Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study

• Published in: Brain Structure and Function Vol. 221; no. 3; pp. 1751 - 1766
• Main Authors: Rojkova, K., Volle, E., Urbanski, M., Humbert, F., Dell’Acqua, F., Thiebaut de Schotten, M.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2016; Springer Nature B.V; Springer Verlag
• Subjects: Adult; Age; Aged; Aging; Atlases as Topic; Bioengineering; Biomedical and Life Sciences; Biomedicine; Brain; Brain - anatomy & histology; Brain - physiology; Cell Biology; Diffusion Magnetic Resonance Imaging - methods; Diffusion Tensor Imaging - methods; Diffusion-weighted imaging; Education; Educational Status; Female; Frontal lobe; Frontal Lobe - anatomy & histology; Frontal Lobe - physiology; Human health and pathology; Humans; Imaging; Life Sciences; Male; Middle Aged; Neural Pathways - anatomy & histology; Neural Pathways - physiology; Neurology; Neurons and Cognition; Neurosciences; Original Article; Studies; Tissues and Organs; Tractography; U-shaped tracts; White matter; Young Adult; Diffusion-weighted imaging; Atlas; Frontal lobe; Fasciculi; Tractography; Aging; White matter; U-shaped tracts
• ISSN: 1863-2653; 1863-2661; 1863-2661; 0340-2061
• DOI: 10.1007/s00429-015-1001-3

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22–71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.