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Ladislas Nalborczyk

@lnalborczyk.bsky.social
1K followers 1.2K following 124 posts

Computational cognitive neuroscientist @cnrs.fr. Visiting scholar at @dukemedschool.bsky.social. Inner speech, mental imagery, cognitive/statistical modelling, M/EEG, open and slow science. More info & job opportunities: lnalborczyk.github.io.

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Reposted by Ladislas Nalborczyk
Ken Paller @paller.bsky.social · 6h
Did you know that your speed — in a simple task of quickly pressing a button every time you see a yellow square — is faster when you are exhaling or pausing then when you are inhaling? Dr. Erika Yamazaki figured this out, did all the work, and published on it this week www.cell.com/iscience/ful...
cell.com
Response speed is modulated by respiratory phase
Behavioral neuroscience; Cognitive neuroscience
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Simon Fisher @profsimonfisher.bsky.social · 23/09/2026
“Bats are extraordinary among mammals, having uniquely evolved powered flight & laryngeal echolocation, along with disease resistance, extended healthspan & ability to hibernate. With genome assemblies of 103 bat species we provide new insights into evolutionary history & trait diversification.”🦇🧬🙌🧪
nature.com
Reference genomes and fossils revise bat family phylogeny and biogeography - Nature
An updated phylogeny of bats is presented, based on new genome assemblies and many ancient fossils and including all known bat families.
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Kobe Desender @kobedesender.bsky.social · 19h
"A single evidence accumulation process informs perceptual choices and subsequent confidence reports"! Reviewed Preprint at @elife.bsky.social led by @johnpgrogan1.bsky.social , @lucvermeylen.bsky.social, @redmondoconnell.bsky.social, and others PDF: elifesciences.org/reviewed-pre... Thread ↓↓↓
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Decision, Action, and Neural Computation (DANC) lab @danclab.bsky.social · 20h
Our multilayer MEG paper is out today in Nature Communications: depth-resolved laminar inference in humans 🧠#neuroskyence www.nature.com/articles/s41...
nature.com
Multilayer MEG source modelling enables depth-resolved laminar inference in humans - Nature Communications
Researchers developed a multilayer MEG framework that estimates activity across cortical depth non-invasively. Simulations and three human datasets show when reliable laminar inference is possible, en...
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Earl K. Miller @earlkmiller.bsky.social · 29/09/2026
Comprehensive profiling of brain dynamics during anesthesia across phylogeny www.nature.com/articles/s41... #neuroscience
nature.com
Comprehensive profiling of brain dynamics during anesthesia across phylogeny - Nature Neuroscience
In this study, Luppi et al. systematically characterized and modeled more than 6,000 features of neural activity during anesthesia. They reveal a shared but reversible dynamical endpoint of anesthesia...
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Andrew Reid @reid-lab.org · 11/09/2026
www.reid-lab.org/blog/22 My (interactive) blog post focused on how #EEG #MEG signals are generated. Aimed at anyone interested in learning about these methods on a biophysical level. Let know what you think -- and share if you think it may interest your followers! #neuroscience #Neuroskyence
reid-lab.org
Learning about EEG (part 1) | Andrew's Blog
This is a teaching-oriented post about the fundamental concepts underlying electroencephalography (EEG), and to some extent magnetoencephalography (MEG). I explore how electromagnetic fields are gener...
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RLDM @rldmparis2027.bsky.social · 29/09/2026
📣 Save the date! RLDM 2027, the Multi-disciplinary Conference on Reinforcement Learning and Decision Making, is coming to Paris, July 6-9, 2027 🎉 Stay tuned for submission deadlines and more updates on our website rldm.org 👀
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Kobe Desender @kobedesender.bsky.social · 29/09/2026
"Trial-by-trial fluctuations in decision criterion shape confidence"! Now out in @nathumbehav.nature.com led by Robin Vloeberghs, Lara Navarette, @anne-urai.bsky.social and me. PDF: desenderlab.com/wp-content/u... Fluctuating Thread ↓↓↓
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Ben Fulcher @bendfulcher.bsky.social · 29/09/2026
Today I'm releasing the "1000×1000 collection": a unified place to learn about dynamical structure. 1000 simulated time series (1000 samples each) spanning 133 dynamical processes. Have a play? 🐛 #timeseries #dynamicalsystems #complexity #opendata dynamicsandneuralsystems.github.io/1000x1000/
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Henrik Singmann @singmann.bsky.social · 09/09/2026
A new version of rtdists is now on CRAN: cran.r-project.org/package=rtdi... Big thanks to @kiante.bsky.social who added a new distribution, the racing diffusion model, fixed a number of long-standing bugs, and increased the speed of the diffusion model. All news: cran.r-project.org/web/packages...
cran.r-project.org
rtdists: Response Time Distributions
Provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model (Ratcliff &amp; McKoon, 2008, &lt;<a href="https:/...
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Ole Jensen @olejensen.bsky.social · 27/09/2026
I would like to highlight two postdoctoral positions in the project Neuronal Mechanisms of Reading in Children Using OPM-MEG at the University of Oxford: my.corehr.com/pls/uoxrecruit… my.corehr.com/pls/uoxrecruit��� Deadline 30 Sep.
my.corehr.com
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Daphné Rimsky Robert @rimskyrobert.bsky.social · 26/09/2026
🍯 Our new study with @clairesergent.bsky.social and @mlisi.bsky.social is out in @commspsychol.nature.com🐝 We investigated flexibility in conscious access (www.nature.com/articles/s44...), and showed you can be made retrospectively aware of a word's meaning in isolation from its case or location.
nature.com
Consciously detecting and recognizing a past visual word after its sensory trace is gone - Communications Psychology
This series of studies shows that conscious detection and recognition of a word can be triggered retrospectively, even after its visual features are masked. This suggests that conscious access may be ...
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Mikkel Wallentin @mikkelwallentin.bsky.social · 26/09/2026
New PhD-opportunity at Aarhus University with a project investigating the cognitive correlates of having no inner speech. Supervised by Johanne Nedergaard and yours truly. Deadline 11 November. Starting date 1 February 2027. Get in touch if you want to know more. phd.arts.au.dk/applicants/o...
phd.arts.au.dk
Individual differences in inner speech: Measurement and modelling (5+3), 2026-14
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Imaging Neuroscience @imagingneurosci.bsky.social · 24/09/2026
New paper in Imaging Neuroscience by David Halpern and Todd Gureckis: Getting blood from a stone: Improving brain–behavior inferences without brain data doi.org/10.1162/IMAG...
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Jianghao Liu @jianghaoliu.bsky.social · 23/09/2026
#Miabridge workshop - the final program is out! You are interested in mental imagery and aphantasia, don't miss it. The registration is still open.
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Princeton Neuroscience Institute @princetonneuro.bsky.social · 23/09/2026
📢 We’re hiring! PNI is seeking a full-time Lecturer in Computational and Cognitive Neuroscience to teach undergraduate and graduate courses in computational modeling and human cognitive neuroscience. Priority consideration: Nov. 30 Apply: apply.interfolio.com/193741 #NeuroSkyence #NeuroJobs
exterior photo/rendering of the PNI and psychology building
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The vOICe vision BCI 🧠🇪🇺 @seeingwithsound.bsky.social · 24/09/2026
Medial temporal default mode network selectively encodes autobiographical visual imagery www.science.org/doi/10.1126/... mental imagery, MT-DMN
Identifying visual information structure in fMRI data scanned during autobiographical imagination.
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Micah G. Allen @micahgallen.com · 22/09/2026
So… we just found out that GPT sol can complete a complex online behavioral/cognitive study producing nearly indistinguishable behavior and subjective reports… right as we are about to launch. Is this doomsday for online cognitive testing?
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Reza Shadmehr @rezashadmehr.bsky.social · 22/09/2026
Faculty position opening in computational neuroscience at Duke University. academicjobsonline.org/ajo/jobs/32697
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Mitchell Ostrow @neurostrow.bsky.social · 21/09/2026
Very excited to announce our most recent paper! TL;DR we made our prior work on comparing dynamics (DSA) much faster and generalizable to diverse data domains and problem settings (1/)
biorxiv.org
A metric for comparing complex systems by their dynamics
Comparisons are fundamental to science: experiment against model, one organism against another, a system against itself across time. Because many systems, from brains to climate, are characterized by ...
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Dan Quintana @dsquintana.bsky.social · 19/09/2026
New preprint! 🎉 I analysed 1660 papers from 4 psychology journals and found materials sharing went from 9% of papers in 2015 to 82% in 2025, and these materials *do* get downloaded — a median of 135 times each. BUT shared code is often hard to run. doi.org/10.31234/osf... Let's walk through it 🧵
Two-panel figure. Panel a is a flow diagram tracking 1,611 empirical psychology articles from publication year (545 in 2015, 552 in 2020, 514 in 2025) to repository-link type: 785 link an OSF project, 85 link another platform, and 741 link no repository. Of those with an OSF link, download counts were retrieved for 670 and not retrieved for 115. Panel b is a line chart of the share of empirical papers linking OSF across 2015, 2020 and 2025. The overall rate, shown as a dashed black line, rises from 9% to 57% to 82%. All four journals rise steeply and end close together: Psychological Science 92%, JESP 89%, JML 83%, Cognition 76%, with Psychological Science highest throughout.Three-panel figure. Panel a: ridgeline plot of downloads per file by material type on a log scale, with the percentage never downloaded labelled for each — archive 16% of 545 files, documents 20% of 2,970, code 12% of 3,471, other 17% of 1,646, data 21% of 10,051, media 35% of 2,120, images 35% of 4,102. Most files cluster between 1 and 10 downloads, with long right tails past 100. Panel b: ridgeline plot of downloads per paper by journal, log scale, with dashed median lines; Psychological Science is highest, then JESP, JML and Cognition. Panel c: stacked bars showing, for documents, data and code separately, the share of papers by download band (0, 1–10, 11–100, more than 100) in 2015, 2020 and 2025. The share exceeding 100 downloads falls sharply over time in all three types, from roughly two-thirds in 2015 to a quarter or less in 2025, as the 1–10 band grows.Four-panel figure. Panel a: statistical languages detected among 333 papers with retrievable code — R 88%, SPSS 12%, Stata 4%, SAS 1%. Panel b: code red flags among those 333 papers — 34% hard-code an absolute path, 40% reference a missing file — above documentation among 672 OSF-linked papers — 21% have a README, 30% are documented by README, description or wiki. Panel c: among 562 Elsevier papers with no repository link, 44% (245) host at least one journal supplementary file but only 14% (77) host data, code or an archive. Panel d: composition of those 448 hosted files — documents 52%, data 21%, media 9%, other 7%, archive 6%, code 3%, images 1%. The code panels are green, the journal-supplement panels blue.Coefficient plot (download predictors)

Dot-and-whisker plot of three standardised predictors of OSF download volume, each with a 95% confidence interval. Repository size (number of files) has the largest effect at about 0.76, citations about 0.38, and altmetric attention about 0.12. All three intervals sit entirely above zero, so each predicts more downloads, with repository size roughly twice the effect of citations and six times that of attention. X-axis: standardised effect, −0.2 to 1.0.
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John Pearson @jmxpearson.bsky.social · 16/09/2026
**Second** job in computational/theoretical neuro at @dukemedschool.bsky.social! Really great opportunity, great colleagues.
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Nanthia Suthana @suthanalab.bsky.social · 16/09/2026
New tenure-track faculty position at Duke! The Neurobiology department is looking for a computational neuroscientist. Join a highly collaborative & interdisciplinary community. My time at Duke has been amazing so far & we would love the opportunity to collaborate with you! Applications due Dec 1.
academicjobsonline.org
Duke University, Neurobiology
Job #AJO32697, Tenure Track Assistant Professor - AI/ML Neurobiology, Neurobiology, Duke University, Durham, North Carolina, US
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Jeremiah Cohen @jeremiahycohen.bsky.social · 16/09/2026
Happy to share the version of record of our locus coeruleus paper here: www.nature.com/articles/s41... Prior thread on some of our discoveries in this study: bsky.app/profile/jere...
nature.com
Topographic structure and function of locus coeruleus noradrenaline neurons - Nature
Dorsal and ventral noradrenergic neurons in the locus coeruleus form topographic subpopulations whose projection patterns and activity encode choice switching, reward-prediction errors and disregard o...
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Steve Fleming @smfleming.bsky.social · 16/09/2026
📖 New review out today in @natrevneuro.nature.com: Towards an integrative neuroscience of metacognition 🧠🧪 Full-text link to the paper is here: rdcu.be/9YK3mF7dYhFa
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Earl K. Miller @earlkmiller.bsky.social · 16/09/2026
Alpha/beta waves in working memory. Alpha reflects the quality of the memory and beta waves track confidence. Distinct oscillatory neural rhythms support representational precision and confidence in working memory www.cell.com/current-biol... #neuroscience
cell.com
Distinct oscillatory neural rhythms support representational precision and confidence in working memory
Di et al. show that two distinct oscillatory neural rhythms encode different aspects of working memory uncertainty. Alpha-band activity carries probabilistic memory representations whose precision pre...
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CuttingEEG @cuttingeeg.bsky.social · 15/09/2026
🌱 #CuttingGardens 2026 in 6 Days! International M/EEG event cuttingeeg.org/cuttinggarde... 🌍 Can’t travel? No problem! Join the Global Program online: 1️⃣ Apply to #EEG101 before Sept. 18 → www.eeg101.eu/join/ 2️⃣ Accept your invite 3️⃣ Join online 🧠Let’s sync our international brain networks!
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Simon Kirby @simonkirby.bsky.social · 15/09/2026
We uncovered spontaneous evolution of new languages in populations of AI agents. This creates extraordinary scientific opportunities but also safety risks. New blog post with about how we created a platform for studying this safely. www.schmidtsciences.org/glossogen/
schmidtsciences.org
AI Agents Evolve Their Own Languages
Schmidt Sciences’ new AI Agents Evolving Communication and Coordination pilot program works toward advancing foundational research on multi-agent communication and coordination, and building an open-s...
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Camille Grasso @grassocamille.bsky.social · 01/04/2026
Happy to share our new preprint: Uncovering the representational geometry of durations Is time represented along a single mental timeline? We combine behaviour + EEG to show that duration is organised in a richer, multidimensional space. w/ @lnalborczyk.bsky.social & @virginievanw.bsky.social
biorxiv.org
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Stanislas Dehaene @standehaene.bsky.social · 14/09/2026
www.lemonde.fr/sciences/art...
lemonde.fr
« Les programmes actuels de maternelle intègrent déjà le principe d’une initiation renforcée à la lecture »
Si la préparation à la lecture avant le CP reste insuffisante, admet le neuroscientifique Stanislas Dehaene dans un entretien au « Monde », notre école souffre de problèmes plus importants, comme la q...
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COSYNE @cosynemeeting.bsky.social · 11/09/2026
📢Have work to share with the computational and systems neuroscience community? Abstract submissions for #COSYNE2027 are now open. Deadline: 18 October 2026, 11:59 p.m. AoE Submit your abstract: www.cosyne.org/abstracts-su... #Neuroscience
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SNL Annual Meeting @snlmtg.bsky.social · 11/09/2026
A prelude to #SNL2026? join us for an SNL pre-symposium webinar: Setting the Stage - Speech, Movement, and the Parietal Link to Reading 📅 September 22, 2026 ⏰ 7–8 AM PDT | 10–11 AM EDT | 4–5 PM CEST 🔗 2026.neurolang.org/virtual-acti...
2026.neurolang.org
Member-Initiated Virtual Activity
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Cogan Lab @coganlab.bsky.social · 18/08/2026
How does a speech plan become fluent movement? In Nature Human Behaviour, led by Kumar Duraivel: Intracranial recordings reveal how hierarchical speech plans become continuous motor sequences across planning, articulation, and monitoring networks. doi.org/10.1038/s415... 1/5
doi.org
Distinct neural processes link speech planning and execution - Nature Human Behaviour
Direct recordings from the human brain reveal a hierarchy in planning to speak, with neural activity organizing whole syllables before the individual sounds that compose them are sequenced.
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Saints-Pères Paris Institute for the Neurosciences @sppin-cnrs.bsky.social · 11/09/2026
@sppin-cnrs.bsky.social @cnrs.fr is organizing #NeuralNet2026 in Paris on Nov. 25–27 ! Join the 15th annual meeting of GDR NeuralNet @upcite.bsky.social , bringing together researchers working across systems neuroscience, neural data, computational modeling, NeuroAI & data science.
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Peter Kok @peterkok.bsky.social · 11/09/2026
I'm very excited about this recent study, led by @pieterbarkema.bsky.social. We find that stimulus representations in the deep layers of V1 can be affected by *later* information: postdiction. See Pieter's thread for more information - and of course the preprint! @jhaarsma.bsky.social #neuroskyence
biorxiv.org
The post-hoc montage of perception: deep layers of primary visual cortex encode postdictive percepts
One of the most puzzling aspects of perception is postdiction: later information can change how a previous stimulus is perceived [1,2]. This indicates that perception is not a livestream of the extern...
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Rhodri Cusack @rhodricusack.bsky.social · 10/09/2026
We're hiring! 2 postdocs + 3 PhD students to join InfantNeuroAI at Trinity College Dublin: awake infant fMRI & OPM-MEG, plus computational models of how infants learn. Aims: understand infant visual cognition, infant neuroimaging methods, more energy-efficient learning 🧵 www.cusacklab.org/vacancies
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Earl K. Miller @earlkmiller.bsky.social · 10/09/2026
Neural activity is often summarized as a small number of shared patterns (low-dimensional structure). sliceTCA offers a more complete and efficient way to uncover meaningful structure in large-scale brain recordings. www.nature.com/articles/s41... #neuroscience
nature.com
Dimensionality reduction beyond neural subspaces with slice tensor component analysis - Nature Neuroscience
Neural activity does not always lie in a low-dimensional subspace. The authors extend this classic view to show that task-relevant information is distributed across multiple covariability classes and ...
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Marco Barilari @marcobarilari.bsky.social · 10/09/2026
New preprint from the CPPlab - our first 7T MRI study How does sound reach the occipital cortex in early blind people? Using 7T VASO layer-fMRI, here the first functional sub-mm dataset in blind people to test if auditory motion engages hMT+/V5 layers via feedforward or feedback lnk.ua/kjYccwS9Y 🧵👇
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Arthur Prat @arthurpr4t.bsky.social · 09/09/2026
We derived six laws of psychophysics from a single efficient-coding equation. The laws include Weber's law; scaling laws in visual working memory (which had been noted before, but with unclear theoretical justification); Wei & Stocker's law of human perception; arthurprat.com/pdfs/Prat-Ca...
arthurprat.com
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Mediterranean Society for Consciousness Science @mesec-community.bsky.social · 04/09/2026
How can students and postdocs shape their field of research? We're excited to share our TiCS piece, showcasing MESEC as a case study for exactly this question! So grateful for our wonderful community of MESECeers 🤗 doi.org/10.1016/j.ti... *Free access* link: authors.elsevier.com/a/1njPQ4sIRv...
doi.org
Redirecting
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Daniel Lakens @lakens.bsky.social · 15/08/2026
New Blog post: Which Data Repository Should you Use? In light of OSF closing down, I compare Zenodo, Dataverse, ResearchBox, PsychArchive, and local repositories on six important dimensions. If you want to know which to pick: It depends! daniellakens.blogspot.com/2026/08/whic...
daniellakens.blogspot.com
Which Data Repository Should You Use?
The Center for Open Science has announced that from November 16, 2026, no new projects can be created on the Open Science Framework. After F...
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Ladislas Nalborczyk @lnalborczyk.bsky.social · 08/09/2026
📢 We're looking for a Master's student to join our team in sunny Aix-en-Provence 🇫🇷 for a *paid* 5-6 month research internship, anytime between now and June 2027, to help replicate an influential behavioural study on inner speech! Details: tinyurl.com/bdcthbp8 #psychjobs #neurojobs #innerspeech
tinyurl.com
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Alessandro Gifford @alessandrogifford.bsky.social · 08/09/2026
(1/2) The EEG Moments Dataset (EMD) is now public! EMD is a large-scale dataset of simultaneous EEG and eye-tracking recordings of 6 participants for 1,102 naturalistic 3-second videos (while maintaining central fixation), together with rich video metadata. arxiv.org/abs/2608.28768
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Alexey Koshevoy @alexeykoshevoy.bsky.social · 07/09/2026
Are you interested in lexical competition, agent-based modelling, strong inference and Ukrainian? Then this paper, just published in @pnasnexus.org, is for you. With @oliviermorin.bsky.social and @sobchuk.bsky.social, we asked a simple question: why do some words become more common than others?
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Nicola Molinaro @nicolaml.bsky.social · 04/09/2026
🔊 New preprint. Speech timing is never regular — syllables stretch, phonemes arrive early or late. That variability is usually averaged away as noise. We asked whether the brain treats it as information instead. www.biorxiv.org/content/10.6...
biorxiv.org
The cortex encodes speech timing as departure from expectation across multiple timescales
Every syllable and every phoneme in natural speech has a different duration. This variability is conventionally treated as jitter, noise the brain must overcome to recover an underlying regularity. He...
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Nicole Rust @nicolecrust.bsky.social · 03/09/2026
Heads-up: Doris Tsao is hiring 15 scientists/engineers to work on the neuroscience of consciousness at her new venture (Astera). astera.org/careers/#box...
astera.org
Careers
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Maxence Pajot @maxencepajot.bsky.social · 02/09/2026
New AI models now show incredible math skill, solving problems that had stumped mathematicians for years. But what about basic geometric abilities? In our new paper in PLOS Computational Biology, we investigate this in vision models: doi.org/10.1371/jour... 1/8
doi.org
Can neural networks model the human perception of geometric shapes?
Author summary Recent neural networks have achieved remarkable success across a wide range of visual tasks, often rivaling or surpassing human performance. Yet, it remains unclear whether these system...
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Rico Stecher @ricostecher.bsky.social · 03/09/2026
The final preprint of my PhD is out! We present a neuro-computational approach that can approximate mental images and allows us to assess their qualities without introspection. We evaluated this approach on a large-scale EEG data set (43,200 trials). (1/n) www.biorxiv.org/content/10.6...
biorxiv.org
A neuro-computational approximation of the qualities of mental images
Mental images are challenging to study, given that our conscious experience is notoriously hard to access. The currently prevalent introspective methods are inherently subjective and can thus only pro...
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Michel Nivard @michelnivard.bsky.social · 02/09/2026
🚨& 🧵 Our new Nature paper is out! Across 46 cohorts and up to 1.14M people per Big Five trait, we do GWAS and ask how robust, generalizable and consequential the genetic signals underlying personality really are. www.nature.com/articles/s41...
nature.com
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Tom McCoy @rtommccoy.bsky.social · 01/09/2026
🤖🧠NEW PAPER🧠🤖 (The result of an 8-year project!) LLMs seem very different from symbolic systems. Yet LLMs excel in symbolic domains (e.g., language/code/math). How do they do it? Our finding: LLM representations have implicit symbolic structure! Link in thread ⬇️ 1/n
Overview of the paper. 
Title: The Emergent Symbolic Structure of Artificial Neural Networks
Authors: Tom McCoy, Paul Soulos, Tal Linzen, Paul Smolensky
Left: Neural networks encode information in vectors (there is then an image of a vector), yet they excel at tasks long thought to require symbolic structure (there is then an image of a symbolic representation, specifically a syntax tree). How do LLMs do it?
Right: We find that LLM representations can be closely approximated with symbolic structures. This approximation lets us edit the structure of an LLM’s output by editing the structure of its internal representations, as shown. There is then an image of two edits to LLMs. In the first one, the original input is 3 + 6 * 8, with an answer of 51. But if we swap the positions of the 3 and the 6, the output becomes 30. In the second one, the original input is a Python command repeating the list [Z, U] three times, producing [Z, U, Z, U, Z, U]. But if we edit the input in a way that adds a Q at the end of the input, the output becomes [Z, U, Q, Z, U, Q, Z, U, Q].
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