RT @zach_ladwig: Hi! Excited to announce that the major work from my PhD is out now on biorxiv!.(w. coauthors @kianzkermani , @allydworetsk….

RT @RodBraga: 🚨 New Preprint 🚨. Targeting intracranial electrical stimulation (ES) to network regions defined within individuals causes net….

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RT @bttyeo: 1/11 Excited to share our @Naturestudy led by @Leon_Oo1 @csabaorban @ZShaoshi. It is well-known that A….

@bttyeo @andreashorn_ 12/12 . I’d like to thank my amazing mentors, @GrattonCaterina & @Campbell_TheLab, my coauthors at WashU: @allydworetsky, Sarah Grossen, Emma Carr, & Dr. Abdulmunaim Eid, as well as the participants who made this work possible. Please let us know if you have any feedback! 🎆.

@bttyeo @andreashorn_ 11/12 . 🧠 Bottom line: Precision RSFC is feasible, reliable, and clinically promising in Parkinson’s disease. This approach could explain the huge variation we see across individuals—and help us treat each person more effectively.

@bttyeo @andreashorn_ 10/12 . These differences aren’t noise—they’re real, reliable, and potentially clinically relevant. 🚀 Implications? .✔️ Understand heterogeneity in progression/symptoms ✔️ Map functional changes before symptoms appear ✔️ Improve DBS targeting .✔️ Personalized interventions.

@bttyeo @andreashorn_ 9/12 . 🗺️ Finding 4: Individual Network Maps .Using seed-based + data-driven techniques (Infomap), we mapped networks in 2 PD participants. Despite the same diagnosis, locations in primary motor cortex can vary in connectivity → One showed SCAN; one somatomotor-face network.

@bttyeo @andreashorn_ 8/12 . 🧮 Finding 3: .Stability & Distinction We tested whether RSFC patterns hold up across days. With 25 mins/session: . 🧠 Within-subject similarity: r = 0.70 .🧠 Across-subject similarity: r = 0.32 . PD participants showed stable, person-specific network profiles.

@bttyeo @andreashorn_ 7/12 . 📈 Finding 2: Reliability With conventional 5 mins of data, reliability was modest (r = 0.49 in subcortex). With 40 mins? .🧠 Cortical: r ≈ 0.90 .🧠 Subcortical: r ≈ 0.81 .🧠 Cerebellar: r ≈ 0.87 .That's a massive boost—critical for clinical applications!

@bttyeo @andreashorn_ 6/12 .📊 Finding 1: Feasibility . Even with stringent motion thresholds (fFD < 0.1 mm), PD participants provided comparable data to controls. ✅ 91.5% of data retained .✅ Motion manageable despite PD symptoms

@bttyeo @andreashorn_ 5/12 . We tested this! .🧪 20 people with PD (OFF medications!), 6 healthy controls .🕒 >100 mins of RSFC per person .📍 Multiple (4-5) sessions . All with the goal: can we reliably map functional brain networks in PD?.

@bttyeo @andreashorn_ 4/12 . That’s where precision RSFC comes in: .✅ 100+ mins of data .✅ Advanced motion correction .✅ Individualized network mapping . It’s been used in healthy people— but can it work in individuals with PD with tremor, fatigue, or increased head motion? 🤔

3/12 . RSFC has identified brain-behavior relationships in healthy adults (see work by @bttyeo) and those with PD (see @andreashorn_), but most studies fail to reliably detect individual differences— offering little insight into clinical heterogeneity.

2/12 . Parkinson’s disease (PD) isn’t just a movement disorder. It affects mood, cognition & more. Complicating matters further, there is huge variability in what, when, and how severe symptoms present. Why symptoms vary so much across individuals with PD is unclear. 🧩.

Excited to share my first preprint investigating the feasibility and reliability of using precision RSFC in people with Parkinson’s disease! 🧠👇 .📄: .🧵 Thread ⬇️ 1/12

RT @TrendsCognSci: Using precision approaches to improve brain-behavior prediction. Review by Hyejin J. Lee (@hyejinjadelee), Ally Dworetsk….