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
Devika Narain
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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!
www.nature.com
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...
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
@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/...
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 😊
Matt Perich
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...
Apparent neural encoding of future words may arise from the statistical structure of language itself, rather than from predictive computations in 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, writes @juangallego.bsky.social. But will we be able to understand them? #neuroskyence
www.thetransmitter.org/neuroai/why-...
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?
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...
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...
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
Laura Grima
Juan Gallego
Disagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data.
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-...
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...
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?
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?
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)
