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The human brain is sexually dimorphic and these sex differences have shown to affect brain response to trauma. We investigated the sex differences in the tract structures by studying diffusion weighted (DW) images of 594 females and 506 males from the Human-Connectome-Project dataset. All the female and male DW images were reconstructed in the ICBM152 space using Q-Space diffeomorphic reconstruction technique and their mapped orientation distribution function images were averaged to generate the female- and male-DW-templates. The tract streamlines were generated through tractography for female and male templates and normalized to the total brain volume . The distributions of normalized tract lengths were significantly different between female- and male-templates and the female-template showed to have more longer normalized tracts compared to the male template. For the regional analysis, the templates were parcellated into sixteen regions of interests (ROI) including brain-stem, five subregions of corpus-callosum, and right and left hippocampus, thalamus, cerebellum white-matter (WM), cerebral WM, and cerebellum cortex using a FreeSurfer-based segmentation atlas. For all the ROIs, the average fractional anisotropy (0.5-5.7%) and normalized tract lengths (1.1-2.7%) were larger in female template while the average mean diffusion was larger (1.3-5.6%) in male-template. Quantifying brain connectivity by counting number of tracts passing through pairs of ROIs, showed more pairs with a higher connectivity in female-template, and one of the highest percentages of sex differences in right/left cerebellum WM/cortex connections. Our results reinforce the need to continue investigating the sex variations in axonal structure and their effects to brain trauma. 

he sex-based human brain structural variations alongside the necessity and development process for sex-specific brain templates were investigated in this study. Comparing magnetic resonance images of 500 female and 500 male subjects, no significant sex-based difference was observed for average cortical thickness, however, all the volumetric values, including the total brain volume (TBV) and major 19 brain regions, were found to be significantly different between females and males. Moreover, analyzing the fractional volume of the regions showed that these sex variations were not proportional to TBV for all regions. These findings underscore the importance of distinguishing the sex-based differences in human brain studies. While brain templates have been developed for general population and cohorts with the same characteristics such as race or age, there is a lack of sex-specific brain templates. To fill this gap and find a representative reference brain image for each sex, nonlinear templates were developed for female, male, and mixed population subjects. Next, a separate set of 109 female and 109 male brain images were used to evaluate the sex-specificity of the brain templates. It was observed that the female and male test subjects were registered to their sex-specific templates with the lowest amount of deformation/warping confirming better representativeness of the sex-specific templates for their target population. The findings of this study including the templates and the reported variations can be used in research involving sex dimorphic brain disorders, diseases, and/or injuries such as traumatic brain injury that is affected by the sex-based brain anatomical differences. Statement of significance: Human brain exhibits sex-based variation both in size and volumetric composition of different regions. Despite these differences, there is a paucity of sex-specific brain templates. Addressing this gap marks the significance of our study as briefly explained here. We have shown that differences in male and female brain go beyond simple scaling and the observation of regional differences that are not proportional to the sex-based total brain volume variations has motivated us to develop sex-specific templates. The representativeness and difference of these sex-specific templates were assessed by measuring the amount of required warping in nonlinear registration of test subjects to them. It was shown that registration of female and male subjects to their corresponding sex-specific template involved lower level of warping compared to their registration to their opposite sex or mixed population brain template. 

Abstract Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.