A cellular resolution atlas of Broca's area

Genomic, molecular, and cellular divergence of the human brain

While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.

Segmentation of supragranular and infragranular layers in ultra-high resolution 7T ex vivo MRI of the human cerebral cortex

Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Leveraging recent advancements in ultra-high resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 μm, we propose a multi-resolution U-Nets framework (MUS) that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation, while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.