Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the white matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor imaging (DTI) tractography to create probabilistic white matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.Methods: Whole-brain diffusion imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.Results: The resulting functionally-defined white matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map white matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroimaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative white matter imaging signals) to these functional brain networks.

BackgroundMorphometric measurements of the corpus callosum (CC) are important to have normative values according to sex, age and race/ethnicity.ObjectivesThis study was done to measure the size of CC and to identify its gender- and age-related differences in the North of Iran.Patients and MethodsThe size of CC on midsagittal section was measured in 100 (45 males, 55 females) normal subjects using magnetic resonance imaging (MRI) admitted to the Kowsar MRI center in Gorgan–Northern Iran.Longitudinal and vertical dimensions of the CC, longitudinal and vertical lengths of the brain and the length of genu and splenium were measured. Data were analyzed by student’s unpaired t test, ANOVA and regression analysis.ResultsThe anteroposterior length and vertical dimension of the CC, the length of genu and splenium were larger in males than in females, but these differences were not significant. The anteroposterior and vertical lengths of the brain were significantly larger in males than in females (P < 0.05). The length of CC increased with age and regression equations for predicting age were derived from the length of the CC. There was also a positive significant correlation between the anteroposterior length of the CC and the length of the brain and vertical dimension of the CC.ConclusionsThis study showed that various CC parameters vary with the values documented in the Caucasian, Indian and Japanese population.