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The coronavirus disease 2019 (COVID-19) outbreak introduced unprecedented health-risks, as well as pressure on the economy, society, and psychological well-being due to the response to the outbreak. In a preregistered study, we hypothesized that the intense experience of the outbreak potentially induced stress-related brain modifications in the healthy population, not infected with the virus. We examined volumetric changes in 50 participants who underwent MRI scans before and after the COVID-19 outbreak and lockdown in Israel. Their scans were compared with those of 50 control participants who were scanned twice prior to the pandemic. Following COVID-19 outbreak and lockdown, the test group participants uniquely showed volumetric increases in bilateral amygdalae, putamen, and the anterior temporal cortices. Changes in the amygdalae diminished as time elapsed from lockdown relief, suggesting that the intense experience associated with the pandemic induced transient volumetric changes in brain regions commonly associated with stress and anxiety. The current work utilizes a rare opportunity for real-life natural experiment, showing evidence for brain plasticity following the COVID-19 global pandemic. These findings have broad implications, relevant both for the scientific community as well as the general public., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2021. Published by Elsevier Inc.)

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses 1 . The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset 2-5 . Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

In vivo white matter tractography by diffusion tensor imaging (DTI) has become a popular tool for investigation of white matter architecture in the normal brain. Despite some unresolved issues regarding the accuracy of DTI, recent studies applied DTI for delineating white matter organization in the vicinity of brain lesions and especially brain tumors. Apart from the intrinsic limitations of DTI, the tracking of fibers in the vicinity or within lesions is further complicated due to changes in diseased tissue such as elevated water content (edema), tissue compression and degeneration. These changes deform the architecture of the white matter and in some cases prevent definite selection of the seed region of interest (ROI) from which fiber tracking begins. We show here that for displaced fiber systems, the use of anatomical approach for seed ROI selection yields insufficient results. Alternatively, we propose to select the seed points based on functional MRI activations which constrain the subjective seed ROI selection. The results are demonstrated on two major fiber systems: the pyramidal tract and the superior longitudinal fasciculus that connect critical motor and language areas, respectively. The fMRI based seed ROI selection approach enabled a more comprehensive mapping of these fiber systems. Furthermore, this procedure enabled the characterization of displaced white matter using the eigenvalue decomposition of DTI. We show that along the compressed fiber system, the diffusivity parallel to the fiber increases, while that perpendicular to the fibers decreases, leading to an overall increase in the fractional anisotropy index reflecting the compression of the fiber bundle. We conclude that definition of the functional network of a subject with deformed white matter should be done carefully. With fMRI, one can more accurately define the seed ROI for DTI based tractography and to provide a more comprehensive, functionally related, white matter mapping, a very important tool used in pre-surgical mapping.