Improved tractography using asymmetric fibre orientation distributions

Matteo Bastiani, Michiel Cottaar, Krikor Dikranian, Aurobrata Ghosh, Hui Zhang, Daniel C. Alexander, Timothy E. Behrens, Saad Jbabdi, Stamatios N. Sotiropoulos

Research output: Contribution to journalArticle

15 Scopus citations


Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and –x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity.

Original languageEnglish
Pages (from-to)205-218
Number of pages14
StatePublished - Sep 2017


  • Asymmetry
  • Connectome
  • Diffusion MRI
  • Structural connectivity
  • Tractography

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    Bastiani, M., Cottaar, M., Dikranian, K., Ghosh, A., Zhang, H., Alexander, D. C., Behrens, T. E., Jbabdi, S., & Sotiropoulos, S. N. (2017). Improved tractography using asymmetric fibre orientation distributions. NeuroImage, 158, 205-218.