Simon Kern

Simon Kern

@skjerns.de

Sleep & Memory researcher @ CIMH Mannheim with @gordonfeld.bsky.social . Interested in replay and applied machine learning in the context of episodic and declarative memory. MEG and Python enthusiast.

506 followers276 following171 posts

Simon Kern reposted

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 🧵

Simon Kern reposted

Closed-loop stimulation may improve memory through more than just boosting slow waves. Grimaldi et al. found that better retention tracked the balance of slow-oscillation vs delta coupling to spindles, along with ⬆️ parasympathetic activity—not simply stronger SO–spindle coupling. buff.ly/JyhmjGn

buff.lyAcoustic enhancement of slow wave sleep improves memory retention by coordinating brain oscillatory rhythms and autonomic activitySleep plays a crucial role in memory consolidation. While the interaction between sleep oscillations and autonomic activity likely influences this process,

Simon Kern reposted

This is an absolutely great metaphor for explaining why experimentally figuring out what the brain is doing is hard. I may have to steal this.

Ben Hayden@benhayden.bsky.social

This is a tricky issue and may require philosophers. For example, in an election (assuming it doesnt come down to one vote), no single vote is essential, no vote is more important than any other; any vote could be removed without affecting the outcome. Many neural processes may be election-like.

Simon Kern reposted

I care about reproducibility, but I find it deeply problematic that the British ecological society is trying to extract free labour from academics (oh no, you get free membership for a year!) to work for them for 3 years on computational reproducibility checks. apply.workable.com/britishecolo...

apply.workable.comAssociate Editor (Code Integrity and Accessibility) - British Ecological SocietyVolunteer role: Associate Editor (Code Integrity and Accessibility) Organisation: British Ecological Society – Methods in Ecology and Evolution Term: 3 years Closing date: 25th Sept 17.00 BST…

Simon Kern reposted

This is wild. >1/2 of HC synapses disappear in artificial hibernation, come back in same/similar locations & memories intact. ~1/2 of engram synapses-between two memory-tagged cells-are clustered on dendrites, those preferentially spared. Not biggest synapses. 1/ www.science.org/doi/10.1126/...

Simon Kern reposted

Come and join our replication initiative in visual neuroscience! Low bar for entry, ideal for anyone from a Master’s student looking for a thesis to faculty who want to get back to the bench. 🤓 re-vision-initiative.org

re-vision-initiative.orgre:vision | Replication Initiative for Visual NeuroscienceTest whether published visual-neuroscience findings (NSD, THINGS, etc.) generalize to broadly-sampled natural images using the LAION-fMRI (LfMRI) 7T dataset.
re-vision-init.bsky.social@re-vision-init.bsky.social

(1/6) Do our visual neuroscience findings actually replicate? And do they generalize beyond the datasets they were found in? We've lauched re:vision, a community-driven initiative to answer these questions, and we are looking for scientistis to participate. re-vision-initiative.org

Simon Kern reposted

Simon Kern reposted

Simon Kern reposted

This is one of my favourite things. Direct replication of MEG and fMRI findings in intracranial recordings and a demonstration that cortical representations update in the right direction around hippocampal ripples.

Blake Richards@tyrellturing.bsky.social

For a long time I felt like there was a hesitation in neuroscience to ascribe anything like a planning function to the various "replay" events we see in the hippocampus, but I think this is rapidly changing. Here's another new entry in human epilepsy patients: www.nature.com/articles/s41... 🧠📈 🧪

Simon Kern reposted

Simon Kern reposted

Simon Kern reposted

If you're dying with anxiety because the status of your paper has not changed from "under review" for weeks, you may want to read the Future of Peer Review report from Silverchair that came out recently and replaced the outdated Publons report from 2018... #ScientificPublishing #PeerReview /

Simon Kern reposted

New preprint! We show low arousal states promote hippocampal ripple genesis in sleep and wake. This bridges rodent work, where ripples predominate during sleep, with human studies reporting ripples during active behavior, identifying low arousal as a common mechanism www.biorxiv.org/content/10.6...

biorxiv.orgArousal state modulates human hippocampal ripplesHippocampal ripples are transient, high-frequency oscillations linked to memory replay and consolidation. Ripples are well-characterized in rodents to occur during periods of behavioral inactivity (i....

Simon Kern reposted

Are the traveling dynamics of sleep slow waves functionally involved in memory consolidation? A new paper from the lab led by @norarouast.bsky.social shows that auditory stimulation during sleep disturbs SWS and affects the traveling dynamics of SWs - which mediated impaired memory consolidation!

Nora Roüast@norarouast.bsky.social

Ever wondered what having auditory stimulation does to the sleep itself? Random stimulation disturbs SWS, memory, and travelling dynamics of slow waves. New paper in iScience with @mschoenauer.bsky.social, @denizkumral.bsky.social, and Steffen Gais! doi.org/10.1016/j.is... #sleep #neuroskyence

Simon Kern reposted

Replying to @richardsever.bsky.social

The extent of the IF obsession is evident from any and every Google search for a journal - even venues that don't warrant one. This literally makes or breaks journals - non-profits are hit particularly hard - and it stifles innovation and distorts science. 2/2

Simon Kern reposted

🧠 New preprint! How well can current algorithms *actually* detect neural "replay" in the human brain under absolutely optimal conditions? We built FASTIMAGES: A combined MEG + fMRI benchmark with KNOWN neural sequences, so replay-detection methods can finally be validated against a ground truth.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).
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🧠 New preprint! How well can current algorithms *actually* detect neural "replay" in the human brain under absolutely optimal conditions? We built FASTIMAGES: A combined MEG + fMRI benchmark with KNOWN neural sequences, so replay-detection methods can finally be validated against a ground truth.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).
View full thread

Effect sizes are comparable in the native modality (TDLM Cohen's d ≈ 0.77). Bootstrap power analysis shows: ~20 participants × 20 trials → 80% power. As this was an absolutely best case scenario and real effects are likely much smaller, you'll likely need to go beyond that for finding real replay.

🧠 New preprint! How well can current algorithms *actually* detect neural "replay" in the human brain under absolutely optimal conditions? We built FASTIMAGES: A combined MEG + fMRI benchmark with KNOWN neural sequences, so replay-detection methods can finally be validated against a ground truth.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).
View full thread

TDLM (built for MEG, Liu et al. 2021) successfully finds significant "sequenceness" at the expected time lag in ALL four speed conditions. But variance is high! Only ~half of participants are individually significant, and sequenceness is highly correlated to decoder quality, not behaviour.

SODA (built for fMRI, Wittkuhn et al. 2021) also recovers the sequences, mainly driven by the "offset" period, which is significant in every speed condition. Similarly, individual participants are not always significant, and variance between participants is high. Dependency on the decoder is less!

🧠 New preprint! How well can current algorithms *actually* detect neural "replay" in the human brain under absolutely optimal conditions? We built FASTIMAGES: A combined MEG + fMRI benchmark with KNOWN neural sequences, so replay-detection methods can finally be validated against a ground truth.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).
View full thread

As a first step, we recorded a localizer, in which participants saw the five images slowly, in random order. Here, apply standard techniques to train a brain decoder that will be used later for sequence detection. Decoders work as expected ~55% in MEG (peak ~150 ms) and ~70% in fMRI (peak ~4 s).

You can literally see the sequence order in the averaged decoder output of the MEG and partially in the fMRI 👀 however, individual trials are much noisier. Perfect, so let's test TDLM and SODA!

🧠 New preprint! How well can current algorithms *actually* detect neural "replay" in the human brain under absolutely optimal conditions? We built FASTIMAGES: A combined MEG + fMRI benchmark with KNOWN neural sequences, so replay-detection methods can finally be validated against a ground truth.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).

The problem: Methods like TDLM & SODA are widely used to find replay, but we rarely know *if* or *when* replay actually happened. Without invasive recordings -> no ground truth. Therefore, we created a dataset that contains clear neural sequences to benchmark current algorithms.

FASTIMAGES = 70 participants (30 MEG + 40 fMRI) who saw 5 images flashing in a fast sequences (132–612 ms onset-to-onset), plus localizer trials to train decoders. This produces clearly-expressed neural sequences with a KNOWN order and timing. See our project page for some animations.

cimh-clinical-psychology.github.ioFASTIMAGES: Validating replay detection methods in human neuroimagingA combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).

Simon Kern reposted

Interested in human replay and solid methods? Jointly with @skjerns.de we're releasing a benchmark dataset with known ground-truth neural sequences in MEG & fMRI, for developing & validating replay methods. First test: existing methods show similar effect sizes, but room to improve shorturl.at/6TgIr

shorturl.atFASTIMAGES: Validating replay detection methods in human neuroimaging using a combined MEG and fMRI datasetStudies in rodents and humans using invasive electrophysiology have established that neural replay is a ubiquitous phenomenon in the brain that is associated with a wide range of cognitive functions, ...

Simon Kern reposted

Der Tankrabatt kostet in zwei Monaten übrigens knapp 25-mal so viel wie die von der Bundesregierung versprochene und jetzt gestoppte Erhöhung der Wohnkostenpauschale beim BAFöG.

Simon Kern reposted

Honored to be giving a keynote at Psychology and the Brain (PuG) this week in Heidelberg. Since starting the lab in 2019, we’ve had many wonderful collaborations across Germany, and I’m excited to share our work on the computational neuroscience of interoception. See you there! pug2026.org

pug2026.orgPuG2026

Simon Kern reposted

No they don't! Humans report being conscious half of the time when awoken from NREM sleep. The NREM/REM, conscious/unconscious dichotomy has been thoroughly debunked. It's time we stop oversimplifying the relationship between sleep and consciousness!

Simon Kern reposted

1/ Can AI help researchers check whether published social science results actually reproduce? In our new PNAS paper, we tested this directly in the AI Replication Games: 288 researchers, 103 teams, and real replication packages from quantitative social science.

Simon Kern reposted

Simon Kern reposted

New paper showing insufficient evidence for neuroimaging features to define reproducible, biologically valid, & clinically meaningful schizophrenia subtypes. The subtypes identified to date likely reflect continuous variation within the disorder rather than discrete, biologically distinct entities.

Biological Psychiatry@biologicalpsych.bsky.social

A review of 18 studies found no consistently reproducible subtypes of schizophrenia, suggesting that differences in brain structure across patients may reflect a spectrum rather than discrete biological categories.