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.

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...

Arousal state modulates human hippocampal ripples

Hippocampal 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....

biorxiv.org

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 · last mo.

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

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

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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.

FASTIMAGES: Validating replay detection methods in human neuroimaging

A combined MEG + fMRI benchmark dataset with known neural sequences to validate replay detection methods (TDLM and SODA).

cimh-clinical-psychology.github.io

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

FASTIMAGES: Validating replay detection methods in human neuroimaging using a combined MEG and fMRI dataset

Studies 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, ...

shorturl.at

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

pug2026.org

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.

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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 · 3mo ago

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.