Our postdoc Dr. Tianjiao Zhang has released "Its Complicated", a great software library that provides infrastructure to implement naturalistic, complex, interactive experiments in game engines. The toolbox supports peripherals and coding game logic for later analysis. gallantlab.org/Its-Complica...

(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

Speech production is fast, complicated, cool (when the right thing is said...) Covert speech is a nice trick to study this. If you like speech planning, forward models, efference copies, brains this work is (we hope) helpful to clarify the brain mechs. #neuroskyence www.pnas.org/doi/10.1073/...

Temporally structured motor and auditory representations in covert syllable production | PNAS

Inner speaking—the deliberate generation of speech through covert production mechanisms—is a common human experience. Current accounts propose that...

pnas.org

(1/2) We’re excited to announce the Algonauts Project Challenge 2027 with CNeuroMod: How The Human Brain Makes Sense of Video Games 🎮 🧠 Launching end of 2026. Top 3 teams will present at CCN 2027 in Edinburgh. algonautsproject.com/2027/ #Algonauts2027 #NeuroAI #CompNeuro #fMRI

Are brains and artificial neural networks converging onto universal representations? There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model). We have thoughts™ 1/n

The Umwelt Representation Hypothesis: rethinking Universality

Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on univer...

cell.com

The journal version is out! www.cell.com/trends-open/... AI is turning machine consciousness into a societal issue. Biological Naturalism (BN), the idea that only biological systems can be conscious, is gaining traction. We argue: either BN is untestable, or it is compatible with functionalism.

What biology can and cannot tell us about conscious AI

Progress in artificial intelligence is turning machine consciousness from a philosophical curiosity into a societal issue, and has led to criticism of the widespread computational functionalist framew...

cell.com

Adrien Doerig@adriendoerig.bsky.social · 4mo ago

1/n New preprint: What biology can, and cannot, tell us about conscious AI arxiv.org/abs/2606.02121 With @ulysse-klatzmann.bsky.social

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

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.

doi.org

New perspective piece out in @cp-neuron.bsky.social with Zaid Zada, @adelegoldberg.bsky.social, and Uri Hasson! We try to articulate some of our excitement about LLMs and discuss what kinds of insights they might provide into the neural computations supporting natural language in the human brain.

Excited to share our new paper: "Probing the content of semantic representations in body-selective regions" We propose a framework based on object co-occurrence to interpret semantic representations of natural scenes predicted by LLM embeddings. doi.org/10.1162/IMAG...

Probing the content of semantic representations in body-selective regions

Abstract. Recent advances in neural networks trained on natural language have revealed that category-selective regions encode complex semantics and contextual information of natural scenes in addition...

doi.org

Exclusive: A cutting-edge gene-editing trial in China went disastrously wrong. A family wants accountability. https://scim.ag/3RuHuDB

Exclusive: Death of girl in Chinese gene-editing trial was never made public

Parents want accountability after study went disastrously wrong, Science and Retraction Watch investigation reveals

scim.ag

🌟📣 Check out the special issue "The Relevance of a Philosophical Toolkit to Advance Neuroscience" in the EJN, co-edited by KLI group leader Isabella Sarto-Jackson. It features 31 interdisciplinary papers on understanding the functions of the brain and mind. onlinelibrary.wiley.com/doi/toc/10.1...

Our new review paper lead by CNAP PhD Student Jim Zhang and @tobiasegner.bsky.social is now published in Neuroscience & Biobehavioral Reviews: “Insights into the neural mechanisms supporting cognitive stability and flexibility from human intracranial EEG.” doi.org/10.1016/j.ne... 1/5

Looking for a Python toolbox to analyze your mobile eye-tracking data collected with @pupil-labs.bsky.social Neon? Meet PyNeon, our open-source toolbox designed to streamline the analysis of such novel data! Check out the paper in @psychonomicsociety.bsky.social's BRM: doi.org/10.3758/s134... ...

PyNeon: A Python package for the analysis of Neon multimodal mobile eye-tracking data - Behavior Research Methods

Mobile eye-tracking has revolutionized the study of human behavior and cognition by enabling researchers to record eye movements in the real world. However, the dynamic and multimodal nature of mobile eye-tracking data also introduces significant analytical challenges, including the alignment, integration, and interpretation of complex data. To fill these gaps, we present PyNeon, a versatile, community-oriented Python package designed to streamline the analysis of mobile eye-tracking, motion, and video data from the Neon eye-tracking system (Pupil Labs GmbH). We describe how PyNeon provides accessible APIs for reading, preprocessing, epoching, and exporting Neon data. Furthermore, it supports advanced video processing such as mapping between eye movement data and real-world coordinates and dynamic scanpath estimation. PyNeon presents an open-source and extendable framework for analyzing mobile eye-tracking data and forms the foundation for higher-level applications.

doi.org

🧠 What's the best way to spend compute & neural data to build brain-aligned models? Our new ICML 2026 paper charts the scaling laws across 8 neural datasets & 600+ vision models. 👇 🌐 multimodal-brain-scaling.epfl.ch w/ @davidtyt.bsky.social & @mschrimpf.bsky.social

We’re happy to announce 2 releases today: - 🧠Brain2qwerty v1 is published at @Nature Neuroscience - 🚀 Brain2Qwerty v2 is now publicly released Explore how we decode sentences from non-invasive brain recordings: facebookresearch.github.io/brain2qwerty/ Code, papers, data below:

We are hosting a special issue on "Is There More to Consciousness Than Computation?" in @nconsc.bsky.social. Full information here: academic.oup.com/nc/pages/cal... With @krysdolega.bsky.social and Yair Pinto.

Call for Papers | Neuroscience of Consciousness

Neuroscience of Consciousness (NCON) is a peer-reviewed, fully open access journal that provides a unique forum for the interdisciplinary fields of consciousnes

academic.oup.com

1/n New preprint: What biology can, and cannot, tell us about conscious AI arxiv.org/abs/2606.02121 With @ulysse-klatzmann.bsky.social

What biology can, and cannot, tell us about conscious AI

Progress in AI is turning machine consciousness from a philosophical curiosity into a societal issue, and has led to criticism of the widespread computational functionalism framework. Biological Natur...

arxiv.org

A short highlight of the beautiful recent work by @varunswadia.bsky.social, Doris Tsao et al., providing single-neuron evidence of the overlap between imagery and perception! www.nature.com/articles/s41...

New preprint as my first post! "Monosynaptic connections link functionally similar regions in human cortex." We use electrical stimulation + fMRI in epilepsy patients to map whole-brain monosynaptic connectivity at 42 cortical sites. doi.org/10.64898/202... 1/n

We wrote a book! www.cambridge.org/core/books/s... Consciousness science is a fascinating but bewildering field: many competing theories, little consensus, and big open questions. If you are looking for an accessible guide through this complex landscape, this book is for you.

Scientific Theories of Consciousness

Cambridge Core - Neurosciences - Scientific Theories of Consciousness

cambridge.org

New paper 🌟out now in Nat. Neurosci.: www.nature.com/articles/s41.... With advisors @davidpoeppel.bsky.social and @Nai! We show that, while LLMs are optimized to predict the next word, the human brain modulates prediction efficiency by strategically grouping words into constituents. 1/n More 👇

We're happy to release NeuralSet: a simple, fast, scalable package for Neuro-AI Supports: 🧠 fMRI, EEG, MEG, iEEG, spikes… preprocessing 💬 text 🔊 audio ▶️ video 🏞️ image… embeddings 📦 pip install neuralset 🔍 facebookresearch.github.io/neuroai/neur... 📄 kingjr.github.io/files/neural... 🧵 Details👇

New paper that merits a read (Im totally unbiased...not). Simple, straightforward, impactful message. Prediction a la LLM is nice. Constituent-constrained prediction is nicer. @jiajiezou.bsky.social and Nai Ding show brain, behavioral, MEG, ECoG data. www.nature.com/articles/s41... #neuroskyence

Constituent-constrained word prediction during language comprehension - Nature Neuroscience

Zou et al. reveal a key difference between human brains and large language models (LLMs). While LLMs are optimized to predict the next word, the human brain modulates prediction efficiency by strategi...

nature.com

John T. Hale and Team Language Cycles are searching for participants from 25 languages for The Little Prince MEG study. Get in touch via languagecycles.com/home/tlpp/. Eight years and seven rejected proposals in the making, now generously funded by the Johns Hopkins University and the @dfg.de

check out the latest paper from the lab!! we build and validate a novel method for recording speech comprehension success (and failure) in real time!

Irmak Ergin@irmakergin.bsky.social · 6mo ago

Excited to share our new publication, “Measuring Naturalistic Speech Comprehension in Real Time”! ➡️ rdcu.be/fa3hk #psynomBRM w/ @kriesjill.bsky.social, Shiven Gupta, Maria Papworth Burrel, & @lauragwilliams.bsky.social 🧵1/11

#JNeurosci: Using fMRI, Zhang et al. found that while both sounds & videos reactivate sensory brain regions during recall, auditory memories rely more on internally constructed, gist-like representations that differ from the original perceptual patterns https://doi.org/10.1523/JNEUROSCI.1576-25.2026

📢 PhD position in Developmental Language Modelling (PLZ RT) What can human language acquisition teach us about training language models? Join us as a PhD! mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-developmental-language @carorowland.bsky.social @mpi-nl.bsky.social

10 PhD positions at JLU Giessen in the new Research Training Group "PIMON"! We will explore how humans perceive and interact with materials and objects in natural environments. More information on the project, the PIs, and how to apply here: www.uni-giessen.de/de/ueber-uns... Please share!

We've posted a new fMRI study of semantic relations (has-part, is-a, made-of, etc.), a key aspect of language. We find that relations are represented in the same brain regions as are other semantic concepts, though voxels tend to be selective for only one relation or another. doi.org/10.64898/202...

📢We're thrilled to announce the first-ever #IRCA Conference on #Aphantasia! Call for abstracts is open, deadline: 17 April 2026 sites.google.com/view/irca-co... This 3-day interdisciplinary conference aims to consolidate current knowledge and draw a future plan for aphantasia research.