Structural characterization of the Extended Frontal Aslant Tract trajectory: A ML-validated laterality study in 3T and 7T
| Autor: | Jose R. Pineda, Saül Pascual-Diaz, Alberto Prats-Galino, Federico Varriano |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Dissecció humana Cognitive Neuroscience Dissecció Orthogonal plane 050105 experimental psychology Lateralization of brain function Functional Laterality Automated fiber quantification lcsh:RC321-571 White matter Machine Learning 03 medical and health sciences 0302 clinical medicine Neural Pathways Lòbul frontal Aprenentatge automàtic Machine learning medicine Connectome Humans 0501 psychology and cognitive sciences lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Mathematics Human Connectome Project Motor area Lateralization Dissection 05 social sciences Laterality Motor Cortex Anatomy White Matter Human dissection medicine.anatomical_structure Diffusion Tensor Imaging Neurology Frontal lobe Lateralitat Extended Frontal Aslant Tract Female 030217 neurology & neurosurgery Tractography |
| Zdroj: | Dipòsit Digital de la UB Universidad de Barcelona NeuroImage, Vol 222, Iss, Pp 117260-(2020) |
| Popis: | The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca’s territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In this study, we aim to characterize the microstructural properties of the exFAT trajectories as a means to perform a laterality analysis to detect interhemispheric structural differences along the tracts using the Human Connectome Project (HCP) dataset. To that end, the bilateral exFAT was reconstructed for 3T and 7T HCP acquisitions in 120 randomly selected subjects. As a complementary exploration of the exFAT anatomy, we performed a white matter dissection of the exFAT trajectory of two ex-vivo left hemispheres that provide a qualitative assessment of the tract profiles. We assessed the lateralization structural differences in the exFAT by performing: (i) a laterality comparison between the mean microstructural diffusion-derived parameters for the exFAT trajectories, (ii) a laterality comparison between the tract profiles obtained by applying the Automated Fiber Quantification (AFQ) algorithm, and (iii) a cross-validated Machine Learning (ML) classifier analysis using single and combined tract profiles parameters for single-subject classification. The mean microstructural diffusion-derived parameter comparison showed statistically significant differences in mean FA values between left and right exFATs in the 3T sample. The diffusion parameters studied with the AFQ technique suggest that the inferiormost half of the exFAT trajectory has a hemispheric-dependent fingerprint of microstructural properties, with an increased measure of tissue hindrance in the orthogonal plane and a decreased measure of orientational dispersion along the main tract direction in the left exFAT compared to the right exFAT. The classification accuracy of the ML models showed a high agreement with the magnitude of those differences. |
| Databáze: | OpenAIRE |
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