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Simon Faghel-Soubeyrand

@simonfsoubeyrand.bsky.social
158 followers 249 following 24 posts

Oxford Postodoctoral Researcher, Staresina Lab || Banting Postdoctoral Fellow || vision, memory, sleep, machine learning

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Reposted by Simon Faghel-Soubeyrand
Sander van Bree @sandervanbree.bsky.social · 12/08/2026
Excited to share our preprint! w/ @martinhebart.bsky.social To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them? biorxiv.org/content/10.6... Quick thread 🧵
biorxiv.org
Shared and Distinct High-Dimensional Object Spaces in Human and Macaque Inferotemporal Cortex
Human and macaque studies of inferotemporal cortex (IT) have shaped our understanding of object vision, yet the extent of their representational alignment and the precise nature of this correspondence...
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Thomas Schreiner @tschreiner.bsky.social · 05/08/2026
Breathing sets the timing for memory processing during sleep! In our new preprint, precisely shifting memory cues within the respiratory cycle changed oscillatory coordination, memory reactivation and next-morning recall. Fabulous work by @estebanbt.bsky.social, with @tobiasstaudigl.bsky.social!👇
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Blake Richards @tyrellturing.bsky.social · 03/06/2026
New perspective piece with @mandanas.bsky.social: We argue, based on LLMs and old connectionist theories, that schemas shouldn't be viewed as distinct from semantic or episodic memories. They're just one end of a detailed-to-abstract memory spectrum: www.cell.com/neuron/fullt... #NeuroAI 🧠📈 🧪
cell.com
The schema spectrum: Emergent structures and levels of abstraction in AI and the brain
Motivated by generative AI, Samiei et al. argue against classical models that treat schemas as distinct memory structures. Instead, they propose that schemas are merely a conceptual tool describing ho...
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Pin-Chun Chen @pinchunc.bsky.social · 18/05/2026
🔔 Preprint: “Hippocampal ripples evoke a stereotyped cortical response followed by spindle-mediated network synchronization.” Combining iEEG+scalp EEG during sleep, we show that hippocampal ripples leave a decodable cortical fingerprint and are followed by brain-wide spindle synchronization!
doi.org
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Aidan Horner @aidanhorner.bsky.social · 11/05/2026
Very excited to have this officially published: A neural state space for episodic memories A brief thread... #neuroskyence #psychscisky #cognition 🧪 @cp-trendscognsci.bsky.social
sciencedirect.com
A neural state space for episodic memories
Episodic memories are highly dynamic and change in nonlinear ways over time. This dynamism is not captured by existing systems consolidation theories …
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Nichole Bouffard @nicholebouffard.bsky.social · 07/05/2026
🚨 New Preprint 🚨 I’m excited to share the first paper from my postdoc. We found age differences in the timescales of neural activity in the hippocampus during movie viewing 👀 These timescales were related to memory specificity in an interesting way (spoiler: the hippocampus may not be special!?)
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Jack Gallant @gallantlab.org · 16/04/2026
We've posted a new group-based lexical-semantic brain viewer! You can now inspect cortical conceptual maps at the group level (24 participants), vertex-by-vertex. Check it out! gallantlab.org/viewer-stori...
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PLOS Biology @plosbiology.org · 13/04/2026
How do experiences reshape our internal representations of the world? @bstaresina.bsky.social &co show that learning sequential experiences reshapes how the #brain represents what we see; a post-learning nap strengthens these predictive changes @plosbiology.org 🧪 plos.io/4dJGwMC
Emergence of Successor Representations and Experimental Design. Top: Example of how sequence learning and sleep might change neural representations. Upon encountering a Welsh Corgi, the brain primarily represents the current stimulus entity. If the Corgi is part of a recurring temporal sequence (Corgi → Girl → House), subsequent stimuli (Girl and House) might be integrated into the Corgi representation. Post-learning sleep might provide an opportunity for the brain to replay learned experiences and thereby further strengthen successor representations. Upon post-sleep exposure to a Corgi image (right), brain activation patterns might reflect both the current stimulus (Corgi) as well as learned successors (Girl, House). Faded images indicate weaker representations. Middle: Timeline of the experiment. Participants first completed a perceptual task, followed by a sequence learning task (Memory Arena). Memory for the learned sequence was then assessed both before and after a period of sleep. Finally, participants completed the perceptual task again. Bottom left: Memory Arena sequence design. Participants (N = 26) were tasked with learning the spatiotemporal structure of 50 images. These images belonged to five distinct categories (letter strings, scenes, objects, faces, and body parts) and were organized into 10 subsequences of five images each, following one of two fixed category orders: (i) letter string, scene, object, face, or (ii) object, scene, letter string, face, with body part images randomly inserted to obscure the primary category sequences. The two subsequence types were counterbalanced across participants. Bottom right: Memory Arena location design. The Arena was spatially organized into five principal ‘slices’, with each slice corresponding to one of the five main image categories.
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Marcel S. Kehl @mskehl.bsky.social · 31/03/2026
🔔PREPRINT: Sleep ripples drive single-neuron reactivation for human memory consolidation 1/9: How does sleep support human memory consolidation? To test this, we recorded hundreds of neurons in the human medial temporal lobe (MTL) across learning, wakefulness, and sleep. doi.org/10.64898/202...
doi.org
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Nature Reviews Neuroscience @natrevneuro.nature.com · 20/03/2026
Clarifying the conceptual dimensions of representation in neuroscience — a Perspective by Stephan Pohl, Edgar Y. Walker, David L. Barack, Jennifer Lee, Rachel N. Denison, Ned Block, Florent Meyniel & Wei Ji Ma www.nature.com/articles/s41...
nature.com
Clarifying the conceptual dimensions of representation in neuroscience - Nature Reviews Neuroscience
Appeals to representation are widespread, despite neuroscientists’ uncertainty about what kind of findings count as evidence for such claims. In this Perspective, Pohl and colleagues develop a unified...
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Nature Human Behaviour @nathumbehav.nature.com · 02/03/2026
Episodic memory encoding fluctuates at a theta rhythm of 3–10 Hz
dlvr.it
Episodic memory encoding fluctuates at a theta rhythm of 3–10 Hz
Nature Human Behaviour, Published online: 02 March 2026; doi:10.1038/s41562-026-02416-5Biba et al. show that episodic memory encoding fluctuates at a theta rhythm of 3–10 Hz.
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Alessandro Gifford @alessandrogifford.bsky.social · 12/02/2026
NSD-synthetic, the out-of-distribution companion dataset of NSD consisting of 7T fMRI responses to 284 artificial images, is now published. #NeuroAI #CompNeuro #neuroscience #AI doi.org/10.1038/s414...
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Hannah Tarder-Stoll @hannahtarder-stoll.bsky.social · 12/02/2026
How do memories guide behaviour? Multiple memory representations, from detailed to gist-like, let us flexibly reconstruct or reproduce past experiences to behave adaptively across species. Now out in Physiological Reviews with Morris Moscovitch, Melanie Sekeres & @brianlevine.bsky.social!
journals.physiology.org
Adaptive episodic memory: how multiple memory representations drive behavior in humans and nonhumans | Physiological Reviews | American Physiological Society
Episodic memory is a declarative long-term memory of a specific past experience. As such, it is multifaceted, encompassing both the objective and subjective components of that experience. These components can be flexibly represented at different levels of granularity, from precise, context-specific details to generalized, gistlike representations. In this review, we suggest that 1) multiple representations of an episodic memory at different levels of granularity are simultaneously encoded into a memory trace and 2) the relative weighting of these representations determines the extent to which a memory is reconstructed or reproduced at retrieval. We propose that this representational flexibility drives adaptive behavior by prioritizing reconstruction or reproduction depending on the age of the memory, its relationship to prior knowledge, current attentional goals or task demands, and individual differences. Drawing on research in humans and nonhuman animals, we show a close correspondence between psychological and neural representations of a memory across encoding, consolidation, and retrieval. Specifically, we discuss how hippocampal activity in humans and engram formation and activation in rodents support the reproduction of detailed memory representations, whereas schema formation across species, mediated by the medial prefrontal cortex, facilitates reconstruction and generalization to guide behavior. Finally, we consider how species- and individual-level differences shape episodic memory representations. By integrating findings across species, we illustrate how the correspondence between neural and psychological representations enables multiple memory representations to balance stability and flexibility, ultimately driving adaptive behavior.
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Cliona O'Doherty @clionaod.bsky.social · 02/02/2026
1/7 Can infants recognise the world around them? 👶🧠 As part of the FOUNDCOG project, we scanned 134 awake infants using fMRI. Published today in Nature Neuroscience, our research reveals 2-month-old infants already possess complex visual representations in VVC that align with DNNs.
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Bernhard Staresina @bstaresina.bsky.social · 19/01/2026
Last week to apply! Cognitive Neuroscience Research Laboratory Manager at @oxexppsy.bsky.social (with links to @oxcin.bsky.social and @ox.ac.uk) www.jobs.ac.uk/job/DPZ833/c...
jobs.ac.uk
Cognitive Neuroscience Research Laboratory Manager at University of Oxford
Check out jobs.ac.uk for opportunities in professional services, including Cognitive Neuroscience Research Laboratory Manager. Apply today and learn more about the role.
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Thomas Schreiner @tschreiner.bsky.social · 19/01/2026
For those into sleep, memory, single units, and neural dynamics this one is for you! New preprint from the fantastic @fabian31415.bsky.social in collaboration with @humansingleneuron.bsky.social exploring how precisely timed sleep rhythms shape memory at the level of single neurons in humans.
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Fabian Schwimmbeck @fabian31415.bsky.social · 13/01/2026
How does the brain replay memories during sleep? Excited to share our new preprint, the outcome of an extensive effort led by Johannes Niediek, showing that reactivation of human concept neurons reflects memory content rather than event sequence.
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Rolando Masís-Obando @xrmasiso.bsky.social · 05/01/2026
What if we could tell you how well you’ll remember your next visit to your local coffee shop? ☕️ In our new Nature Human Behaviour paper, we show that the 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗮 𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 can be measured with neuroimaging – and 𝘁𝗵𝗮𝘁 𝘀𝗰𝗼𝗿𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝘀 𝗵𝗼𝘄 𝘄𝗲𝗹𝗹 𝗻𝗲𝘄 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀 𝘄𝗶𝗹𝗹 𝘀𝘁𝗶𝗰𝗸.
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Apurva Ratan Murty @apurvaratan.bsky.social · 04/12/2025
Need more fMRI data (beyond the amazing NSD)? Introducing MOSAIC! Incredible effort led expertly by Ben Lahner, with help from grad student Mayukh Deb. Work in collaboration with the amazing Aude Oliva! @neurosky.bsky.social. More below..
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Pin-Chun Chen @pinchunc.bsky.social · 24/11/2025
Thrilled that my recent paper, Hippocampal Ripples during Offline Periods Predict Human Motor Sequence Learning, was selected for the “This Week in The Journal” highlight! 🤩 Huge thanks to @bstaresina.bsky.social and our collaborators who made this work possible! doi.org/10.1523/JNEU... #JNeurosci
jneurosci.org
Hippocampal Ripples during Offline Periods Predict Human Motor Sequence Learning
High-frequency bursts in the hippocampus, known as ripples (80–120 Hz in humans), have been shown to support episodic memory processes. However, converging recent evidence in rodent models and human n...
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Anna á V. Guttesen @annaavali.bsky.social · 19/11/2025
Check out our new paper! We evaluate what we know (and don't know) about the link between memory consolidation during sleep and next-day learning 👇
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Andrew Lampinen @lampinen.bsky.social · 12/11/2025
What aspects of human knowledge do vision models like CLIP fail to capture, and how can we improve them? We suggest models miss key global organization; aligning them makes them more robust. Check out LukasMuttenthaler's work, finally out (in Nature!?) www.nature.com/articles/s41... + our blog! 1/3
nature.com
Aligning machine and human visual representations across abstraction levels - Nature
Aligning foundation models with human judgments enables them to more accurately approximate human behaviour and uncertainty across various levels of visual abstraction, while additionally improving th...
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Andrea Costantino @costantinoai.bsky.social · 12/11/2025
Super excited to share a new preprint! We asked a simple-but-big question: What changes in the brain when someone becomes an expert? Using chess ♟️ + fMRI 🧠 + representational geometry & dimensionality 📈, we ask: 1️⃣ WHAT information is encoded? 2️⃣ HOW is it structured? 3️⃣ WHERE is it expressed? 1/n
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Tomoyasu Horikawa @hkt52.bsky.social · 06/11/2025
Our "mind captioning" paper is now published in Science Advances @science.org . The method generates descriptive text of what we perceive and recall from brain activity — a linguistic interpretation of nonverbal mental content rather than language decoding. doi.org/10.1126/scia...
doi.org
Mind captioning: Evolving descriptive text of mental content from human brain activity
Nonverbal thoughts can be translated into verbal descriptions by aligning semantic representations between text and the brain.
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Yvonne Chen @yvonnechen.bsky.social · 05/11/2025
My Lab @unlv.edu is recruiting motivated students interested in human memory and brain research! Learn #EEG, #fMRI, and data analysis while exploring how we remember 🧠 📧 DM me or check out #PhD program www.unlv.edu/degree/phd-n... & www.unlv.edu/psychology/g... Plus, Vegas is a fun place to live!🤟
unlv.edu
Doctor of Philosophy - Neuroscience
This interdisciplinary Ph.D. program provides coursework and research training in neuroscience, with research mentoring spanning a range of different dimensions (basic to applied/clinical neuroscience...
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Aidan Horner @aidanhorner.bsky.social · 03/11/2025
I wrote a thing on episodic memory and systems consolidation. I hope you all enjoy it and/or find it interesting. A neural state space for episodic memories www.sciencedirect.com/science/arti... #neuroskyence #psychscisky #cognition 🧪
sciencedirect.com
A neural state space for episodic memories
Episodic memories are highly dynamic and change in nonlinear ways over time. This dynamism is not captured by existing systems consolidation theories …
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Reposted by Simon Faghel-Soubeyrand
Victoria Bosch @initself.bsky.social · 03/11/2025
Introducing CorText: a framework that fuses brain data directly into a large language model, allowing for interactive neural readout using natural language. tl;dr: you can now chat with a brain scan 🧠💬 1/n
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Pascal Mamassian @mamassian.bsky.social · 24/09/2025
A nice shift in perceived colour between central and peripheral vision. The fixated disc looks purple while the others look blue. The effect presumably comes from the absence of S-cones in the fovea. From Hinnerk Schulz-Hildebrandt: arxiv.org/pdf/2509.115...
An array of 9 purple discs on a blue background. Figure from Hinnerk Schulz-Hildebrandt.
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Marcel S. Kehl @mskehl.bsky.social · 27/10/2025
🚨Preprint: Semantic Tuning of Single Neurons in the Human Medial Temporal Lobe 1/8: How do human neurons encode meaning? In this work, led by Katharina Karkowski, we recorded hundreds of human MTL neurons to study semantic coding in the human brain: doi.org/10.1101/2025...
doi.org
Semantic Tuning of Single Neurons in the Human Medial Temporal Lobe
The Medial Temporal Lobe (MTL) is key to human cognition, supporting memory, emotional processing, navigation, and semantic coding. Rare direct human MTL recordings revealed concept cells, which were ...
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Simon Kern @skjerns.de · 24/10/2025
How well do classifiers trained on visual activity actually transfer to non-visual reactivation? #Decoding studies often rely on training in one (visual) condition and applying it to another (e.g. rest-reactivation). However: How well does this work? Show us what makes it work and win up to 1000$!
kaggle.com
IMAGINE-decoding-challenge
Predict which words participants were hearing, based upon brain activity recordings of visually seeing these items?
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Peter Kok @peterkok.bsky.social · 21/10/2025
@dotproduct.bsky.social's first first author paper is finally out in @sfnjournals.bsky.social! Her findings show that content-specific predictions fluctuate with alpha frequencies, suggesting a more specific role for alpha oscillations than we may have thought. With @jhaarsma.bsky.social. 🧠🟦 🧠🤖
jneurosci.org
Contents of visual predictions oscillate at alpha frequencies
Predictions of future events have a major impact on how we process sensory signals. However, it remains unclear how the brain keeps predictions online in anticipation of future inputs. Here, we combin...
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Shahab Bakhtiari @shahabbakht.bsky.social · 13/10/2025
What do we talk about when we talk about "readout"? I argued that our overly specialized, modular approach to studying the brain has given us a simplistic view of readout. 🧠📈
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Matthias Nau @matthiasnau.bsky.social · 13/10/2025
Why do we remember emotional events so vividly? Our new paper @nathumbehav.nature.com suggests that emotional arousal enhances memory by strengthening integration across large-scale brain networks! Led by the amazing @jadynpark.bsky.social & @ycleong.bsky.social! doi.org/10.1038/s415...
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Mariam Aly @mariamaly.bsky.social · 25/09/2025
A memory can be represented at different levels of granularity, from highly specific to generalized. Different representational formats of a memory can be used at different times or in different contexts, and draw on different neural representations. doi.org/10.31234/osf...
doi.org
OSF
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Yuki Kamitani @ykamit.bsky.social · 18/09/2025
Our article is out in Annual Review of Vision Science: “Visual Image Reconstruction from Brain Activity via Latent Representation” We trace the path from early brain decoding to modern NeuroAI, highlight progress & pitfalls, and discuss future directions www.annualreviews.org/content/jour...
annualreviews.org
Visual Image Reconstruction from Brain Activity via Latent Representation | Annual Reviews
Visual image reconstruction, the decoding of perceptual content from brain activity into images, has advanced significantly with the integration of deep neural networks (DNNs) and generative models. T...
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Alex Barnett @alexbarnett.bsky.social · 16/09/2025
New preprint! My stellar undergrad, June Kim, & @charan-neuro.bsky.social find that intersubject pattern similarity at encoding (especially in posteromedial cortex) relates to shared/differing content between Ss at recall (measured using topic modeling) www.biorxiv.org/content/10.1...
biorxiv.org
Natural language processing captures memory content associated with shared neural patterns at encoding
People can experience the same event yet form distinct memories shaped by individual interpretations. Prior research shows that multivariate activity patterns in the Default Mode Network (DMN) are cor...
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Hayoung Song @hayoungsong.bsky.social · 05/09/2025
How does the brain🧠 make causal inferences and use memories to understand narratives🎬? We built an RNN🤖 with key-value episodic memory that learns causal relationships between events and retrieves memories like humans do! Preprint www.biorxiv.org/content/10.1... w/ @qlu.bsky.social, Tan Nguyen &👇
biorxiv.org
A neural network with episodic memory learns causal relationships between narrative events
Humans reflect on past memories to make sense of an ongoing event. Past work has shown that people retrieve causally related past events during comprehension, but the exact process by which this causa...
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Matthias Nau @matthiasnau.bsky.social · 04/09/2025
A transformation from vision to imagery in the human brain. Intriguing new preprint by Roy & Naselaris et al for anyone interested in mental imagery! www.biorxiv.org/content/10.1...
biorxiv.org
A transformation from vision to imagery in the human brain
Extensive work has shown that the visual cortex is reactivated during mental imagery, and that models trained on visual data can predict imagery activity and decode imagined stimuli. These findings ma...
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Matthias Nau @matthiasnau.bsky.social · 28/08/2025
Quantifying memory recall is hard! Luckily, natural language processing (incl. #LLMs) offers new, automated, and scalable ways to do that! Great new review by Fenerci & @signysheldon.bsky.social in @cp-trendscognsci.bsky.social! www.cell.com/trends/cogni...
cell.com
Studying memory narratives with natural language processing
Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differenc...
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Alexander Huth @alexanderhuth.bsky.social · 18/08/2025
New paper with @rjantonello.bsky.social @csinva.bsky.social, Suna Guo, Gavin Mischler, Jianfeng Gao, & Nima Mesgarani: We use LLMs to generate VERY interpretable embeddings where each dimension corresponds to a scientific theory, & then use these embeddings to predict fMRI and ECoG. It WORKS!
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Adrien Doerig @adriendoerig.bsky.social · 07/08/2025
🚨 Finally out in Nature Machine Intelligence!! "Visual representations in the human brain are aligned with large language models" 🔗 www.nature.com/articles/s42...
nature.com
High-level visual representations in the human brain are aligned with large language models - Nature Machine Intelligence
Doerig, Kietzmann and colleagues show that the brain’s response to visual scenes can be modelled using language-based AI representations. By linking brain activity to caption-based embeddings from lar...
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Xiongbo Wu @xiongbowu.bsky.social · 30/07/2025
🚨 New preprint alert! Excited to share our latest work on alpha/beta activity, eye movements, and memory. Across 4 experiments combining scalp EEG/iEEG with eye tracking, we show that alpha/beta activity directly reflects eye movements, and only indirectly relates to memory. 👇 Highlights (1/7):
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Courtois Project on Neuronal Modelling @cneuromod.ca · 30/07/2025
New CNeuroMod-THINGS open-access fMRI dataset: 4 participants · ~4 000 images (720 categories) each shown 3× (12k trials per subject)· individual functional localizers & NSD-inspired QC . Preprint: arxiv.org/abs/2507.09024 Congrats Marie St-Laurent and @martinhebart.bsky.social !!
four brain maps showing noise ceiling estimates in response to image presentation
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Cody Dong @codydong.bsky.social · 26/07/2025
My first, first author paper, comparing the properties of memory-augmented large language models and human episodic memory, out in @cp-trendscognsci.bsky.social! authors.elsevier.com/a/1lV174sIRv... Here’s a quick 🧵(1/n)
authors.elsevier.com
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Fernando Rosas @frosas.bsky.social · 22/07/2025
Finally published: “Top-down and bottom-up neuroscience: overcoming the clash of research cultures” www.nature.com/articles/s41... Looking for ways to better understand different neuroscientific perspectives and enable productive collaborations
nature.com
Top-down and bottom-up neuroscience: overcoming the clash of research cultures - Nature Reviews Neuroscience
As scientists, we want solid answers, but we also want to answer questions that matter. Yet, the brain’s complexity forces trade-offs between these desiderata, bringing about two distinct research app...
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Anna á V. Guttesen @annaavali.bsky.social · 21/07/2025
Excited to share our newly published paper! 👇 Massive thanks to @harrington-mo.bsky.social @sacairney.bsky.social @mggaskell.bsky.social
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Olivia Christiano @oliviachristiano.bsky.social · 19/07/2025
How reliable is OPM-MEG, and how does it compare to other neuroimaging modalities? 🤔 In a new preprint with ‪@s-michelmann.bsky.social‬, we evaluate the reliability of OPM-MEG within & between individuals, and compare it to fMRI & iEEG during repeated movie viewing. 🧠 📄 doi.org/10.1101/2025...
doi.org
Reliability and signal comparison of OPM-MEG, fMRI & iEEG in a repeated movie viewing paradigm
Optically pumped magnetometers (OPMs) offer a promising advancement in noninvasive neuroimaging via magnetoencephalography (MEG), but establishing their reliability and comparability to existing metho...
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Rob Mok @robmok.bsky.social · 18/07/2025
JOB ALERT: Computational Cognitive Neuroscience Postdoc position in Osaka, Japan! Possible start in October 2025 (contact me ASAP), or from April 2026. PLEASE REPOST! #postdocjobs #neuroskyence #neuroscience #psychscisky #compneurosky #neurojobs 1/
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Le Neuro (Institut-Hôpital neurologique de Montréal) @theneuro.bsky.social · 15/07/2025
Happy 107th Birthday, Brenda Milner! Her contributions to neuropsychology shaped the way we understand the human brain. From surviving two world wars and two pandemics, to paving the way for future generations of researchers, Milner’s legacy continues. @mcgill.ca @cusm-muhc.bsky.social
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Simon Faghel-Soubeyrand @simonfsoubeyrand.bsky.social · 12/07/2025
www.nature.com/articles/s43...
nature.com
Inter-individual and inter-site neural code conversion without shared stimuli - Nature Computational Science
A neural code conversion method is introduced using deep neural network representations to align brain data across individuals without shared stimuli. The approach enables accurate inter-individual br...
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