Devika Narain
@neuronarain.bsky.social
Neuroscientist in search of lost time. Studying temporal control of movement. PI Donders/Erasmus MC, Netherlands. Side hustle: Building theories for neural manifolds
www.narainlab.org
www.narainlab.org
Pinned
Devika Narain
@neuronarain.bsky.social
· Apr 14
Neural circuits encode prior knowledge of temporal statistics - Nature Neuroscience
This study shows that cerebellar circuits learn and encode prior probabilities of event timing. Cell-type-specific neural activity reflects environmental statistics and guides predictive motor behavio...
www.nature.com
Our work on how neural circuits in the cerebellum encode prior probabilities led by Julius Koppen is out now in Nature Neuroscience www.nature.com/articles/s41...
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Reposted by Devika Narain
With talks by @kaytrue.bsky.social, Carl-Philipp Heisenberg, @neuronarain.bsky.social, Matz Liebel, Giorgio Scita, Sebastian Deindl, Louise Jawerth, Ewa Paluch
July 29, 2026 at 8:51 AM
With talks by @kaytrue.bsky.social, Carl-Philipp Heisenberg, @neuronarain.bsky.social, Matz Liebel, Giorgio Scita, Sebastian Deindl, Louise Jawerth, Ewa Paluch
Reposted by Devika Narain
A hackathon reveals that disagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data, write @mattiachini.bsky.social and Gaelle Chapuis. #neuroskyence
www.thetransmitter.org/reproducibil...
www.thetransmitter.org/reproducibil...
18 teams analyzed a neuro dataset and got different answers
Disagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data.
www.thetransmitter.org
June 1, 2026 at 2:38 PM
A hackathon reveals that disagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data, write @mattiachini.bsky.social and Gaelle Chapuis. #neuroskyence
www.thetransmitter.org/reproducibil...
www.thetransmitter.org/reproducibil...
Reposted by Devika Narain
New paper with @paulm-k.bsky.social and Mark Stokes on how we switch internal attention between working memory contents. Beta-band oscillations tracked the magnitude and success of these switches.
www.jneurosci.org/content/46/1...
#neuroskyence
www.jneurosci.org/content/46/1...
#neuroskyence
Human Beta Oscillations Reflect Magnitude and Fidelity of Priority Shifts in Working Memory
Flexible prioritization in working memory (WM) is supported by neural oscillations in frontal and sensory brain areas, but the roles of different oscillations remain poorly understood. Recordings in h...
www.jneurosci.org
May 25, 2026 at 3:37 PM
New paper with @paulm-k.bsky.social and Mark Stokes on how we switch internal attention between working memory contents. Beta-band oscillations tracked the magnitude and success of these switches.
www.jneurosci.org/content/46/1...
#neuroskyence
www.jneurosci.org/content/46/1...
#neuroskyence
Reposted by Devika Narain
@fluketc.bsky.social and @dudman.bsky.social have hit it out the park again. In my (perhaps biased) opinion this - along with their previous papers - is field-defining work. www.science.org/doi/10.1126/...
Reward magnitude determines reinforcement learning efficiency
Standard animal learning studies minimize individual reward magnitudes to maximize the repetitions of reinforced behaviors. We investigated how reward magnitude influences initial learning across five...
www.science.org
May 23, 2026 at 3:58 PM
@fluketc.bsky.social and @dudman.bsky.social have hit it out the park again. In my (perhaps biased) opinion this - along with their previous papers - is field-defining work. www.science.org/doi/10.1126/...
Reposted by Devika Narain
And a nice summary by Richard Antonello can be found here: elifesciences.org/articles/111...
April 28, 2026 at 8:11 AM
And a nice summary by Richard Antonello can be found here: elifesciences.org/articles/111...
Reposted by Devika Narain
After rereading the cool hidden brain paper (www.frontiersin.org/journals/sys...) I decided to make a new version. Code and everything available here:
github.com/koerding/neu...
Most popular: hippocampus. Why are diagonal band, medial geniculate nucleus, and interposed nucleus so unpopular?
github.com/koerding/neu...
Most popular: hippocampus. Why are diagonal band, medial geniculate nucleus, and interposed nucleus so unpopular?
April 28, 2026 at 5:52 PM
After rereading the cool hidden brain paper (www.frontiersin.org/journals/sys...) I decided to make a new version. Code and everything available here:
github.com/koerding/neu...
Most popular: hippocampus. Why are diagonal band, medial geniculate nucleus, and interposed nucleus so unpopular?
github.com/koerding/neu...
Most popular: hippocampus. Why are diagonal band, medial geniculate nucleus, and interposed nucleus so unpopular?
Reposted by Devika Narain
What are the real promises and looming perils of neural foundation models? 🧠
I put my thoughts on (virtual) paper for @thetransmitter.bsky.social following a very energised workshop at @cosynemeeting.bsky.social 2025.
It's also my first piece for them 😊
I put my thoughts on (virtual) paper for @thetransmitter.bsky.social following a very energised workshop at @cosynemeeting.bsky.social 2025.
It's also my first piece for them 😊
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity, writes @juangallego.bsky.social. But will we be able to understand them? #neuroskyence
www.thetransmitter.org/neuroai/why-...
www.thetransmitter.org/neuroai/why-...
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
www.thetransmitter.org
April 14, 2026 at 1:33 PM
What are the real promises and looming perils of neural foundation models? 🧠
I put my thoughts on (virtual) paper for @thetransmitter.bsky.social following a very energised workshop at @cosynemeeting.bsky.social 2025.
It's also my first piece for them 😊
I put my thoughts on (virtual) paper for @thetransmitter.bsky.social following a very energised workshop at @cosynemeeting.bsky.social 2025.
It's also my first piece for them 😊
Our work on how neural circuits in the cerebellum encode prior probabilities led by Julius Koppen is out now in Nature Neuroscience www.nature.com/articles/s41...
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Neural circuits encode prior knowledge of temporal statistics - Nature Neuroscience
This study shows that cerebellar circuits learn and encode prior probabilities of event timing. Cell-type-specific neural activity reflects environmental statistics and guides predictive motor behavio...
www.nature.com
April 14, 2026 at 1:17 PM
Our work on how neural circuits in the cerebellum encode prior probabilities led by Julius Koppen is out now in Nature Neuroscience www.nature.com/articles/s41...
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Big thanks to Julius Koppen & the whole team! And dedicated to all of us who found inspiration in Bayesian theories of the brain!
Reposted by Devika Narain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity, writes @juangallego.bsky.social. But will we be able to understand them? #neuroskyence
www.thetransmitter.org/neuroai/why-...
www.thetransmitter.org/neuroai/why-...
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
www.thetransmitter.org
April 13, 2026 at 1:26 PM
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity, writes @juangallego.bsky.social. But will we be able to understand them? #neuroskyence
www.thetransmitter.org/neuroai/why-...
www.thetransmitter.org/neuroai/why-...
Reposted by Devika Narain
New paper hot off the (pre-)press! We dig into the evolutionary origins of neural computations for behavioral control across mice, monkeys, and humans: www.biorxiv.org/content/10.6....
As our lab's first foray into comparative analysis of neural dynamics, I’m super excited about this work! 1/18
As our lab's first foray into comparative analysis of neural dynamics, I’m super excited about this work! 1/18
March 10, 2026 at 5:43 PM
New paper hot off the (pre-)press! We dig into the evolutionary origins of neural computations for behavioral control across mice, monkeys, and humans: www.biorxiv.org/content/10.6....
As our lab's first foray into comparative analysis of neural dynamics, I’m super excited about this work! 1/18
As our lab's first foray into comparative analysis of neural dynamics, I’m super excited about this work! 1/18
Reposted by Devika Narain
Excited and thrilled and humbled that our work is now out at Nature Human Behaviour linking Memorability with Time Perception! I hope you all find it of interest 🙂
Memorability shapes perceived time (and vice versa)
#academicsky #neuroskyence #psychscisky #science
Memorability shapes perceived time (and vice versa)
#academicsky #neuroskyence #psychscisky #science
Memorability shapes perceived time (and vice versa) - Nature Human Behaviour
In this Article, Ma et al. show, across a series of experiments, that time and memorability (the probability of recalling a visual stimulus) mutually influence one another, suggesting that time is a f...
www.nature.com
April 22, 2024 at 3:17 PM
Excited and thrilled and humbled that our work is now out at Nature Human Behaviour linking Memorability with Time Perception! I hope you all find it of interest 🙂
Memorability shapes perceived time (and vice versa)
#academicsky #neuroskyence #psychscisky #science
Memorability shapes perceived time (and vice versa)
#academicsky #neuroskyence #psychscisky #science
Reposted by Devika Narain
