Comparison of diffusion tractography and tract-tracing measures of connectivity strength in rhesus macaque connectome

Abstract

With the mapping of macroscale connectomes by means of in vivo diffusion-weighted MR Imaging (DWI) rapidly gaining in popularity, one of the necessary steps is the examination of metrics of connectivity strength derived from these reconstructions. In the field of human macroconnectomics the number of reconstructed fiber streamlines (NOS) is more and more used as a metric of cortico-cortical interareal connectivity strength, but the link between DWI NOS and in vivo animal tract-tracing measurements of anatomical connectivity strength remains poorly understood. In this technical report, we communicate on a comparison between DWI derived metrics and tract-tracing metrics of projection strength. Tract-tracing information on projection strength of interareal pathways was extracted from two commonly used macaque connectome datasets, including (1) the CoCoMac database of collated tract-tracing experiments of the macaque brain and (2) the high-resolution tract-tracing dataset of Markov and Kennedy and coworkers. NOS and density of reconstructed fiber pathways derived from DWI data acquired across 10 rhesus macaques was found to positively correlate to tract-tracing based measurements of connectivity strength across both the CoCoMac and Markov dataset (both P < 0.001), suggesting DWI NOS to form a valid method of assessment of the projection strength of white matter pathways. Our findings provide confidence of in vivo DWI connectome reconstructions to represent fairly realistic estimates of the wiring strength of white matter projections. Our cross-modal comparison supports the notion of in vivo DWI to be a valid methodology for robust description and interpretation of brain wiring.

Building connectomes using diffusion MRI: why, how and but

“…However, it is questionable how informative such properties are when treating connectomes as networks, which would require some proxy of connectivity. In a recent study no correlation was found between such microstructural measures and axonal strengths measured by tracers . On the other hand, functions of streamline counts can be thought to be more relevant in such a network context .…”

Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth

“…First, we constructed a symmetric N × N streamline count matrix for each subject, where edge weights were equal to the number of probabilistic streamlines connecting each pair of GM-WM boundary nodes [39,74]. Second, we constructed networks where edge weights were equal to the total number of streamlines connecting a node pair divided by their total volume [48,75,76]. Third and finally, we also constructed networks where edge weights were equal to the connectivity probability between each pair of brain regions, which represents the proportion of total samples (probabilistic streamlines) initiated from the seed region that reached the target region [77–79].…”

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

“…In the monkey, whole-brain tract-tracer connection networks and tractography networks demonstrate a significant, but only moderately high correspondence. Currently, the highest reported correlation stands at r = 0.59 (Donahue et al, 2016), though it is often much lower (van den Heuvel et al, 2015a). Future work could probably improve these relationships substantially by imposing rigorous anatomical constraints in the tractography process (Smith et al, 2015), but such efforts have not seen extensive validation yet.…”