Oualid Benkarim

TL;DR: BrainSpace is presented, a Python/Matlab toolbox for the identification of gradients, their alignment, and their visualization, and allows for controlled association studies between gradients with other brain-level features, adjusted with respect to null models that account for spatial autocorrelation.

TL;DR: The iSeg-2017 challenge provides a set of six-month infant subjects with manual labels for training and testing the participating methods, and among the 21 automatic segmentation methods participating, the eight top-ranked teams are reviewed, in terms of Dice ratio, modified Hausdorff distance, and average surface distance.

TL;DR: A novel coordinate system of the human cortex based on an advanced model of its connectivity is proposed and the results advance the understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation.

TL;DR: A compact workflow and open-access toolbox that allows for the identification of gradients, their alignment (across subjects or modalities), and their visualization (in embedding or cortical space) and allows for controlled association studies between gradients with other brain-level features, adjusted with respect to several null models that account for spatial autocorrelation.