@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
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04.03.2026 07:48 — 👍 1 🔁 0 💬 0 📌 0
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...
16.02.2026 21:41 — 👍 46 🔁 14 💬 0 📌 0
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)!
08.01.2026 16:37 — 👍 45 🔁 9 💬 0 📌 0
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
26.11.2025 04:12 — 👍 3 🔁 0 💬 1 📌 0
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."
25.11.2025 22:35 — 👍 9 🔁 2 💬 0 📌 0
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.
13.08.2025 01:06 — 👍 5 🔁 2 💬 1 📌 1
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.
21.11.2025 03:25 — 👍 0 🔁 0 💬 1 📌 0
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
21.11.2025 03:25 — 👍 0 🔁 0 💬 1 📌 0
He we compared >6000 time-series metrics to index time reversibility from simulations of 35 different reversible and irreversible processes
21.11.2025 03:25 — 👍 1 🔁 0 💬 1 📌 0Quantifying time reversibility from data is important because it connects to concepts in thermodynamics (entropy production of non-equilibrium systems) & constrains the system's generative mechanisms (by ruling out linear dynamics; cf. related concepts of non-Gaussianity & nonlinearity)
21.11.2025 03:25 — 👍 2 🔁 0 💬 1 📌 0
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?_
In case anyone is interested, I've put that animation I made of brain development from 21-40 weeks GA on YouTube for your enjoyment/reference🤰👶🧠 Now you don't need to go to that other place anymore to find it 😁
youtu.be/C20GQ5CtVt0
Plus the code is now up!
github.com/StuartJO/Fet...
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Preprint site arXiv is banning computer-science reviews: here’s why www.nature.com/articles/d41...
A "methods primer" article in the journal "BMJ Medicine", titled "Factors associated with: problems of using exploratory multivariable regression to identify causal risk factors"
We wrote an article explaining why you shouldn't put several variables into a regression model and report which are statistically significant - even as exploratory research. bmjmedicine.bmj.com/content/4/1/.... How did we do?
27.10.2025 17:39 — 👍 272 🔁 108 💬 26 📌 20
Glad to share the publication of our #newpaper (aka #blueprint) :
> A Predictive Approach to Enhance Time-Series Forecasting
By Skye Gunasekaran, Assel Kembay, Hugo Ladret, Rui-Jie Zhu, myself, Omid Kavehei and Jason Eshraghian
www.nature.com/articles/s41...
#neuroscience #AI #prediction #time
Nature research paper: Arousal as a universal embedding for spatiotemporal brain dynamics
go.nature.com/4nMUgYz
random neuroimaging question: does anyone in bluesky-land have access to the loadings for neurosynth topics in schaefer 400 (yeo7) space? #neuroskyence @misicbata.bsky.social @richardfbetzel.bsky.social @borismontreal.bsky.social @sofievalk.bsky.social
26.09.2025 02:39 — 👍 10 🔁 5 💬 1 📌 0