🎊Ain’t no party like a thesis submission party🎊

Honored to have submitted my PhD as a recipient of the Paulette Isabel Jones Career Development Award from The University of Sydney!

Thank you x1000000 to MVP supervisor @bendfulcher.bsky.social & co-supervisor @macshine.bsky.social 😊

Thank you all for the great chats about this work and the inspiring ideas for where to go next with this project!

And a big thank you to @bendfulcher.bsky.social and @macshine.bsky.social for your guidance and support throughout this project, as with all others of my PhD 😊

#OHBM2025 was a blast -- the perfect way to celebrate submitting my PhD thesis with y'all 🎉
It was an honor (and so fun!) to represent the Aussie imaging community alongside a fab panel in the LOC Symposium, sharing my final thesis work on homotopic connectivity:

www.biorxiv.org/content/10.1...

Unbiased opinion, but I’m really interested in how we can get the most bang for our info theory buck in computational neuroscience 🧠 So, we demo the implementation and interpretation of all 11 measures with an illustrative BOLD fMRI case study:

We organized 11 measures into 6 categories according to temporal dependency and the type(s) of dynamical properties each measure captures. These measures are summarized in one large ‘pocket reference’ schematic, and we then zoom in to discuss the ‘what/how/why’ of each measure individually 🔎

Info theory offers powerful measures for capturing complexity & interaction among elements of a complex system, like the brain! 🧠 Here's our new unified reference for key info-theoretic time series measures ft. 📊 visuals, ➗equations, & 💬descriptions:

arxiv.org/abs/2505.13080

🎨🧑‍🎨 Looking for a tool to visualize subcortical/thalamic data in 2D? Check out this python-based package I put together (subcortex-visualization on PyPI), plus a guide for creating your own custom atlas meshes and vector graphics! All feedback/tips welcome 😊

anniegbryant.github.io/subcortex_vi...

@christopherjwhyte.bsky.social and I introduce a novel data-driven framework to evaluate >200 connectivity-based neural correlates of consciousness! Results are used to quantitatively compare predictions from neurodynamical models tailored to theoretic predictions.

www.biorxiv.org/content/10.1...

Together with new biological insights into the brain’s overlapping structural architecture, this work introduces a generalizable method for systematically comparing overlapping community detection algorithms to an ensemble of simulated networks tailored to your particular dataset at hand:

In contrast to Louvain clustering, which doesn’t allow overlapping assignments, OSLOM can disentangle communities bridged by two key regions, with the flexibility to capture the brain as a complex system characterized by fluid distributed interactions:

These 15 nodes generally (though not always!) sit at the apex of the topographical hierarchy of the cortex quantified by the first principal gradient (PG) of functional connectivity (shoutout to Dan Margulies for sharing the data via neuromaps from Ross and Justine in @misicbata.bsky.social lab):

After pinpointing OSLOM (order statistics local optimization method) as the top-performing algorithm, we identified seven structural communities in the right cortex collectively bridged by fifteen overlapping nodes with demonstrated cross-community connectivity:

📣🎉 Excited to share work co-led with @aditijh.bsky.social, developing a data-driven selection technique for overlapping community detection algorithms, applied to the human structural connectome! 📣🎉

www.biorxiv.org/content/10.1...

📣 First three years of my PhD have culminated in this work now published at PLoS Computational Biology! 🥳 We take a deep dive into all the many ways we can slice n dice fMRI dynamics to quantify biologically relevant properties 🧠🧮

doi.org/10.1371/jour...