Jake Chernicky

1/11 Excited to share our @Naturestudy led by @leonooi.bsky.social @csabaorban.bsky.social @shaoshiz.bsky.social

AI performance is known to scale with logarithm of sample size (Kaplan 2020), but in many domains, sample size can be # participants or # measurements...

doi.org/10.1038/s415...

1000s of studies have been published mapping neuroanatomical changes in psychiatric disorders. Can we ever converge on robust disease phenotypes? Our latest PP led by Trang Cao in a huge collab effort investigates this question...

@nsb-lab.bsky.social

12/12

I’d like to thank my amazing mentors, @caterinagratton.bsky.social & @campbell-thelab.bsky.social, my coauthors at WashU: @allydworetsky.bsky.social, Sarah Grossen, Emma Carr, @ameid.bsky.social and the participants who made this work possible.

Please let us know if you have any feedback! 🎆

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.

10/12

These differences aren’t noise—they’re real, reliable, and potentially clinically meaningful.

🚀 Implications?
✔️ Understand heterogeneity in progression/symptoms
✔️ Map functional changes before symptoms appear
✔️ Improve DBS targeting
✔️ Develop personalized interventions

9/12

🗺️ Finding 4: Individual Network Maps
Using seed-based + data-driven techniques (Infomap), we mapped networks in two individuals with PD.

Despite the same diagnosis, locations in primary motor cortex can have very different connectivity
→ One showed SCAN; one showed somatomotor-face network.

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.

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!

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

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?

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.bsky.social) and those with PD (see @andreashorn.org‬), 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’s a complex condition affecting mood, cognition & more.

Complicating matters further, there is a 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! 🧠👇
📄: go.illinois.edu/PDfeasibility

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