pyhctsa is out! A native Python port of the majority of the hctsa feature library (highly comparative time-series analysis). Thousands of interpretable time-series features available via a pip install. Built by Joshua Moore. Paper: doi.org/10.21105/jos... Code: github.com/DynamicsAndN...
Ben Fulcher
@bendfulcher.bsky.social
I lead the Dynamics and Neural Systems Group at the School of Physics, the University of Sydney. We develop time series tools & physical models to understand the dynamics of complex (usually neural) systems. Also: @bendfulcher@fediscience.org
Applications are open for SFI's 2027 Complexity Postdoctoral Fellowships. SFI is looking for recent Ph.D. graduates with strong quantitative and computational skills who want to pursue independent, transdisciplinary research. Deadline: September 30, 2026 Apply: santafe.edu/sfifellowship
Applications now open for Complexity Postdoctoral Fellowships at @sfiscience.bsky.social! apply-sfi.smapply.org/prog/complex...
Complexity Postdoctoral Fellowship - Santa Fe Institute
apply-sfi.smapply.org
My short (7.5 min) talk on "Comprehensive quantitative phenotyping of physiological dynamics": www.youtube.com/watch?v=dPH1...
Comprehensive quantitative phenotyping of physiological dynamics
YouTube video by Faculty of Science, University of Sydney
youtube.com
Function is not tied to specific brain structures or time scales. The brain is not just a set of parts that each “do their own job”. Instead, networks are multifunctional and active across different speeds simultaneously. doi.org/10.1073/pnas... #neuroscience
Shared spatial and temporal principles govern connectome dynamics across timescales | PNAS
While the brain processes information at various speeds, little is known about how the functional connectome can concurrently support multiple spee...
doi.org
Our paper "Neural timescales from a computational perspective" is finally out in @natneuro.nature.com: www.nature.com/articles/s41... We discuss how computational models and methods can distill empirical observations on neural timescales into quantitative, testable theories of brain computation.
Neural timescales from a computational perspective - Nature Neuroscience
This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...
nature.com
I’ve officially resigned as Associate Editor for Frontiers in Systems Neuroscience. It used to be a reputable journal, but became a case study in how forced automation destroys academic integrity. 👇
How do time series foundation models forecast unseen dynamical systems? In new experiments, we find that small transformers learn to approximate transfer operators in-context. (1/N) arxiv.org/abs/2602.18679
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...
Unfalsifiable by Design: A Year of Trying and Failing to Reproduce a Human Microbiome and Autism Study
The myth of open data, reproducibility, responsibility, and accountability in science, and your role in it
merenlab.org
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...
Identifying statistical indicators of temporal asymmetry using a data-driven approach
The dynamics of time-reversible systems are statistically indistinguishable when observed forward or backward in time. A rich literature of statistical methods to distinguish irreversible dynamics fro...
journals.aps.org
New preprint: "Identifying statistical indicators of temporal asymmetry using a data-driven approach" arxiv.org/abs/2511.15991 _Can we statistically distinguish the forward- versus reverse-time dynamics of a system from a finite time series?_
🚨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...
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 close up of a person 's hand holding a marker that says sharpie
Alt: a close up of a person's hand holding a marker that says sharpie
media.tenor.com
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...
Scientific Publishing: Rethinking how research is reviewed and published
Taking a radical new approach to the publication process resulted in eLife losing its impact factor, but authors, reviewers, editors and funders support the journal and its efforts to reform scientifi...
elifesciences.org
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...
Coding with AI - Better Code, Better Science
bettercodebetterscience.github.io
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 ;)
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...
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 😉
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...
OHBM 2025 | Oral Session | Stuart Oldham | Only a matter of time: developmental heterochronicity c…
YouTube video by Organization for Human Brain Mapping
youtube.com
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...
Job Search
careers.pageuppeople.com
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...
Inferring intrinsic neural timescales using optimal control theory - Nature Communications
Here, the authors develop novel dynamical methods to model brain regions’ intrinsic neural timescales (INTs) from data, and find that they couple whole-brain structural connectivity to dynamic switchi...
nature.com
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.🧵⬇️
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
Time-series dimension reduction: a comprehensive review and conceptual unification of algorithms
High-dimensional multivariate time-series data are analyzed in fields such as neuroscience, climatology, and finance. Time-series dimension-reduction (TSDR) methods are important for extracting inform...
techrxiv.org
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.
Copula-based analytical results of horizontal visibility graphs for correlated time series
The visibility graph (VG) algorithm and its variants have been extensively studied in the time series analysis as they transform the time series into the network of nodes and links, enabling to charac...
arxiv.org