeted
We performed ephys recordings, in head-fixed and freely moving animals, and found the head-direction system boosts its gain when a landmark is seen—suggesting a mechanism that signals stronger confidence in vision when natural objects are present. 4/
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Carsen Stringer @Computingnature@neuromatch.social retweeted
@eric_denovellis @computingnature 👆 good use case examples/tutorials help a lot!
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Carsen Stringer @Computingnature@neuromatch.social retweeted
@computingnature Guidance for implement on HPC. Colab demo notebook. Suggestions on data size limitation.
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Carsen Stringer @Computingnature@neuromatch.social retweeted
Great tips! We’ve been through this with @thepynapple, to do it properly is much harder than you can imagine.
Six tips for going public with your lab’s software: nature.com/articles/d4158…
1) make time for maintenance
2) simplify installation
3) add a GUI or good CLI
4) good documentation
5) use github/git
6) automated testing
Any other tips people have?
#OpenScience #OpenSource
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Carsen Stringer @Computingnature@neuromatch.social retweeted
@computingnature Video tutorials like your for using Cellpose
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Six tips for going public with your lab’s software: nature.com/articles/d4158…
1) make time for maintenance
2) simplify installation
3) add a GUI or good CLI
4) good documentation
5) use github/git
6) automated testing
Any other tips people have?
#OpenScience #OpenSource
1) make time for maintenance
2) simplify installation
3) add a GUI or good CLI
4) good documentation
5) use github/git
6) automated testing
Any other tips people have?
#OpenScience #OpenSource
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Carsen Stringer @Computingnature@neuromatch.social retweeted
We are excited to introduce PetaKit5D, a comprehensive suite of software tools designed to tackle challenges in the handling of large datasets and make processing of petabyte-scale datasets feasible: nature.com/articles/s4159…
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Carsen Stringer @Computingnature@neuromatch.social retweeted
This is a *beautiful* paper and method, and while the paper itself is very careful about drawing conclusions from the variety of datasets it analyzes, I'd say the edifice of "the brain is chaotic" hypothesis is crumbling!
📢 #Rastermap paper out now, easily explore and visualize your neural recordings 🐭🐒🐟 and ANNs 🤖 nature.com/articles/s4159…. Updates from preprint include analyses of primate data and IBL task data.
Video tutorial: youtu.be/oQHq7yUWn2k #Neuroscience #MachineLearning
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Carsen Stringer @Computingnature@neuromatch.social retweeted
Wonderful tool for exploring neural data! Stationary and dynamic patterns, all in one place and along a single dimension. Not a petri dish mold-shaped point-cloud in sight. It’s become one of my favorite ways of trying to guess at what neurons are up to.
Make your next discovery using #Rastermap, a visualization method for large-scale neural data. Paper now out, w/ @marius10p : biorxiv.org/content/10.110…
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📢 #Rastermap paper out now, easily explore and visualize your neural recordings 🐭🐒🐟 and ANNs 🤖 nature.com/articles/s4159…. Updates from preprint include analyses of primate data and IBL task data.
Video tutorial: youtu.be/oQHq7yUWn2k #Neuroscience #MachineLearning
Video tutorial: youtu.be/oQHq7yUWn2k #Neuroscience #MachineLearning
Make your next discovery using #Rastermap, a visualization method for large-scale neural data. Paper now out, w/ @marius10p : biorxiv.org/content/10.110…
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Carsen Stringer @Computingnature@neuromatch.social retweeted
It's the middle of breast cancer awareness month! I must admit I dislike getting mammograms. It's not the procedure, it's just the fear of the unknown. But, breast cancer can be very treatable if caught early, so please get checked!
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Carsen Stringer @Computingnature@neuromatch.social retweeted
@KordingLab and I efficiently optimize high-dimensional biophysical neuron models with heterogeneous active dendrites using the gradient-based backpropagation of error algorithm typically used to train models in deep learning. Preprint on arxiv: arxiv.org/abs/2407.04025 1/18
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Do we really need neural networks to predict the activity of ~real~ neurons? Yes, but we can make them a lot simpler, at least in V1 of 🐭+🐒 #minimodels #neuroAI
🚨Preprint‼️
1/ Predicting neural activity is notoriously difficult and requires complicated models. Here we develop simple “minimodels” which explain 70% of neural variance in V1! 🐭🐒 #neuroai @computingnature @marius10p @NunezKant
Paper: biorxiv.org/content/10.110…
Recording 🔬 :
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