Mechanical hierarchy in the formation and modulation of cortical folding patterns

Gyral peak variations between HCP and CHCP: functional and structural implications

Significant culture and ethnic diversity play an important role in shaping brain structure and function. Many attempts have been undertaken to connect ethnic variations with brain function, which, however, fluctuates over time and is costly, limiting its utility to identify consistent brain markers as well as its application to a broad population. In contrast, brain anatomy is less altered during a short period of time, but it is not fully understood whether it could serve as the ethnicity-sensitive landmark, or its variation is associated with functional one. In this study, We utilized gyral peaks, a set of early cortical folds, as cortical landmarks to explore the role of ethnic factors in brain anatomy and their relationship to brain function. Comparative experiments were conducted using the Human Connectome Project and the Chinese Human Connectome Project. In populations with similar ethnic backgrounds, gyral peak patterns showed greater consistency. For groups with significantly different ethnic backgrounds, we identified both shared peaks and peaks unique to each group. Compared to shared peaks, unique peaks showed significant differences in anatomical and functional network attributes and were spatially associated with working memory networks, which exhibited increased activation in their presence. Gene enrichment analysis provided additional support, suggesting that the unique peaks are associated with genes linked to working memory functions. These findings could provide new knowledge to understanding how ethnic diversity interplay with brain functions and associate with brain shapes.

Genetic and neurochemical profiles underlying cortical morphometric vulnerability to Parkinson's disease

BACKGROUND

Increasing evidence has documented cortical involvement at all stages of PD. The local vulnerabilities within certain brain regions in PD have been previously demonstrated, whereas its underlying genetic and neurochemical factors remain unclear. This study aims to investigate the spatial spectrum of cortical atrophy in Parkinson's disease (PD) and link these variances in gray matter properties and curvature respectively to putative molecular pathways and neurotransmitter factors.

METHODS

We recruited 141 clinically diagnosed PD patients and 70 healthy controls. Cortical morphological abnormalities of PD were obtained by intergroup comparisons in gray matter properties metrics and curvature measurements. Then we performed gene-category enrichment and spatial correlation analyses to evaluate the specific correspondence between cortical alteration in PD and genetic expression from the Allen Human Brain Atlas and normative neurotransmitter atlases from Neuromaps.

RESULTS

We found decreased gray matter properties in temporal, somatomotor, cingulate and occipital cortices, decreased curvature measures in occipital, temporal and orbitofrontal cortices, and increased curvature measures in somatomotor, prefrontal and posterior parietal cortices for PD patients. The related genes were enriched for the glucose metabolism, mitochondrial function, and post-translational histone modifications processes. In addition, the serotonin and norepinephrine transporter devoted more to gray matter properties alterations while the dopamine, gamma-aminobutyric acid receptors, and norepinephrine transporter were strong contributors of curvature abnormalities in PD.

CONCLUSIONS

Collectively, the present study offered interpretation of cortical morphological alterations and the cortical pathogenic theory in PD from genetic and neurochemical perspectives, which inspire further research on new pharmacotherapeutic approaches.

Stress landscape of folding brain serves as a map for axonal pathfinding

Understanding the mechanics linking cortical folding and brain connectivity is crucial for both healthy and abnormal brain development. Despite the importance of this relationship, existing models fail to explain how growing axon bundles navigate the stress field within a folding brain or how this bidirectional and dynamic interaction shapes the resulting surface morphologies and connectivity patterns. Here, we propose the concept of "axon reorientation" and formulate a mechanical model to uncover the dynamic multiscale mechanics of the linkages between cortical folding and connectivity development. Simulations incorporating axon bundle reorientation and stress-induced growth reveal potential mechanical mechanisms that lead to higher axon bundle density in gyri (ridges) compared to sulci (valleys). In particular, the connectivity patterning resulting from cortical folding exhibits a strong dependence on the growth rate and mechanical properties of the navigating axon bundles. Model predictions are supported by in vivo diffusion tensor imaging of the human brain.

Role of data-driven regional growth model in shaping brain folding patterns

The surface morphology of the developing mammalian brain is crucial for understanding brain function and dysfunction. Computational modeling offers valuable insights into the underlying mechanisms for early brain folding. Recent findings indicate significant regional variations in brain tissue growth, while the role of these variations in cortical development remains unclear. In this study, we explored how regional cortical growth affects brain folding patterns using computational simulation. We first developed growth models for typical cortical regions using machine learning (ML)-assisted symbolic regression, based on longitudinal real surface expansion and cortical thickness data from prenatal and infant brains derived from over 1000 MRI scans of 735 pediatric subjects with ages ranging from 29 postmenstrual weeks to 2 years of age. These models were subsequently integrated into computational software to simulate cortical development with anatomically realistic geometric models. We comprehensively quantified the resulting folding patterns using multiple metrics such as mean curvature, sulcal depth, and gyrification index. Our results demonstrate that regional growth models generate complex brain folding patterns that more closely match actual brains structures, both quantitatively and qualitatively, compared to conventional uniform growth models. Growth magnitude plays a dominant role in shaping folding patterns, while growth trajectory has a minor influence. Moreover, multi-region models better capture the intricacies of brain folding than single-region models. Our results underscore the necessity and importance of incorporating regional growth heterogeneity into brain folding simulations, which could enhance early diagnosis and treatment of cortical malformations and neurodevelopmental disorders such as cerebral palsy and autism.

A theoretical framework for predicting the heterogeneous stiffness map of brain white matter tissue

Finding the stiffness map of biological tissues is of great importance in evaluating their healthy or pathological conditions. However, due to the heterogeneity and anisotropy of biological fibrous tissues, this task presents challenges and significant uncertainty when characterized only by single-mode loading experiments. In this study, we propose a new theoretical framework to map the stiffness landscape of fibrous tissues, specifically focusing on brain white matter tissue. Initially, a finite element (FE) model of the fibrous tissue was subjected to six loading cases, and their corresponding stress-strain curves were characterized. By employing multiobjective optimization, the material constants of an equivalent anisotropic material model were inversely extracted to best fit all six loading modes simultaneously. Subsequently, large-scale FE simulations were conducted, incorporating various fiber volume fractions and orientations, to train a convolutional neural network capable of predicting the equivalent anisotropic material properties solely based on the fibrous architecture of any given tissue. The proposed method, leveraging brain fiber tractography, was applied to a localized volume of white matter, demonstrating its effectiveness in precisely mapping the anisotropic behavior of fibrous tissue. In the long-term, the proposed method may find applications in traumatic brain injury, brain folding studies, and neurodegenerative diseases, where accurately capturing the material behavior of the tissue is crucial for simulations and experiments.

Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.

Axonal tension contributes to consistent fold placement

Cortical folding is a critical process during brain development, resulting in morphologies that are both consistent and distinct between individuals and species. While earlier studies have highlighted important aspects of cortical folding, most existing computational models, based on the differential growth theory, fall short of explaining why folds tend to appear in particular locations. The axon tension hypothesis may provide insight into this conundrum; however, there has been significant controversy about a potential role of axonal tension during the gyrification. The common opinion in the field is that axonal tension is inadequate to drive gyrification, but we currently run the risk of discarding this hypothesis without comprehensively studying the role of axonal tension. Here we propose a novel bi-layered finite element model incorporating the two theories, including characteristic axonal tension in the subcortex and differential cortical growth. We show that axon tension can serve as a perturbation sufficient to trigger buckling in simulations; similarly to other types of perturbations, the natural stability behavior of the system tends to determine some characteristics of the folding morphology (e.g. the wavelength) while the perturbation determines the location of folds. Certain geometries, however, can interact or compete with the natural stability of the system to change the wavelength. When multiple perturbations are present, they similarly compete with each other. We found that an axon bundle of reasonable size will overpower up to a 5% thickness perturbation (typical in the literature) and determine fold placement. Finally, when multiple axon tracts are present, even a slight difference in axon stiffness, representing the heterogeneity of axonal connections, is enough to significantly change the folding pattern. While the simulations presented here are a very simple representation of white matter connectivity, our findings point to urgent future research on the role of axon connectivity in cortical folding.

Potential of focal cortical dysplasia in migraine pathogenesis

Focal cortical dysplasias are abnormalities of the cerebral cortex associated with an elevated risk of neurological disturbances. Cortical spreading depolarization/depression is a correlate of migraine aura/headache and a trigger of migraine pain mechanisms. However, cortical spreading depolarization/depression is associated with cortical structural changes, which can be classified as transient focal cortical dysplasias. Migraine is reported to be associated with changes in various brain structures, including malformations and lesions in the cortex. Such malformations may be related to focal cortical dysplasias, which may play a role in migraine pathogenesis. Results obtained so far suggest that focal cortical dysplasias may belong to the causes and consequences of migraine. Certain focal cortical dysplasias may lower the threshold of cortical excitability and facilitate the action of migraine triggers. Migraine prevalence in epileptic patients is higher than in the general population, and focal cortical dysplasias are an established element of epilepsy pathogenesis. In this narrative/hypothesis review, we present mainly information on cortical structural changes in migraine, but studies on structural alterations in deep white matter and other brain regions are also presented. We develop the hypothesis that focal cortical dysplasias may be causally associated with migraine and link pathogeneses of migraine and epilepsy.