9️⃣ Sensitivity analysis
• Cross-dataset replication: HCP and MSC showed highly similar individualized topographies and FOCA matrices.
• GSR stability: FOCA was consistent with/without GSR in adults and neonates.
• Scan duration: Matching adult scans to neonatal length had minimal impact.(12/12)

8️⃣ FOCA vs. conventional FC
FOCA provides a much more robust view of negative coupling.
It is far more stable to GSR, captures greater inter-individual variability, shows stronger neonate–adult developmental effects, and predicts brain age markedly better than conventional FC.(11/12)

7️⃣ Neonatal functional topography matters
The spatial alignment of functional topography encodes brain development at birth and predicts neurodevelopmental outcomes at 18 months.(10/12)

6️⃣ Why neonatal organization looks “adult-inverted”
Negative topographies show the largest developmental shifts: DAN’s strongest negative couplings move from motor cortex (neonates) to TPJ/precuneus (adults), while positive patterns stay stable. The visual network shows similar changes.(9/12)

5️⃣ Neonatal organization is "adult-inverted"
Higher-order networks show strong positive coupling, and the visual system couples positively with the DMN rather than with somatomotor regions—the reverse of the adult patterns. (8/12)

4️⃣ Hierarchical organization
FOCA revealed a clear architecture:
• Primary systems → mainly positive coupling
• Higher-order systems → mainly negative coupling
These patterns are strongly predicted by aerobic glycolysis. (7/12)

3️⃣ FOCA matrix
We quantified these relations via spatial correlations between individualized network topographies(defined as FOCA).
The resulting FOCA matrix showed high cross-subject consistency and strong within-subject stability. (6/12)

2️⃣ Positive vs. negative topographic pairs
Visual inspection revealed widespread coupling patterns:
• Positive (convergent): FP ↔ DAN
• Negative (divergent): Default-Anterolateral ↔ CO/Action-mode (5/12)

1️⃣ Individualized spatial topography
We generated whole-brain spatial topographies for 20 functional networks—including the recently proposed action-mode and somato-cognitive-action networks.(4/12)

🚨 New preprint out!

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

We introduce a framework that maps convergent (positive) and divergent (negative) spatial topographies of individualized brain networks—and reveals how these network interactions invert in newborns and reorganize across development.

Thread 🧵 ⬇️

5️⃣ Neonatal organization is "adult-inverted"
Higher-order networks show strong positive coupling, and the visual system couples positively with the DMN rather than with somatomotor regions—the reverse of the adult patterns. (8/12)

3️⃣ FOCA matrix
We quantified these relations via spatial correlations between individualized network topographies(defined as FOCA).
The resulting FOCA matrix showed high cross-subject consistency and strong within-subject stability. (6/12)

1️⃣ Individualized spatial topography
We generated whole-brain spatial topographies for 20 functional networks—including the recently proposed action-mode and somato-cognitive-action networks.(4/12)