Modelling white matter in gyral blades as a continuous vector field

Abstract

Many brain imaging studies aim to measure structural connectivity with diffusion tractography. However, biases in tractography data, particularly near the boundary between white matter and cortical grey matter can limit the accuracy of such studies. When seeding from the white matter, streamlines tend to travel parallel to the convoluted cortical surface, largely avoiding sulcal fundi and terminating preferentially on gyral crowns. When seeding from the cortical grey matter, streamlines generally run near the cortical surface until reaching deep white matter. These so-called “gyral biases” limit the accuracy and effective resolution of cortical structural connectivity profiles estimated by tractography algorithms, and they do not reflect the expected distributions of axonal densities seen in invasive tracer studies or stains of myelinated fibres. We propose an algorithm that concurrently models fibre density and orientation using a divergence-free vector field within gyral blades to encourage an anatomically-justified streamline density distribution along the cortical white/grey-matter boundary while maintaining alignment with the diffusion MRI estimated fibre orientations. Using in vivo data from the Human Connectome Project, we show that this algorithm reduces tractography biases. We compare the structural connectomes to functional connectomes from resting-state fMRI, showing that our model improves cross-modal agreement. Finally, we find that after parcellation the changes in the structural connectome are very minor with slightly improved interhemispheric connections (i.e, more homotopic connectivity) and slightly worse intrahemi-spheric connections when compared to tracers.

The Digital Brain Bank, an open access platform for post-mortem imaging datasets

“…Here, gyral tractography (occipital lobe) reveals an overall pattern of fibers turning into the gyral bank at 0.5 mm. At 1 mm, an underestimation of connectivity at the gyral banks is observed, known as the ‘gyral bias’ ( Cottaar et al, 2021 ; Schilling et al, 2018 ). At 2 mm, tractography bears little resemblance to the expected architecture.…”

The Digital Brain Bank, an open access platform for post-mortem datasets

“…Here, gyral tractography (occipital lobe) reveals an overall pattern of fibres turning into the gyral bank at 0.5 mm. At 1 mm, an underestimation of connectivity at the gyral banks is observed, known as the ‘gyral bias’ (Cottaar et al, 2021; Schilling et al, 2018). At 2 mm, tractography bears little resemblance to the expected architecture.…”

“…overcoming ‘gyral bias’ – Fig. 1b) (Cottaar et al, 2021; Schilling et al, 2018). Polarised light imaging (PLI) provides estimates of myelinated fibre orientation (Axer et al, 2011), and complementary PLI data acquired in a subset of brain regions (4 μm in-plane) facilitates cross-scale comparisons (Fig.…”

Surface-based tracking for short association fibre tractography

“…One of the manifestations of gyral bias is drastically different angulation of streamline origins/terminations with respect to the cortical surface depending on their position along the gyral blades. A typical distribution will see streamlines near-radial to the surface in the gyral crowns and near-tangential along the banks and the sulcal fundi(Cottaar et al (2021); Van Essen et al (2014)). To investigate how the differences in fODFs between scanners and sequences might affect this pattern, the angle between the first streamline segment and the cortex was plotted against the position along the gyral blade.Anatomical distribution of connections.…”

“…To investigate how the differences in fODFs between scanners and sequences might affect this pattern, the angle between the first streamline segment and the cortex was plotted against the position along the gyral blade.Anatomical distribution of connections. To determine which type of SAF streamlines were most affected by the parameters of interest, position along the gyral blades was split into five zones (from sulcal fundi to gyral crowns) of equal surface areas, and undirected connectivity matrices were plotted with edge weights determined by streamline counts similar to the recent work byCottaar et al (2021).…”