Biophysical basis for brain folding and misfolding patterns in ferrets and humans
- Department of Mathematics, The Chinese University of Hong Kong, China
- School of Engineering and Applied Sciences, Harvard University, United States
- Department of Cell Biology, Duke University, United States
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, United States
- Division of Genetics and Genomics, Manton Center for Orphan Disease, and Howard Hughes Medical Institute, United States
- Boston Children’s Hospital, United States
- Department of Organismic and Evolutionary Biology, Harvard University, United States
- Department of Physics, Harvard University, United States
Figures
Figure 1
Time course of ferret brain morphogenesis.
(a) Whole brain samples from ferrets of various ages show progressive development of cortical gyri and sulci. (b) Ferret brains show an increase in complexity of sulcal pattern and in sulcal depth throughout development. The rhinal sulcus (rs), cruciate sulcus (crs), coronal sulcus (cns), suprasylvian sulcus (sss), pseudosylvian sulcus (pss), lateral sulcus (ls), and ansate sulcus (as) are labeled. Schematic by G. Séjourné.
Figure 2
Physical gel model of ferret brain morphogenesis.
(a) Schematic of the gel experiment. We first produced a two-layer gel model of a ferret brain from MRI scans as previously described (Tallinen et al., 2016). We then immersed the gel model in n-hexane for 1.5 hours, which induced the outer layer to swell by absorbing the solvent over time, resulting in the development of cortical gyri and sulci. (b) The swelling experiment for the P8 ferret model, in which it can be observed that the swelling of the cortical layer produces sulcal patterns and characteristics comparable to the real ferret brain. (c) The swelling experiment for the P16 gel model. Scale bar = 1 cm. Notation guide: cruciate sulcus (crs), coronal sulcus (cns), suprasylvian sulcus (sss), rhinal sulcus (rs), pseudosylvian sulcus (pss), lateral sulcus (ls), and ansate sulcus (as).
Figure 3
Numerical model of ferret brain morphogenesis.
(a) Continuous growth simulation from P0 to adolescence. The P0 brain tetrahedral mesh was used as the input for the numerical simulation. (b) Stepwise growth simulation from P0 to P4, P4 to P8, P8 to P16, and P16 to P32. For different growth intervals, we use different brain tetrahedral meshes as the input for the numerical simulation. Different views of the input P0 brain and the simulated P16 brain are provided.
Figure 4
Comparison of cortical folding in real and simulated ferret brain models.
(a) The top row shows the increase in complexity of sulcal pattern and in sulcal depth of ferret brains from P8 to P16. The middle row shows a numerical model of a P8 brain and its deformed state mimicking progression to P16. The bottom row shows a physical gel model of P8 and its post-swelling state mimicking progression to P16 (scale bar = 1 cm). The P8 initial states have invaginations corresponding to the cruciate sulcus (crs), coronal sulcus (cns), and suprasylvian sulcus (sss), and both the numerical deformed state and the physical post-swelling state have sulci corresponding in location and self-contacting nature to the crs, cns, sss, lateral sulcus (ls), and ansate sulcus (as) observed in P16 real ferrets. (b) The real P16 brain reconstructed from MRI scans, the simulated P16 brain, and their respective landmark-aligned spherical mappings obtained by the FLASH algorithm (Choi et al., 2015), each color-coded with the shape index (Koenderink and van Doorn, 1992) of the brain.
Figure 5
Numerical and gel experiments on the P8 ferret brain with globally modified brain gyrification.
(a) The numerical and gel experimental results with a global reduction of the cortical thickness to of the original thickness. (b) The numerical and gel experimental results with a global increase in the cortical thickness to twice the original thickness. Scale bar = 1 cm.
Figure 6
Modeling malformations of cortical development (MCD) using our model.
(a) Control, (b) SCN3A, (c) ASPM, (d) TMEM161B. For each example, we show human (top) and ferret (middle) brain MRIs (images adapted from Smith et al., 2018; Johnson et al., 2018; Akula et al., 2023b). We then perform a modified numerical brain simulation on the P8 model with different tangential growth rate and cortical thickness parameters, including (a) the original growth rate and cortical thickness, (b) a reduction of the cortical thickness at a localized zone, (c) a reduction of the growth rate globally, and (d) a reduction of the growth rate and an increase of the cortical thickness globally. All numerical simulation results (bottom) qualitatively capture the cortical malformations.
© 2018 Elsevier Inc. The ferret (middle) brain MRI image in panel a is reprinted from Smith et al., 2018 with permission. It is not covered by the CC-BY 4.0 licence and further reproduction of this image would need permission from the copyright holder.
Appendix 1—figure 1
Swelling experiment for an input P4 gel brain.
Here, the two-layer PDMS model of a P4 ferret brain was immersed in n-hexane for 1.5 hours. Analogous to the gel brain experiments presented in the main text, gyrification patterns can be observed in the swollen gel brain. Scale bar = 1 cm.
Appendix 1—figure 2
Stepwise growth simulation of ferret brain.
The P0 brain and the simulated brains from P0 to P4, from P4 to P8, from P8 to P16, and from P16 to P32 are shown. For each brain, six different views are provided (not to scale).
Appendix 1—figure 3
Mesh independence for the numerical simulation.
The continuous growth simulations from P0 to adolescence using P0 brain tetrahedral meshes with 250,000 tets (first row), 1 million tets (second row), 2 million tets (third row), and 3 million tets (fourth row). It can be observed that the resulting folding patterns are highly similar.
Appendix 1—figure 4
The spherical harmonics representations of the MRI-based brain and the numerically simulated brain with different maximum order used.
Appendix 1—figure 5
Comparison between human brain surface MRI reconstructions and our ferret brain simulations for the malformations of cortical development (MCD) polymicrogyria (PMG).
(a) Surface MRI reconstructions of human MRIs performed using FreeSurfer software of control (top) and age-matched affected individual with a gain-of-function SCN3A variant resulting in PMG. Red box outlines the PMG of perisylvian and surrounding areas, where the normal gyri and sulci form microgyri/sulci, pushing together to make an appearance of “Moroccan leather”.) The numerical growth simulations on the P8 ferret brain without modification in the cortical thickness (top) and with a reduced cortical thickness to of the original thickness, i.e., (bottom). The differences are highlighted by the red boxes.
© 2018 Elsevier Inc. Images in panel a are reprinted from Smith et al., 2018 with permission. They are not covered by the CC-BY 4.0 licence and further reproduction of this panel would need permission from the copyright holder.
Appendix 1—figure 6
Numerical simulations with locally modified brain growth.
We performed numerical simulations on the P8 brain with different modifications in the tangential growth rate and the cortical layer thickness at a localized region (dotted ellipse). The results without modification (normal), with an increased growth rate to 1.5 times the original growth rate () or 2 times the original growth rate (), with a reduced cortical thickness to of the original thickness () or of the original thickness (), and with a modification in both the growth rate and the cortical thickness ( and and ) are presented.
Videos
Video 1
Time-lapse video of the swelling experiment for the P8 gel brain, where the 2-layer PDMS model was immersed in n-hexane for 1.5 hours.
Video 2
Time-lapse video of the swelling experiment for a P16 gel brain, where the two-layer PDMS model was immersed in n-hexane for 1.5 hours.
Video 3
Continuous numerical simulation of the ferret brain folding from P0 to P32.
Video 4
Stepwise numerical simulations of the ferret brain folding from P0 to P4, from P4 to P8, from P8 to P16, and from P16 to P32.
Tables
Table 1
Human genetic variants modeled in ferret developmental brain phenotypes.
| Gene | Change in geometry | Relevant brain developmental disorder |
|---|---|---|
| SCN3A (Smith et al., 2018) | Excessive number of tightly packed folds | Polymicrogyria |
| ASPM (Johnson et al., 2018) | Reduced brain size and cortical surface area | Microcephaly |
| Cdk5 (Shinmyo et al., 2017) | Reduced depth of the sulcus | Lissencephaly |
| ARHGAP11B (Kalebic et al., 2018) | Expansion in both the radial and tangential dimensions | Megalencephaly |
| TMEM161B (Akula et al., 2023b) | Reduced gyrus size and sulcal depth | Lissencephaly |
Appendix 1—table 1
Similarity between the real and simulated ferret half-brain surfaces.
| Surface | Similarity (1-norm) | Similarity (2-norm) | Similarity (∞-norm) |
|---|---|---|---|
| Real P8 and simulated P8 (left) | 0.8040 | 0.7432 | 1.0000 |
| Real P8 and simulated P8 (right) | 0.7893 | 0.7260 | 1.0000 |
| Real P16 and simulated P16 (left) | 0.8247 | 0.7632 | 1.0000 |
| Real P16 and simulated P16 (right) | 0.7980 | 0.7339 | 1.0000 |
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Biophysical basis for brain folding and misfolding patterns in ferrets and humans
eLife 14:RP107141.
https://doi.org/10.7554/eLife.107141.3
