Devika Narain

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

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Devika Narain
@neuronarain.bsky.social

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!

nature.comNeural circuits encode prior knowledge of temporal statistics - Nature NeuroscienceThis 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...

Devika Narain reposted

The Transmitter
@thetransmitter.bsky.social

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...

thetransmitter.org18 teams analyzed a neuro dataset and got different answersDisagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data.

Devika Narain reposted

Nick Myers
@nick-myers.bsky.social

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

jneurosci.orgHuman Beta Oscillations Reflect Magnitude and Fidelity of Priority Shifts in Working MemoryFlexible 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...

Devika Narain reposted

Laura Grima
@lauragrima.bsky.social

@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/...

science.orgReward magnitude determines reinforcement learning efficiencyStandard animal learning studies minimize individual reward magnitudes to maximize the repetitions of reinforced behaviors. We investigated how reward magnitude influences initial learning across five...

Devika Narain reposted

Floris de Lange
@predictivebrain.bsky.social

And a nice summary by Richard Antonello can be found here: elifesciences.org/articles/111...

elifesciences.orgLanguage Models: Does the brain really know what word is coming next?Apparent neural encoding of future words may arise from the statistical structure of language itself, rather than from predictive computations in the brain.
ines-schoenmann.bsky.social@ines-schoenmann.bsky.social

New peer-reviewed paper w/ @mheilbron.bsky.social, @predictivebrain.bsky.social & Jakub Szewczyk! Pre-onset brain encoding has been taken as evidence that brains–like LLMs–predict upcoming words. We show that the same signatures arise in systems that cannot predict. (elifesciences.org) (1/8)

Devika Narain reposted

Juan Gallego
@juangallego.bsky.social

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 😊

The Transmitter @thetransmitter.bsky.social

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-...

thetransmitter.orgWhy neural foundation models work, and what they might—and might not—teach us about the brainThese 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?

Devika Narain reposted

The Transmitter
@thetransmitter.bsky.social

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-...

thetransmitter.orgWhy neural foundation models work, and what they might—and might not—teach us about the brainThese 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?

Devika Narain reposted

Matt Perich
@mattperich.bsky.social

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

Devika Narain reposted

Martin Wiener
@martinwiener.bsky.social

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

nature.comMemorability shapes perceived time (and vice versa) - Nature Human BehaviourIn 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...

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