How every layer of science's "self-correcting machinery" failed when Iva Veseli and I simply wanted to reproduce the findings of a high-profile study on gut microbiome and autism:
merenlab.org/2026/04/15/u...
Our work on time reversibility has been published online today in @apsphysics.bsky.social Physical Review Research. See below for summary :)
journals.aps.org/prresearch/a...
🚨new lab preprint; brain fingerprinting entirely revisited:
Can we differentiate individuals from just seconds of neurophysiological recordings with machine learning, without resorting to black-box approaches?
In this work, Maxence Lapatrie says 'yes'.
www.biorxiv.org/content/10.6...
Schematic of theta waves and gamma packets recorded from the mouse visual cortex
How does the visual cortex coordinate neural activity over spatial and temporal scales? We found broad θ waves organize local γ bursts and spiking, forming a flexible spatiotemporal code to multiplex feedforward/feedback signals. Now out in full @natcomms.nature.com: doi.org/10.1038/s414... 🧵
New preprint!
So, say you're studying some critical transition. How do you catch its universality? Pair correlations? Boring!
We threw line segments at the system, looked at intersections with clusters, and uncovered static and dynamical universal behavior of MIPS!
arxiv.org/abs/2511.09444
a while ago, I made this feed for neuroscience/cognitive science summer schools. after some tuning, it generally manages to find cool events. 🙂
bsky.app/profile/did:...
Scientific publishing: Rethinking how research is reviewed and published
Review of how the loss of impact factor affected submissions at eLife - uneven drop across countries, but generally holding up remarkably well and shows a new model is possible
elifesciences.org/articles/110...
Synaptome architecture shapes regional dynamics in the mouse brain | doi.org/10.1371/jour...
How do diverse synapses relate to the spatial patterning of whole-brain dynamics? Justine Hansen explores @plosbiology.org ⤵️
😂🫡
My new chapter of Better Code, Better Science on AI-assisted coding is now complete! It's been completely revised in an attempt to futureproof it. Comments welcome. bettercodebetterscience.github.io/book/ai-codi...
New toolbox for visualizing subcortex in python and R is very well made.
Worth pivoting your research program to study subcortical structures just as an excuse to use it ;)
Nine subcortical/cerebellar atlases included in the subcortex_visualization Python package (and subcortexVisualizationR package in R). The atlases are depicted in two-dimensional vector graphic format.
The extended version of my thesis procrastination project/subcortex visualization package is out now in both Python and R, now that I’ve graduated 🤠 This figure shows the 9 atlases included (and counting)!
Preprint: www.biorxiv.org/content/10.6...
Website: anniegbryant.github.io/subcortex_vi...
Thrilled to see the first preprint of the lab out 🤩 Check it out if you need to compare dynamics in your data and RNN (or any other combinations of dynamical systems)!
Wanna compare dynamics across neural data, RNNs, or dynamical systems? We got a fast and furious method🏎️
The 1st preprint of my PhD 🥳 fast dynamical similarity analysis (fastDSA):
📜: arxiv.org/abs/2511.22828
💻: github.com/CMC-lab/fast...
I’ll be @cosynemeeting.bsky.social - happy to chat 😉
My very normal, by the book presentation from this years OHBM is now available. So if you weren't at OHBM, were there but happened to miss it, or if you did see it and just want to relive it all over again, here is your chance :)
I'm quite fond of this one.
www.youtube.com/watch?v=lP86...
Come and join our team! We are looking for a Research Officer to help with recruitment and assessment on a large-scale human brain imaging study:
careers.pageuppeople.com/513/cw/en/jo...
New preprint! Do you like ocean waves? We found similar waves on bacterial colonies! We found that this collective behavior, known as rippling, is nothing but surface waves on an active nematic. @princeton.edu @mpipks.bsky.social @ub.edu @icreacommunity.bsky.social
www.biorxiv.org/content/10.1...
Finally got the job ad—looking for 2 PhD students to start spring next year:
www.gao-unit.com/join-us/
If comp neuro, ML, and AI4Neuro is your thing, or you just nerd out over brain recordings, apply!
I'm at neurips. DM me here / on the conference app or email if you want to meet 🏖️🌮
Exciting new work from @lindenmp.bsky.social and friends!
Inferring intrinsic neural timescales using optimal control theory
www.nature.com/articles/s41...
How do brain areas control each other? 🧠🎛️
✨In our NeurIPS 2025 Spotlight paper, we introduce a data-driven framework to answer this question using deep learning, nonlinear control, and differential geometry.🧵⬇️
And there's an open python repo with really clear and easy to read and code implementing the key methods:
github.com/KieranOwens/...
Take a look?! 👀
Kieran explains how all the methods can be understood through these conceptual groupings, derives new relationships between existing methods, and provides some case-study demonstrations/comparisons of how insanely well they can work on data
These powerful methods are underappreciated: A recent review of the field included *0* methods designed for time-series data, instead focusing on generic dimension reduction methods.
This paper assembles a diversity of >60 scientific methods for the first time, and unifies them across 7 categories.
New preprint! (by Kieran Owens)
Of interest to anyone who analyzes time-series data!:
"Time-series dimension reduction: a comprehensive review and conceptual unification of algorithms"
www.techrxiv.org/users/999518...
#timeseries #dimensionreduction #complexsystems
Congrats to Dr Caroline Wormell from the School of Mathematics and Statistics on their recently announced DECRA award "From chaos to clarity: reliable data-driven analysis of dynamical systems."
Our new preprint is out in arXiv: Copula-based analytical results of horizontal visibility graphs for correlated time series arxiv.org/abs/2508.08934 This is from the collaboration with my undergraduate student Jeong-Min Lee.
If you're interested in the statistics of time-irreversibility, and how they could be used to capture novel, interpretable properties from real-world time series, take a look:
arxiv.org/abs/2511.15991
(Code here: github.com/DynamicsAndN...)
The breath of comparison (of both methods and processes) also allowed us to demonstrate that all tested indices of irreversibility had weaknesses: i.e., we could always find an irreversibile process on which any given irreverisbility index will fail to detect irreversibility.
We found key families of algorithmic constructions that were could accurately index irreversibility: (i) generalized autocorrelation functions; (ii) symbolic sequences; and (iii) forecasting-derived metrics. Some recapitulate concepts studied previously but in isolation; others are novel directions
He we compared >6000 time-series metrics to index time reversibility from simulations of 35 different reversible and irreversible processes
