bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.10.08.757624

Grow2Fold: mapping heterogeneous developmental growth to human brain folding

Abstract

Cortical folding emerges through complex developmental processes, yet what organizes these processes into the characteristic folding patterns of the human brain remains unclear. Here, we developed an imaging-informed whole-brain modeling framework, Grow2Fold, that integrates developmental cortical regionalization, quantitative growth characterization, and mechanics-guided simulation to investigate how cortical growth shapes brain folding patterns. Using 836 fetal and neonatal MRI sessions from 747 participants spanning 21-45 postmenstrual weeks, we identified a reproducible and hierarchical spatiotemporal organization of cortical expansion characterized by coordinated regional growth trajectories. Rapid expansion occurs earlier around peri-central territories and progressively shifts toward frontal, parietal, and temporal association cortices. We encoded these imaging-derived trajectories into region- and age-specific growth laws and incorporated them into anatomically realistic whole-brain mechanical models. The resulting simulations recapitulate major sulcal landmarks and characteristic folding development across global and regional morphological measures. Comparing regional and uniform growth, we find that differential growth drives cortical instability, while heterogeneous developmental growth organizes this instability into anatomically recognizable folding patterns. Combined with subject-specific anatomy, these population-informed growth laws reproduce individualized longitudinal folding trajectories. Together, our results identify spatiotemporally patterned developmental growth as a key spatial constraint on cortical morphogenesis and establish a quantitative bridge from developmental imaging, through mechanical instability, to anatomically organized folding.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hou, J., Solhtalab, A., Jiang, K., Gu, B., Li, T., Chen, X., Wu, T., Song, K., Liu, Y., Song, W., zhu, D., Liu, T., Kuhl, E., Li, G., Razavi, M. J., Wang, X.. 2026-10-09. Grow2Fold: mapping heterogeneous developmental growth to human brain folding. https://doi.org/10.64898/2026.10.08.757624

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cancers relax selection on charge at the mitochondrial complex I quinone cavity

Mitochondrial complex I translocates protons through hydrated channels whose connectivity and electrostatics are both defined by structure, but whether they are distinctly constrained is unknown. From a 2.39 cryo-EM structure modelling 2,945 ordered waters, we built the proton wire of the seven mtDNA-encoded ND subunits and scored all 40,166 missense substitutions on two near-orthogonal axes (r = 0.17): electrostatic shift at proton-loading sites, and topological disruption of the wire. Across 858 germline variant sites, loading sites (0.51) and cut vertices (0.67) are both depleted. In tumours only loading sites are enriched (1.42 TCGA, 1.67 PCAWG, 1.29 MSK-IMPACT), a 3.06-fold difference tested as a wire class tissue-type interaction (P = 3.6 10-). It survives adjustment for conservation, burial and coverage, and is concentrated in ND1 within 15 of the quinone cavity, not spread along the proton path. Selection separates charge from connectivity, without establishing a fitness benefit.

biophysics↗

Rugnux: from diffraction images to structure at synchrotrons and XFELs in one program

Rising data rates in macromolecular crystallography outpace multi-program pipelines on computing clusters. Rugnux, a single GPU-accelerated program, turns rotation or serial still diffraction images into merged data and an initial structure. At synchrotrons, results arrive seconds after the last image; on one workstation, 207 public datasets from 36 sources took a median of 15 s each, with deposition-quality. Serial XFEL data were processed faster than the collection rate, enabling real-time structure determination.

biophysics↗

Phase Separation of Intracellular Proteins Influences Synaptic Bistability

Synaptic bistability at the post synaptic density has been proposed to be the result of the nucleation and evaporation of receptor clusters. The exact biophysical mechanism underlying these inter-receptor attractions that can trigger nucleation remains to be elucidated. Emerging evidence demonstrates that numerous postsynaptic density submembrane proteins, that interact with various membrane receptors, can undergo phase separation, necessitating a revised conceptual model. By employing Langevin dynamics simulations of coarse-grained scaffold proteins and interacting membrane receptors, we study how phase transitions of scaffold proteins alter receptor clustering at the membrane. In our model, scaffold macromolecules can undergo phase separation and interact with receptor molecules at the model membranes. We observed that the presence of scaffold polymers across the membrane creates an attractive interaction between otherwise purely repulsive receptors. By systematically varying the number of receptors at the membrane, we dissected the coupling between receptor clustering and the phase behavior of scaffold macromolecules. We show that the propensity for receptor clustering is enhanced by the condensation of scaffold proteins. We then used two different scaffolds and systematically varied the interaction between them, to change the spatial organization of two condensed phases w.r.t. one another. Interestingly, we observed that receptor clustering can be reduced by co-phase separation of scaffold macromolecules, indicating the role of competing interactions in receptor clustering. Our work advances understanding of receptor-mediated signaling and phase separation, providing insights into cellular compartmentalization and biochemical regulation at the synapse.

biophysics↗