Identifying spatiotemporal changes in cortical neurodevelopment using post-mortem and in vivo data
Poster No:
1289
Submission Type:
Abstract Submission
Authors:
Thanos Tsigaras1, Juergen Dukart1, Simon Eickhoff1, Casey Paquola1
Institutions:
1INM-7, Forschungszentrum Jülich, Jülich, North Rhine Westphalia
First Author:
Co-Author(s):
Introduction:
Despite numerous attempts to model human cortical neurodevelopment, we lack details on spatiotemporal changes occurring within the cortex. Here, we leverage the complementarity of post-mortem and in vivo approaches to track cortical microstructure throughout early development.
Methods:
We assessed age-related changes in cortical cytoarchitecture using photomicrographs of cresyl-stained post-mortem human brain tissue (254 cortical patches from 29 Von Economo areas; 0, 1, 3, 15, 24 and 48 months; 6-7 brains per age)1-6. We identified the contours of individual cells using a tailored segmentation algorithm7 and used a sliding-window approach to extract the number of cells per window and the percentage of area covered by cells in each window (Fig. 1A). Measurements were averaged across matching depths (Fig. 1B). To examine temporal changes of the cytoarchitectural features, we calculated the product-moment correlation coefficients (r) between age and cytoarchitecture for each area and depth.
We characterised cortical microstructure in vivo using T1w/T2w images from the developing Human Connectome Project (dHCP, n=328, 37-44 weeks post-menstrual age)8. We sampled T1w/T2w intensities at 14 intracortical depths9, producing microstructure profiles at each vertex (Fig. 2A). Given these profiles are inherently smoother than the histological profiles, we synopsised their shape using central moments (CMs; mean, centre of gravity, standard deviation). We assessed the influence of age on microstructure via area-specific product-moment correlations with the CMs.
To test whether the CMs can be explained by depth-specific cytoarchitecture changes, we linearly modelled their relationships. Post hoc univariate tests were performed to better interpret how depth-specific changes in cytoarchitecture contribute to in vivo changes in microstructure.
We characterised cortical microstructure in vivo using T1w/T2w images from the developing Human Connectome Project (dHCP, n=328, 37-44 weeks post-menstrual age)8. We sampled T1w/T2w intensities at 14 intracortical depths9, producing microstructure profiles at each vertex (Fig. 2A). Given these profiles are inherently smoother than the histological profiles, we synopsised their shape using central moments (CMs; mean, centre of gravity, standard deviation). We assessed the influence of age on microstructure via area-specific product-moment correlations with the CMs.
To test whether the CMs can be explained by depth-specific cytoarchitecture changes, we linearly modelled their relationships. Post hoc univariate tests were performed to better interpret how depth-specific changes in cytoarchitecture contribute to in vivo changes in microstructure.
Results:
Number of cells per window decreases with age at all cortical depths in most brain areas, though the magnitude of the effect varied (Fig. 1C). In contrast, the area covered by cells increased or decreased with age depending on cortical depth. Age-related increases were prominent deeper in the cortex, whereas decreases were widespread in superficial cortex. This depth-wise shift was most prominent in association cortex, including prefrontal cortex and temporo-parietal areas that neighbour the occipital lobe.
We observed significant global increases in mean intensity of MRI-derived profiles, but region-specific changes in the balance of microstructure across cortical depths (Fig. 2B). Specifically, the centre of gravity increased in areas on the inferior surface of the cortex, suggestive of microstructural increases deeper in the cortex. In contrast, the standard deviation of the profiles decreased with age in the frontal and temporal lobes, signifying increasingly balanced microstructural density across cortical depths.
Multivariate regressions showed more than 60% of variance in CM changes could be explained by depth-specific changes in cytoarchitecture. Effects were more prominent in mid-cortical depths, pointing towards a depth-specific correlation between cytoarchitecture and MRI-derived microstructure.
We observed significant global increases in mean intensity of MRI-derived profiles, but region-specific changes in the balance of microstructure across cortical depths (Fig. 2B). Specifically, the centre of gravity increased in areas on the inferior surface of the cortex, suggestive of microstructural increases deeper in the cortex. In contrast, the standard deviation of the profiles decreased with age in the frontal and temporal lobes, signifying increasingly balanced microstructural density across cortical depths.
Multivariate regressions showed more than 60% of variance in CM changes could be explained by depth-specific changes in cytoarchitecture. Effects were more prominent in mid-cortical depths, pointing towards a depth-specific correlation between cytoarchitecture and MRI-derived microstructure.
Conclusions:
Our study provides novel insights into the cellular basis of intracortical development. We found evidence for selective decreases in cellular density, as well as increases in cell size. Furthermore, by demonstrating the statistical relationship between histology- and MRI-derived changes, our work provides the foundation for further investigations into the multi-scale nature of cortical development, involving microstructure, morphology and connectivity.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Cyto- and Myeloarchitecture 2
Keywords:
Development
STRUCTURAL MRI
Other - Post-mortem histology
1|2Indicates the priority used for review
Provide references using author date format
2. Conel J. L. (1942). The postnatal development of the human cerebral cortex. The cortex of the one-month infant: Vol. II. Harvard University Press.
3. Conel J. L. (1947). The postnatal development of the human cerebral cortex. The cortex of the three-month infant: Vol. III. Harvard University Press.
4. Conel J. L. (1955). The postnatal development of the human cerebral cortex. The cortex of the fifteen-month infant: Vol. V. Harvard University Press.
5. Conel J. L. (1959). The postnatal development of the human cerebral cortex. The cortex of the twenty-four-month infant: Vol. VI. Harvard University Press.
6. Conel J. L. (1963). The postnatal development of the human cerebral cortex. The cortex of the four-year child: Vol. VII. Harvard University Press.
7. Upschulte, E., Harmeling, S., Amunts, K., & Dickscheid, T. (2022). Contour proposal networks for biomedical instance segmentation. Medical Image Analysis, 77, 102371. https://doi.org/10.1016/j.media.2022.102371
8. Makropoulos, A., Robinson, E. C., Schuh, A., Wright, R., Fitzgibbon, S., Bozek, J., Counsell, S. J., Steinweg, J., Vecchiato, K., Passerat-Palmbach, J., Lenz, G., Mortari, F., Tenev, T., Duff, E. P., Bastiani, M., Cordero-Grande, L., Hughes, E., Tusor, N., Tournier, J.-D., … Rueckert, D. (2018). The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction. NeuroImage, 173, 88–112. https://doi.org/10.1016/j.neuroimage.2018.01.054
9. Paquola, C., Vos De Wael, R., Wagstyl, K., Bethlehem, R. A. I., Hong, S.-J., Seidlitz, J., Bullmore, E. T., Evans, A. C., Misic, B., Margulies, D. S., Smallwood, J., & Bernhardt, B. C. (2019). Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLOS Biology, 17(5), e3000284. https://doi.org/10.1371/journal.pbio.3000284
10. Scholtens, L. H., de Reus, M. A., & van den Heuvel, M. P. (2015). Linking contemporary high resolution magnetic resonance imaging to the von economo legacy: A study on the comparison of MRI cortical thickness and histological measurements of cortical structure. Human Brain Mapping, 36(8), 3038–3046. https://doi.org/10.1002/hbm.22826