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simonfsoubeyrand.bsky.social
Simon Faghel-Soubeyrand
@simonfsoubeyrand.bsky.social
110 followers 200 following 24 posts
Oxford Postodoctoral Researcher, Staresina Lab || Banting Postdoctoral Fellow || vision, memory, sleep, machine learning
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simonfsoubeyrand.bsky.social
Simon Faghel-Soubeyrand @simonfsoubeyrand.bsky.social · Mar 25
Preprint alert! 🚨
1/ How does deep sleep reshape our memories? Our new study shows that slow-wave sleep (SWS) reorganises episodic memory networks, shifting recall from the parietal cortex to the anterior temporal lobe (ATL). With Polina Perzich and @bstaresina.bsky.social . A thread below👇
biorxiv-neursci.bsky.social
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · Mar 25
Slow wave sleep supports the reorganisation of episodic memory networks https://www.biorxiv.org/content/10.1101/2025.03.24.644966v1
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Reposted by Simon Faghel-Soubeyrand
mariamaly.bsky.social
Mariam Aly @mariamaly.bsky.social · 13d
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...
OSF
doi.org
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Reposted by Simon Faghel-Soubeyrand
ykamit.bsky.social
Yuki Kamitani @ykamit.bsky.social · 20d
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...
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...
www.annualreviews.org
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Reposted by Simon Faghel-Soubeyrand
alexbarnett.bsky.social
Alex Barnett @alexbarnett.bsky.social · 22d
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...
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...
www.biorxiv.org
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Reposted by Simon Faghel-Soubeyrand
hayoungsong.bsky.social
Hayoung Song @hayoungsong.bsky.social · Sep 5
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 &👇
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...
www.biorxiv.org
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Reposted by Simon Faghel-Soubeyrand
matthiasnau.bsky.social
Matthias Nau @matthiasnau.bsky.social · Sep 4
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...
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...
www.biorxiv.org
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Reposted by Simon Faghel-Soubeyrand
matthiasnau.bsky.social
Matthias Nau @matthiasnau.bsky.social · Aug 28
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...
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...
www.cell.com
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Reposted by Simon Faghel-Soubeyrand
alexanderhuth.bsky.social
Alexander Huth @alexanderhuth.bsky.social · Aug 18
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!
biorxiv-neursci.bsky.social
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · Aug 13
Evaluating scientific theories as predictive models in language neuroscience https://www.biorxiv.org/content/10.1101/2025.08.12.669958v1
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Reposted by Simon Faghel-Soubeyrand
adriendoerig.bsky.social
Adrien Doerig @adriendoerig.bsky.social · Aug 7
🚨 Finally out in Nature Machine Intelligence!!
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
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...
www.nature.com
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Reposted by Simon Faghel-Soubeyrand
xiongbowu.bsky.social
Xiongbo Wu @xiongbowu.bsky.social · Jul 30
🚨 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):
biorxiv-neursci.bsky.social
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · Jul 30
Low-frequency brain oscillations reflect the dynamics of the oculomotor system: a new perspective on subsequent memory effects https://www.biorxiv.org/content/10.1101/2025.07.29.667451v1
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Reposted by Simon Faghel-Soubeyrand
cneuromod.ca
Courtois Project on Neuronal Modelling @cneuromod.ca · Jul 30
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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Reposted by Simon Faghel-Soubeyrand
codydong.bsky.social
Cody Dong @codydong.bsky.social · Jul 26
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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Reposted by Simon Faghel-Soubeyrand
frosas.bsky.social
Fernando Rosas @frosas.bsky.social · Jul 22
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
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...
www.nature.com
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Reposted by Simon Faghel-Soubeyrand
annaavali.bsky.social
Anna á V. Guttesen @annaavali.bsky.social · Jul 21
Excited to share our newly published paper! 👇 Massive thanks to @harrington-mo.bsky.social @sacairney.bsky.social @mggaskell.bsky.social
cognitionjournal.bsky.social
Cognition @cognitionjournal.bsky.social · Jul 21
"Does overnight memory consolidation support next-day learning?"

📢 New paper from: Anna Guttesen (annaavali.bsky.social), Marcus Harrington (@harrington-mo.bsky.social), Gareth Gaskell (mggaskell.bsky.social), & Scott Cairney (sacairney.bsky.social)

www.sciencedirect.com/science/arti...
Does overnight memory consolidation support next-day learning?
Sleep supports memory consolidation and next-day learning. The Active Systems model of consolidation proposes that sleep facilitates a shift in the me…
www.sciencedirect.com
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Reposted by Simon Faghel-Soubeyrand
oliviachristiano.bsky.social
Olivia Christiano @oliviachristiano.bsky.social · Jul 19
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...
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...
doi.org
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Reposted by Simon Faghel-Soubeyrand
robmok.bsky.social
Rob Mok @robmok.bsky.social · Jul 18
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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Reposted by Simon Faghel-Soubeyrand
theneuro.bsky.social
Le Neuro (Institut-Hôpital neurologique de Montréal) @theneuro.bsky.social · Jul 15
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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simonfsoubeyrand.bsky.social
Simon Faghel-Soubeyrand @simonfsoubeyrand.bsky.social · Jul 12
www.nature.com/articles/s43...
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...
www.nature.com
2
Reposted by Simon Faghel-Soubeyrand
feilong.bsky.social
Feilong Ma @feilong.bsky.social · Jul 11
Excited to share our News&Views on Kamitani Lab's NatComputSci paper! Their neural code converter enables transformation of brain activity patterns across individuals, and it doesn't need shared stimuli or connectivity information!
www.nature.com/articles/s43...
Advancing neural decoding with deep learning - Nature Computational Science
A recent study introduces a neural code conversion method that aligns brain activity across individuals without shared stimuli, using deep neural network-derived features to match stimulus content.
www.nature.com
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Reposted by Simon Faghel-Soubeyrand
matthiasnau.bsky.social
Matthias Nau @matthiasnau.bsky.social · Jul 6
The most brain-like representations of visual neural networks are also the most universal ones, i.e., they are largely independent of a network’s architecture or training. Cool new work by Chen & Bonner in #ScienceAdvances! #neuroAI
www.science.org/doi/10.1126/...
Universal dimensions of visual representation
Probing neural representations reveals universal aspects of vision in artificial and biological networks.
www.science.org
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Reposted by Simon Faghel-Soubeyrand
martinhebart.bsky.social
Martin Hebart @martinhebart.bsky.social · Jun 23
What makes humans similar or different to AI? In a paper out in @natmachintell.nature.com led by @florianmahner.bsky.social & @lukasmut.bsky.social, w/ Umut Güclü, we took a deep look at the factors underlying their representational alignment, with surprising results.

www.nature.com/articles/s42...
Dimensions underlying the representational alignment of deep neural networks with humans - Nature Machine Intelligence
An interpretability framework that compares how humans and deep neural networks process images has been presented. Their findings reveal that, unlike humans, deep neural networks focus more on visual ...
www.nature.com
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Reposted by Simon Faghel-Soubeyrand
xianhuihe.bsky.social
Xianhui He @xianhuihe.bsky.social · Jun 16
How does our brain learn that thunder follows lightning? We don't just remember two separate events; we build a predictive model to anticipate the world. My research dives into this very question: how we learn and predict the order of events. 🧵👇 1/9 #neuroscience #memory #sleep
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simonfsoubeyrand.bsky.social
Simon Faghel-Soubeyrand @simonfsoubeyrand.bsky.social · Jun 16
New preprint alert 🚨
@xianhuihe.bsky.social shows how memories of learned object sequences reshape brain representational geometry—even when task-irrelevant.

This change in representational format (linked to higher-level DNN features) correlates with amount of sleep

www.biorxiv.org/content/10.1...
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Reposted by Simon Faghel-Soubeyrand
katschruers.bsky.social
Katrijn Schruers @katschruers.bsky.social · May 30
Congrats to our amazing postdoc @mskehl.bsky.social for their fantastic talk at the REPLAY conference in Cardiff! 🧠 Their work on "Human ripples facilitate memory consolidation by reactivating learning-related neurons" sparked many great discussions. Proud lab cheering him on!
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Reposted by Simon Faghel-Soubeyrand
jeanremiking.bsky.social
Jean-Rémi King @jeanremiking.bsky.social · May 30
Our EEG-Foundation Challenge, on more than 3,000 subjects, is accepted at #Neurips 2025, go check it out:
eeg2025.github.io

Led by B Aristimunha D Truong P Guetschel and SY Shirazi!
EEG Challenge (2025)
From Cross-Task to learning subject invariance representation in EEG decoding
eeg2025.github.io
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Reposted by Simon Faghel-Soubeyrand
biorxiv-neursci.bsky.social
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · May 27
A Python Toolbox for Representational Similarity Analysis https://www.biorxiv.org/content/10.1101/2025.05.22.655542v1
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