Samuel Guay

Objective: Medio-lateral trunk dynamics during walking may be sensitive to subtle changes in locomotor regulation and can be measured with trunk-worn inertial sensors in natural sport environments. This study examined whether head impact exposure (HIE) sustained during Canadian varsity football games was associated with magnitude-dependent differences in medio-lateral trunk dynamics.Methods: Sixty-nine male collegiate football athletes were monitored across multiple competitive seasons using instrumented mouthguards for head impact detection and chest-worn inertial measurement units for walking analysis. HIE was quantified at play-level and game-level temporal scales. Linear mixed-effects models assessed associations between HIE and root mean square lateral trunk acceleration (ACC) and trunk roll angular velocity (ROLL) extracted from linear walking bouts, controlling for baseline dynamics, movement speed, physical workload, and game exposure.Results: Across 10,156 linear walking bouts and 3,403 head impacts, HIE was associated with magnitude-dependent differences in medio-lateral trunk dynamics. Play-level HIE was associated with increased ROLL (β = 0.06, p < 0.001), independent of concurrent physical workload. Game-level HIE was associated with post-game increases in ACC (β = 0.09, p = 0.041) and ROLL (β = 0.15, p < 0.001), with larger estimates than play-level models. Across temporal scales, associations were more consistent for ROLL than ACC.Conclusion: HIE was associated with measurable differences in medio-lateral trunk dynamics during field-based walking, particularly trunk roll angular velocity. Continuous trunk-worn inertial sensing may provide a scalable field-based approach for characterizing locomotor-dynamics changes associated with head impact exposure in contact sport athletes

A bstract: Pitch control models quantify spatial dominance in football by estimating which player can arrive first at each pitch location, but they treat all players as equivalently capable regardless of preceding effort. We introduce physiology-aware pitch control (Phys-PC), a model-agnostic time-to-arrive correction that imposes two physiological capacity channels calibrated from tracking data: a transient recoverable burden capturing incomplete recovery from recent high-intensity efforts, and a cumulative non-recoverable drain accumulating across match play. Both channels reduce a bounded access scale that modulates kinematic TTA before any downstream pitch-control computation. All parameters are anchored to exercise-physiology benchmarks; no laboratory measurements are assumed. Applied to a 64-match international tournament, Phys-PC reveals structure that kinematic models cannot detect. In head-to-head races, the dominant burden channel shifts from transient to cumulative over the course of a match, with a transient resurgence in the final 15 minutes. These physiological asymmetries predict match outcomes: relative reserve advantage is associated with higher odds of winning ground challenges (OR = 1.20, p = 0.006; +4.2 pp), completing over-the-top passes past recovering defenders (OR = 1.45, p = 0.034; +8.3 pp), and progressing possession sequences into the final third (OR = 1.31, p = 0.013; +5.1 pp). At the player-profile level, an acute-cumulative decomposition of contested space access separates roles and individuals whose territorial reach is maintained through sustained positioning from those whose access is rebuilt through repeated high-intensity actions, providing a physiological lens on team tactical structure.

Head finite element models (hFEMs) are valuable in understanding injury mechanisms in head impacts. Personalizing hFEMs is important for capturing individualized brain responses, with brain volume scaling proving effective. However, the role of refined white matter (WM) parcellation in hFEMs for evaluating brain strain responses, particularly important in the context of subconcussive head impacts (SHIs) often assessed through changes in WM integrity, remains relatively underexplored. This study evaluated the effect of refined subject-specific WM parcellation in 34 WM segments on responses variability due to brain volume variations, using peak maximum principal strain (95MPS) and strain rate (95MPSr) as injury predictive metrics. Data from diffusion-weighted imaging of 21 Canadian varsity football players were utilized to personalize 21 hFEMs. Simulating four different head impacts, representing 50th and 99th percentile resultant accelerations in frontal and angled-top-right directions, refined player-specific WM parcellation better captured variability of strain responses compared to baseline parcellation. Up to 75.71% of 95MPS and 77.14% of 95MPSr responses were deemed different across refined WM segments for players, compared to a maximum of 16.19% of responses with baseline parcellation. These results suggest that player-specific refined WM parcellation improves the ability to capture player-specific responses. Both impact direction and intensity influenced variations in strain response, with angled-top head impacts combined with high intensity showing greater player-specificity compared to lower intensity and frontal head impacts. These findings highlight the potential benefit of model scaling along with player-specific refined WM parcellation in hFEMs for comprehensively evaluating strain responses. Detailed WM parcellation in hFEMs is important for comprehensive injury assessment, enhancing the alignment of hFEMs with imaging studies evaluating changes in WM integrity across segments. The simple and straightforward method presented herein to achieve player-specific strain response is promising for future SHI studies.

Brain age prediction algorithms using structural magnetic resonance imaging (MRI) estimate the biological age of the brain by comparing it to a normal aging trajectory, allowing for the identification of deviations that may indicate slower or accelerated biological aging. Traumatic brain injury (TBI) and sports-related concussion (SRC) have been associated with greater brain age gap (BAG) compared to healthy controls. In this study, we aimed to investigate BAG in athletes suffering from persistent postconcussion syndrome (PCS+) compared to PCS− athletes, and used SHapley Additive exPlanations (SHAP), an explainable artificial intelligence framework, to provide further details on which specific features drive the brain age predictions. Brain age was derived from T1-weighted MRI images in a cohort of 50 athletes (24 with PCS+) from 22 to 73 years old from the general population. The results revealed that athletes with PCS+ had a brain age approximately 5 years older than the PCS− athletes, with no clinical variable associated with it. Exploratory analyses also showed a greater brain age in athletes who self-reported five or more SRCs. Regarding SHAP, the third ventricle was found to be the most informative feature in the PCS+ group, while the superior temporal sulcus posterior area was more informative in the PCS− group. This study demonstrated the potential of using brain age and explainable artificial intelligence frameworks to study athletes with PCS. Further research is needed to explore the underlying mechanisms driving brain aging in this population and to identify potential biomarkers for early detection and intervention.

OHBM Brainhack 2022 took place in June 2022. The first hybrid OHBM hackathon, it had an in-person component taking place in Glasgow and three hubs around the globe to improve inclusivity and fit as many timezones as possible. In the buzzing setting of the Queen Margaret Union and of the virtual platform, 23 projects were presented after development. Following are the reports of 14 of those, as well as a recapitulation of the organisation of the event.

TractoInferno is the world’s largest open-source multi-site tractography database, including both research- and clinical-like human acquisitions, aimed specifically at machine learning tractography approaches and related ML algorithms. It provides 284 samples acquired from 3 T scanners across 6 different sites. Available data includes T1-weighted images, single-shell diffusion MRI (dMRI) acquisitions, spherical harmonics fitted to the dMRI signal, fiber ODFs, and reference streamlines for 30 delineated bundles generated using 4 tractography algorithms, as well as masks needed to run tractography algorithms. Manual quality control was additionally performed at multiple steps of the pipeline. We showcase TractoInferno by benchmarking the learn2track algorithm and 5 variations of the same recurrent neural network architecture. Creating the TractoInferno database required approximately 20,000 CPU-hours of processing power, 200 man-hours of manual QC, 3,000 GPU-hours of training baseline models, and 4 Tb of storage, to produce a final database of 350 Gb. By providing a standardized training dataset and evaluation protocol, TractoInferno is an excellent tool to address common issues in machine learning tractography.

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities.Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design.Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Transcranial alternating current stimulation, a non-invasive brain stimulation technique, has been used to increase alpha (8–12 Hz) power, the latter being associated with various brain functions and states. Heterogeneity among stimulation parameters across studies makes it difficult to implement reliable transcranial alternating current stimulation protocols, explaining the absence of consensus on optimal stimulation parameters to modulate the alpha rhythm. This project documents the differential impact of controlling for key transcranial alternating current stimulation parameters, namely the intensity, the frequency and the stimulation site (anterior versus posterior). Phase 1:20 healthy participants underwent 4 different stimulation conditions. In each experimental condition, stimulation via 2 electrodes was delivered for 20 min. Stimulation conditions were administered at PO7-PO8 or F3-F4 at individual’s alpha frequency, or at individual’s theta frequency or sham. Stimulation intensity was set according to each participant’s comfort following a standardized unpleasantness scale (≤ 40 out of 100) and could not exceed 6 mA. All conditions were counterbalanced. Phase 2: participants who tolerated higher intensity of stimulation (4–6 mA) underwent alpha-frequency stimulation applied over PO7–PO8 at 1 mA to investigate within-subject modulation of stimulation response according to stimulation intensity. Whether set over posterior or anterior cortical sites, alpha-frequency stimulation showed greater increase in alpha power relative to stimulation at theta frequency and sham stimulation. Posterior alpha-frequency stimulation showed a greater increase in alpha power relative to the adjacent frequency bands over frontal and occipito-parietal brain areas. Low intensity (1 mA) posterior alpha stimulation showed a similar increase in alpha power than at high (4–6 mA) intensity when measured immediately after stimulation. However, when tested at 60 min or 120 min, low intensity stimulation was associated with significantly superior alpha power increase relative to high intensity stimulation. This study shows that posterior individual’s alpha frequency stimulation at higher intensities is well tolerated but fails to increase stimulation aftereffects recorded within 2 h of stimulation on brain oscillations of the corresponding frequency band. In sharp contrast, stimulating at 1 mA (regardless of phosphene generation or sensory perception) effectively and selectively modulates alpha power within that 2-h time window, thus validating that it as a reliable stimulus intensity for future studies. This study also shows that posterior alpha-frequency stimulation preferentially modulates endogenous brain oscillations of the corresponding frequency band. Moreover, our data suggest that posterior alpha-frequency transcranial alternating current stimulation is a reliable and precise non-invasive brain stimulation technique for persistent modulation of both frontal and occipito-parietal alpha power.