Janne Lappalainen
@lappalainenjk.bsky.social
machine learning, connectomics, comp neuro
Pinned
Ever wanted to do deep learning with a neural net that is one-to-one mapped to 65.05% of the fruit fly brain? 😄
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Reposted by Janne Lappalainen
Our work on training biophysical models with Jaxley is now out in @natmethods.nature.com. Led by @deismic.bsky.social, with @philipp.hertie.ai, @ppjgoncalves.bsky.social & @jakhmack.bsky.social et al.
Paper: www.nature.com/articles/s41...
Paper: www.nature.com/articles/s41...
Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics - Nature Methods
Jaxley is a versatile platform for biophysical modeling in neuroscience. It allows efficiently simulating large-scale biophysical models on CPUs, GPUs and TPUs. Model parameters can be optimized with ...
www.nature.com
November 13, 2025 at 1:08 PM
Our work on training biophysical models with Jaxley is now out in @natmethods.nature.com. Led by @deismic.bsky.social, with @philipp.hertie.ai, @ppjgoncalves.bsky.social & @jakhmack.bsky.social et al.
Paper: www.nature.com/articles/s41...
Paper: www.nature.com/articles/s41...
Reposted by Janne Lappalainen
🪰 A new ‘Eyemap’ developed by a team led by Arthur Zhao & @michaelreiser.bsky.social reveals how visual information detected by the fly’s eye shows up in neurons deep in the brain. Remarkably, the eye’s shape determines how flies see motion.👁️
🔗 hhmi.news/4kSZjou
🔗 hhmi.news/4kSZjou
July 23, 2025 at 3:18 PM
🪰 A new ‘Eyemap’ developed by a team led by Arthur Zhao & @michaelreiser.bsky.social reveals how visual information detected by the fly’s eye shows up in neurons deep in the brain. Remarkably, the eye’s shape determines how flies see motion.👁️
🔗 hhmi.news/4kSZjou
🔗 hhmi.news/4kSZjou
Reposted by Janne Lappalainen
Computational sciences can offer a unique opportunity for democratized access and participation, but we are currently falling far short of that goal, writes @neuromatch.bsky.social's @meganakpeters.bsky.social and Bradley Roberts.
#neuroskyence
www.thetransmitter.org/education/ho...
#neuroskyence
www.thetransmitter.org/education/ho...
How to build a truly global computational neuroscience community
Computational sciences offer an opportunity to increase global access to, and participation in, neuroscience. Neuromatch’s inclusive, scalable model for community building shows how to realize this…
www.thetransmitter.org
July 23, 2025 at 2:01 PM
Computational sciences can offer a unique opportunity for democratized access and participation, but we are currently falling far short of that goal, writes @neuromatch.bsky.social's @meganakpeters.bsky.social and Bradley Roberts.
#neuroskyence
www.thetransmitter.org/education/ho...
#neuroskyence
www.thetransmitter.org/education/ho...
Reposted by Janne Lappalainen
In the physical world, almost all information is transmitted through traveling waves -- why should it be any different in your neural network?
Super excited to share recent work with the brilliant @mozesjacobs.bsky.social: "Traveling Waves Integrate Spatial Information Through Time"
1/14
Super excited to share recent work with the brilliant @mozesjacobs.bsky.social: "Traveling Waves Integrate Spatial Information Through Time"
1/14
March 10, 2025 at 3:34 PM
In the physical world, almost all information is transmitted through traveling waves -- why should it be any different in your neural network?
Super excited to share recent work with the brilliant @mozesjacobs.bsky.social: "Traveling Waves Integrate Spatial Information Through Time"
1/14
Super excited to share recent work with the brilliant @mozesjacobs.bsky.social: "Traveling Waves Integrate Spatial Information Through Time"
1/14
Reposted by Janne Lappalainen
🚀 Applications are OPEN for the CAJAL NeuroAI course!
Learn how AI & deep learning help us model brain activity & behavior. Work with experts, get hands-on training & join a global network!
📅 Apply by March 7
🔗 loom.ly/xg_uRKE
#NeuroAI #DeepLearning #Neuroscience
Learn how AI & deep learning help us model brain activity & behavior. Work with experts, get hands-on training & join a global network!
📅 Apply by March 7
🔗 loom.ly/xg_uRKE
#NeuroAI #DeepLearning #Neuroscience
February 3, 2025 at 12:27 PM
🚀 Applications are OPEN for the CAJAL NeuroAI course!
Learn how AI & deep learning help us model brain activity & behavior. Work with experts, get hands-on training & join a global network!
📅 Apply by March 7
🔗 loom.ly/xg_uRKE
#NeuroAI #DeepLearning #Neuroscience
Learn how AI & deep learning help us model brain activity & behavior. Work with experts, get hands-on training & join a global network!
📅 Apply by March 7
🔗 loom.ly/xg_uRKE
#NeuroAI #DeepLearning #Neuroscience
Reposted by Janne Lappalainen
How can we use machine learning to find subtle patterns in our data and have them visualized?
Read the thread below to find out how!
Or head to @adjavon.bsky.social's blog post and let Simon the duck walk you through it (like a duck of course): tinyurl.com/yy7csdcd
www.biorxiv.org/content/10.1...
Read the thread below to find out how!
Or head to @adjavon.bsky.social's blog post and let Simon the duck walk you through it (like a duck of course): tinyurl.com/yy7csdcd
www.biorxiv.org/content/10.1...
January 15, 2025 at 8:50 PM
How can we use machine learning to find subtle patterns in our data and have them visualized?
Read the thread below to find out how!
Or head to @adjavon.bsky.social's blog post and let Simon the duck walk you through it (like a duck of course): tinyurl.com/yy7csdcd
www.biorxiv.org/content/10.1...
Read the thread below to find out how!
Or head to @adjavon.bsky.social's blog post and let Simon the duck walk you through it (like a duck of course): tinyurl.com/yy7csdcd
www.biorxiv.org/content/10.1...
Ever wanted to do deep learning with a neural net that is one-to-one mapped to 65.05% of the fruit fly brain? 😄
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
December 30, 2024 at 8:38 PM
Ever wanted to do deep learning with a neural net that is one-to-one mapped to 65.05% of the fruit fly brain? 😄
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Before this year ends, I will quickly advertise our code release of `flyvis.`
Docs: t.ly/YqWzR
Repo: t.ly/pMWpp
Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Reposted by Janne Lappalainen
Thinking about this a lot as a (pre-tenure) PI. There just isn't enough time to go deeply into an idea, which is obviously bad for (my) science.
Instead of listing my publications, as the year draws to an end, I want to shine the spotlight on the commonplace assumption that productivity must always increase. Good research is disruptive and thinking time is central to high quality scholarship and necessary for disruptive research.
December 26, 2024 at 2:42 AM
Thinking about this a lot as a (pre-tenure) PI. There just isn't enough time to go deeply into an idea, which is obviously bad for (my) science.
Why study the fruit fly brain? Tech giants spend billions on gigantic neural networks, but there’s a fruit fly with only 130_000 neurons that can do so much more and runs on less power than a quartz watch.
Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but recent work by @lappalainenjk.bsky.social et al. shows a strategy for getting closer to this goal. Read more on our blog: www.machinelearningforscience.de/en/improving...
How a tiny animal helps us improve brain simulations with AI
Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but our new paper shows a strategy for getting closer to this goal.
www.machinelearningforscience.de
December 21, 2024 at 2:06 PM
Why study the fruit fly brain? Tech giants spend billions on gigantic neural networks, but there’s a fruit fly with only 130_000 neurons that can do so much more and runs on less power than a quartz watch.