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

Abstract

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.

Using principal component analysis to capture individual differences within a unified neuropsychological model of chronic post-stroke aphasia: Revealing the unique neural correlates of speech fluency, phonology and semantics

“…2E. The speech quanta measure (F1) was uniquely correlated with the left pre-central gyrus, superior insula and putamen, and the underlying white matter (including the superior longitudinal fasciculus, caudate–premotor tracts and the frontal ‘aslant’ tract (FAT) that connects the medial-superior portion of the frontal lobe to the inferior-lateral frontal region) (Basilakos et al., 2014, Catani et al., 2012, Rojkova et al., 2015). The semantic variety factor (F2) was uniquely correlated with the SMG and pMTG/STG plus the anterior/orbito frontal gyrus.…”

Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke

“…Changes in model fits between the lesion load control models and the full models were considered significant if the p- value for the F -test on the R 2 change statistic survived Bonferroni-Holm correction to control the FWE at 0.05 across all three R 2 change tests (one for each task). To illustrate that the conclusions drawn from these analyses are robust against changes in ROI definition, control analyses were performed using ROIs defined using an alternate white matter atlas (Rojkova et al, 2016), and are provided in the Supplementary Material (Supplementary Analysis 4). Additional control analyses provided in the Supplementary Material further illustrate that the addition of lesion loads for other cortical areas (i.e.…”

Shared white matter alterations across emotional disorders: A voxel-based meta-analysis of fractional anisotropy

“…This threshold has been shown to optimize sensitivity at the same time as correctly controlling the false positive rate, and was approximately equivalent to a corrected p value of .025 (Radua et al, 2012). Peaks of significant clusters were labeled automatically by the SDM software (Rojkova et al, 2016, Thiebaut de Schotten et al, 2011a, Thiebaut de Schotten et al, 2011b). A jack-knife analysis was performed to establish reliability of the results (Radua and Matrix-Cols, 2009).…”