A Bimodal Taxonomy of Adult Human Brain Sulcal Morphology Related to Timing of Fetal Sulcation and Trans-Sulcal Gene Expression Gradients

Neurology Biochemistry Genetics Medical Imaging Life Sciences Medicine Cell Biology
brain sulci sulcal morphology fetal development gene expression morphology

Bimodal Classification of Adult Brain Sulcal Morphology Research Background and Objectives

This study focuses on the complex morphological features of the adult cerebral cortex sulci, specifically the classification of linear and complex morphologies of brain sulci and their developmental mechanisms. The sulci are groove structures on the surface of the cerebral cortex, corresponding to different genetic traits, functional areas, and sulcal development timings during the fetal period. Our research team attempts to explore the classification features of brain sulcal structures and their relationship with gene expression gradients through automated data analysis. The significance of this study lies in: although there is great individual variability in brain surface structures, their formation process may follow certain rules. This study aims to provide a quantitative classification system for sulcal morphology, reveal the developmental origins of sulcal complexity, and offer new perspectives for future research on neurodevelopment and diseases.

Source and Authors of the Study

This research was completed by William E. Snyder and his team and published in the October 2024 issue of the journal “Neuron.” The research team comes from several renowned research institutions, including the University of Cambridge, the National Institute of Mental Health in the United States, King’s College London, and Paris-Saclay University. By bringing together researchers from different disciplines, the team conducted interdisciplinary in-depth discussions combining genetics, data science, and imaging technologies.

Research Methods and Process

The study utilizes a new computational pipeline to analyze the morphological features of 40 sulci in the adult cerebral cortex using brain MRI data to establish a “sulcal phenotype network” (SPN). The research follows several key steps:

  1. Sample Collection and Data Processing: The research is based on MRI scans provided by the UK Biobank, covering 34,725 adult participants aged 45-82. All data were subjected to quality screening to ensure completeness and consistency.

  2. Sulcal Phenotype Measurement: In each MRI sample, 40 sulci were segmented and labeled. Five morphological indicators were extracted, including sulcal depth, depth variability, longest branch length, branch span, and fractal dimension (FD). These features were measured from both the radial (perpendicular to the sulcus) and tangential (along the external surface of the sulcus) directions to comprehensively characterize sulcal geometry.

  3. Sulcal Classification and Clustering Analysis: By calculating the Pearson correlation coefficient matrix between sulcal phenotypic features of 40 sulci, the research team constructed the SPN and performed hierarchical clustering analysis on the network. The clustering results revealed two major types of sulcal morphology: one is the linear type, which is deeper with simple branching and higher heritability, mainly located in unimodal cortex; the other is the complex type, which is shallower with diverse branching and lower heritability, primarily located in heteromodal cortex.

  4. Associative Analysis of Fetal Sulcal Development and Adult Morphology: The study further analyzed fetal brain MRI data (gestational weeks 21-36) to track curvature development curves of each sulcus. It was found that the time of sulcul formation during the fetal period is closely related to the linear or complex morphology of adult sulci. Linear sulci generally form early in the fetal period, whereas complex sulci form late. Correlation analysis showed a significant positive correlation between fetal sulcal formation timing and adult sulcal complexity.

  5. Gene Expression Gradient Analysis: Using high-resolution gene expression maps, the study validated the biological hypothesis of sulcal formation, namely that linear sulci form in regions of sharp gene expression changes. The research team found significant changes in gene expression gradients on both sides of the sulcus, particularly around the central sulcus and parieto-occipital sulcus, which are closely associated with the development of inhibitory neurons and microglia, further supporting the hypothesis of the genetic regulation mechanism of sulcal morphology.

Main Research Findings

The main findings of this study include:

  1. Bimodal Classification of Sulci: The research proposes a bimodal classification system for sulcal morphology based on morphological features, dividing adult brain sulci into two categories: linear and complex morphologies. This classification system not only reveals the diversity of sulcal morphological features but is also closely related to the genetic characteristics and functional differences of different cortical regions. Linear sulci mostly occur in central cortical regions with high heritability, while complex sulci are concentrated in peripheral cortical regions with lower heritability.

  2. Association between Sulcal Morphology and Fetal Development Timing: The complexity of sulcal structures is closely related to their formation timing during the fetal period. Sulci that form early exhibit simpler structures in adulthood, whereas those that form later exhibit diversified branching structures, indicating that the formation of sulcal morphology is influenced by fetal development timing.

  3. Relationship between Gene Expression Gradients and Sulcal Formation: Linear sulci tend to locate in areas with high gene expression gradient changes, especially at functional area boundaries, supporting the hypothesis of genetic regulation in sulcal formation. This finding provides a molecular-level explanation for the developmental mechanisms of sulcal structures.

  4. New Computational Pipeline and Data Resources: The automated analysis pipeline developed in this study has been publicly released, including the computational process of 5 sulcal morphological indicators, SPN construction methods, and analysis tools. The research team hopes these resources will provide standardized reference data for future neuroscience research and facilitate further exploration of the relationship between sulcal morphology and gene expression.

Significance and Application Value of the Research

This research, by establishing the sulcal phenotype network, proposes a bimodal sulcal morphology classification method and reveals a deep relationship between adult brain sulcal morphology and fetal development as well as gene expression. The scientific significance lies in several aspects:

  1. Providing Theoretical Basis for Sulcal Development and Individual Differences: Through quantitative analysis, the study reveals the dual classification of sulcal structures, providing empirical evidence for the regularity of sulcal development and a new interpretation for individual differences in sulcal morphology.

  2. Revealing Association between Sulcal Morphology and Function: Research results suggest that linear sulci are more likely associated with unimodal cortical functions, whereas complex sulci are related to cross-modal association areas. This offers a new perspective for understanding the relationship between sulcal structure, cognitive function, and mental disorders.

  3. Providing Tool Support for Future Disease Research: The relationship between sulcal morphology, development timing, and gene expression, particularly its potential application in mental and neurodevelopmental disorders, offers possible research directions for understanding the mechanisms of these diseases and potential therapeutic targets.

Research Highlights

  • New Classification System: The bimodal classification system for sulcal morphology proposed in this study fills the gap in quantitative classification of sulcal morphology.
  • Verification of Gene Expression Gradient: The study validates the biological hypothesis of sulcal structures through gene expression gradient analysis, highlighting the effects of genetic regulation on sulcal morphology.
  • Release of Automated Analysis Tools: The automatic computational pipeline provided by this research offers reusable tool support for future large-scale brain imaging data analysis.

Conclusion

This study not only proposes a new method for sulcal morphology classification but also reveals the formation mechanisms of brain sulcal morphology through verification of fetal development and gene expression gradients. The data resources and computational tools provided by the research team can promote basic research in neuroscience and have potential application value. The research holds significant importance in brain anatomy, developmental neuroscience, gene regulation, and neurodisease studies and lays the foundation for standardized research on sulcal morphology in the future.