Anatomy-Guided Dense Individualized and Common Connectivity-Based Cortical Landmarks (A-DICCCOL)
Establishment of structural and useful correspondences of human brain that can be quantitatively encoded and reproduced across different subjects and populations is one in every of the key problems in brain mapping. As an try to handle this challenge, our recently developed Dense Individualized and Common Connectivity-based mostly Cortical Landmarks (DICCCOL) system reported 358 connectional landmarks, each of which possesses consistent DTI-derived white matter fiber connection pattern that's reproducible in over 240 healthy brains. However, the DICCCOL system can be substantially improved by integrating anatomical and morphological data throughout landmark initialization and optimization procedures. During this paper, we have a tendency to gift a novel anatomy-guided landmark discovery framework that defines and optimizes landmarks via integrating made anatomical, morphological, and fiber connectional information for landmark initialization, group-wise optimization and prediction, that are formulated and solved as an energy minimization drawback. The framework finally determined 55five consistent connectional landmarks. Validation studies demonstrated that the 55five landmarks are reproducible, predictable, and exhibited fairly correct anatomical, connectional, and purposeful correspondences across individuals and populations and thus are named anatomy-guided DICCCOL or A-DICCCOL. This A-DICCCOL system represents common cortical architectures with anatomical, connectional, and functional correspondences across different subjects and would doubtless give opportunities for varied applications in brain science.
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