Distinct Components in the Right Extended Frontal Aslant Tract Mediate Language and Working Memory Performance: A Tractography-Informed VBM Study

The extended frontal aslant tract (exFAT) is a tractography-based extension of the frontal aslant tract (FAT) which has been shown to be related with language and working memory performance in healthy human adults, but whether those functional implications map to structurally separate regions along its trajectory is still an open question. We present a tractography-informed Voxel-Based Morphometry procedure capable of detecting local tract-specific structural differences in white matter regions and apply it in two maximum variation sampling studies by comparing local differences in diffusion-derived microstructural parameters and fiber density along the exFAT territory between top performers and bottom performers in language and working memory tasks. In the right hemisphere we were able to detect, without prior constraints, a vertical frontal aslant component approximating the original FAT trajectory whose fiber density was significantly correlated with language (but not working memory) performance and an anterior cluster component corresponding to a distinct anterior frontal aslant component whose fiber density was significantly correlated with working memory (but not language) performance. The reported sub-division of the exFAT territory describes a set of frontal connections that are compatible with previously reported results on the Broca's territory and frontal cortex hierarchical organization along an anterior-posterior gradient, suggesting that the exFAT could be part of a common neuroanatomical scaffold where language and working memory functions are integrated in the healthy human brain

Structural characterization of the Extended Frontal Aslant Tract trajectory: A ML-validated laterality study in 3T and 7T

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

Default Mode Network structural alterations in Kocher-Monro trajectory white matter transection: A 3 and 7 tesla simulation modeling approach

The Kocher-Monro trajectory to the cerebral ventricular system represents one of the most common surgical procedures in the field of neurosurgery. Several studies have analyzed the specific white matter disruption produced during this intervention, which has no reported adverse neurological outcomes. In this study, a graph-theoretical approach was applied to quantify the structural alterations in whole-brain level connectivity. To this end, 132 subjects were randomly selected from the Human Connectome Project dataset and used to create 3 independent 44 subjects groups. Two of the groups underwent a simulated left/right Kocher-Monro trajectory and the third was kept as a control group. For the right Kocher-Monro approach, the nodal analysis revealed decreased strength in the anterior cingulate gyrus of the transected hemisphere. The network-based statistic analysis revealed a set of right lateralized subnetworks with decreased connectivity strength that is consistent with a subset of the Default Mode Network, Salience Network, and Cingulo-Opercular Network. These findings could allow for a better understanding of structural alterations caused by Kocher-Monro approaches that could reveal previously undetected clinical alterations and inform the process of designing safer and less invasive cerebral ventricular approaches

When the FAT goes wide: Right extended Frontal Aslant Tract volume predicts performance on working memory tasks in healthy humans

<div><p>The Frontal Aslant Tract (FAT) is a tract recently described as having implications on language function. The originally proposed anatomical FAT definition characterizes a connection between Broca’s territory and anterior supplementary and pre-supplementary motor areas in the Superior Frontal Gyrus (SFG). Here we propose an extended definition of the FAT (the exFAT) that propagates more anteriorly into the SFG. A sample of 834 subjects from the WU-Minn HCP 900 subjects data release (S900) was selected. The bilateral exFATs were reconstructed for the whole sample using an automated pipeline and thresholded adjusted tract volumes were calculated. A laterality test was performed on the whole sample. The frontal cortex has known implications on superior cognitive functions, so here we evaluate the implications of exFAT volume on performance in a language task and on a set of working memory tasks. Two sub-samples of 70 subjects each were drawn from the S900 sample by selecting the 35 top-performers and 35 bottom-performers for both language and working memory tasks. Additional laterality tests were performed on each subsample. We did not find the exFAT to be lateralized in any of the samples. We found statistically significant differences in left adjusted exFAT volume between top-performers and bottom-performers in the language task. We also found statistically significant differences in right adjusted exFAT volume between top-performers and bottom-performers for 2-back working memory tasks. To check for the predictive power of the exFAT volumes as correlates for performance, we ran a repeated random sub-sampling cross-validation procedure based on a Support Vector Machine (SVM) classifier that was capable of correctly classifying holdout subjects to their corresponding group (top-performer vs bottom-performer) with an average accuracy of 74.5% for language task performance based on left exFAT volume and an accuracy of 64.2% for Working Memory performance based on right exFAT volume.</p></div

Performance tests in working memory samples.

<p>Performance tests in working memory samples.</p

Language task vs adjusted volume index correlations.

<p>Language task vs adjusted volume index correlations.</p

Performance tests in language samples.

<p>Performance tests in language samples.</p

Working memory vs adjusted volume index correlations.

<p>Working memory vs adjusted volume index correlations.</p

Lateralization tests for language samples.

<p>Lateralization tests for language samples.</p