Annie G. Bryant
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anniegbryant.bsky.social
Annie G. Bryant
@anniegbryant.bsky.social
Postdoc in the Adaptive Dynamical Systems group led by @macshine.bsky.social at The University of Sydney 🧠
I'm probs either biking, hammocking, and/or caffeinating rn ☀️🌻
Thank you 😊 That’s a brilliant idea, I’ll be in touch!
January 30, 2026 at 1:30 AM
So kind, thank you Valerie! 😊
January 30, 2026 at 1:26 AM
Thank you for taking the time to check this out, and for sharing your inspiring work for the community to benefit from and build upon! 😊
January 28, 2026 at 12:25 AM
Have I missed your favorite subcortical/cerebellar/brainstem atlas?? 🥲
Feel free to create an issue suggesting one, or create your own vectorized map (& hopefully share with other researchers via repo PR 🙏) following the guide in the preprint + project website!
Repo: github.com/anniegbryant...
January 27, 2026 at 3:13 AM
These plots can be readily integrated with cortical surface visualizations created using the fantastic ggseg package (github.com/ggseg/ggseg) led by @drmowinckels.io, as shown here with a GABAA-a1 PET map from Hansen et al. 2026: doi.org/10.1007/s004...
January 27, 2026 at 3:10 AM
Live your best data viz life below the cortical surface, with pre-vectorized atlases ready to apply to subcortical/cerebellar stats from neuroimaging, transcriptomics, cytoarchitecture, etc 💅 demo'ed here on neurotransmitter PET receptor maps from Justine Hansen & co in @misicbata.bsky.social group
January 27, 2026 at 3:07 AM
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 😊
June 29, 2025 at 3:21 AM
Big shout-out to @jlizier.bsky.social, whose patience, dedication, and guidance in supervising me through this project have been invaluable 🙏 Thank you also to our other fab co-authors for their insightful input as always: Oliver Cliff, @macshine.bsky.social, and @bendfulcher.bsky.social!
May 20, 2025 at 3:29 AM
I learned so much through working on this piece! My goal with this is to share a beginner-friendly and intuitive guide for all my fellow visual learners out there, that also doesn’t shy away from the maths and important nitty-gritty details 😊
May 20, 2025 at 3:28 AM
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:
May 20, 2025 at 3:28 AM
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 🔎
May 20, 2025 at 3:27 AM