Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

Multimodal MRI template creation in the ring-tailed lemur and rhesus macaque

We present a multimodal registration algorithm for simultaneous alignment of datasets with both scalar and tensor MRI images. We employ a volumetric, cubic B-spline parametrised transformation model. Regularisation is based on the logarithm of the singular values of the local Jacobian and ensures diffeomorphic warps. Tensor registration takes reorientation into account during optimisation, through a finite-strain approximation of rotation due to the warp. The combination of scalar, tensor and regularisation cost functions allows us to optimise the deformations in terms of tissue matching, orientation matching and distortion minimisation simultaneously. We apply our method to creating multimodal T2 and DTI MRI brain templates of two small primates (the ring-tailed lemur and rhesus macaque) from high-quality, ex vivo, 0.5/0.6 mm isotropic data. The resulting templates are of very high quality across both modalities and species. Tissue contrast in the T2 channel is high indicating excellent tissue-boundary alignment. The DTI channel displays strong anisotropy in white matter, as well as consistent left/right orientation information even in relatively isotropic grey matter regions. Finally, we demonstrate where the multimodal templating approach overcomes anatomical inconsistencies introduced by unimodal only methods