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The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data., Competing Interests: The authors have declared that no competing interests exist.

Background: A small number of blind people are adept at echolocating silent objects simply by producing mouth clicks and listening to the returning echoes. Yet the neural architecture underlying this type of aid-free human echolocation has not been investigated. To tackle this question, we recruited echolocation experts, one early- and one late-blind, and measured functional brain activity in each of them while they listened to their own echolocation sounds., Results: When we compared brain activity for sounds that contained both clicks and the returning echoes with brain activity for control sounds that did not contain the echoes, but were otherwise acoustically matched, we found activity in calcarine cortex in both individuals. Importantly, for the same comparison, we did not observe a difference in activity in auditory cortex. In the early-blind, but not the late-blind participant, we also found that the calcarine activity was greater for echoes reflected from surfaces located in contralateral space. Finally, in both individuals, we found activation in middle temporal and nearby cortical regions when they listened to echoes reflected from moving targets., Conclusions: These findings suggest that processing of click-echoes recruits brain regions typically devoted to vision rather than audition in both early and late blind echolocation experts.