Comparison between diffusion MRI tractography and histological tract-tracing of cortico-cortical structural connectivity in the ferret brain

• Published in: Network neuroscience (Cambridge, Mass.) Vol. 3; no. 4; pp. 1038 - 1050
• Main Authors: Delettre, Céline, Messé, Arnaud, Dell, Leigh-Anne, Foubet, Ophélie, Heuer, Katja, Larrat, Benoit, Meriaux, Sebastien, Mangin, Jean-Francois, Reillo, Isabel, de Juan Romero, Camino, Borrell, Victor, Toro, Roberto, Hilgetag, Claus C
• Format: Journal Article
• Language: English
• Published: One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.01.2019; MIT Press Journals, The
• Subjects: Algorithms; Brain; Brain architecture; Computational neuroscience; Diffusion MRI; Ferret; In vivo methods and tests; Life Sciences; Magnetic resonance imaging; Neural networks; Structural connectivity; Tracing; Tract-tracing; Tractography; Validation; Validation; Neuroscience; Structural connectivity; Tractography; Ferret; Diffusion MRI; Tract-tracing
• ISSN: 2472-1751; 2472-1751
• DOI: 10.1162/netn_a_00098

The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture and noninvasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal, and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearman’s rho ranging from 0.67 to 0.91), while only small, nonsignificant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms, and hence into the influence of choosing one algorithm over another. In this article we used tract-tracing data as a gold standard to validate the use of diffusion MRI tractography for inferring structural connectivity in the ferret brain as well as for assessing the influence of several state-of-the-art tractography algorithms on the inferred connections. We found high correspondence between diffusion MRI tractography and tract-tracing with little differences between the explored algorithms. We conclude that diffusion MRI tractography provides a worthwhile whole-brain estimate of structural connectivity that can be employed in further anatomical, developmental, and computational studies of the ferret brain.