Characterizing Cerebral Blood Flow Responses to Virtual Reality Gaming
Bibliographic record
Abstract
Virtual reality (VR) gaming provides an immersive 3D environment that is thought to stimulate cardiovascular (CV) function. Cerebral blood flow (CBF) is stimulated by cognitive and visual changes which enhances cerebral metabolic activity. We developed a 3D printed headpiece to assess CBF during VR gaming. The headpiece attached a transcranial Doppler (TCD) ultrasound probe to participants, allowing continuous measurement during dynamic tasks. Objective: We aim to characterize the impact of a rhythm game Beat Saber (VR BS ) on CBF through middle cerebral artery (MCAv) and posterior cerebral artery (PCAv) velocity responses. Further, we aim to assess the dose response of VR BS on CBF by increasing the difficulty of the game with easy, moderate, and hard levels. We hypothesized that increasing game difficulty would elicit progressive increases in MCAv and PCAv, an index of CBF. In addition, we aim to understand if song preference has an impact on CBF. We hypothesize that song familiarity would modulate MCAv and PCAv responses, enhancing flow efficiency compared to standardized songs. Participants (n= 7, 3F) played a total of six VR BS songs of increasing difficulty (easy, moderate, hard) while MCAv and PCAv were measured using TCD ultrasound. Song choice was standardized using 1 pre-selected song choice with progressive difficulty. Next, participants were allowed one song choice played at progressive difficulty. Mean CBF did not change during standard selection songs regardless of difficulty (MCAv: Easy 51.32±17.2, Moderate 52.0±16.6, Hard 51.4±19.4; PCAv: Easy 43.8±9.9, Moderate 38.7±3.9, Hard 40.5±5.2). Mean CBF did not change during preferred song selection regardless of difficulty (MCAv: Easy 51.8 ± 16.3, Moderate 48.9 ± 16.5, Hard 48.6 ± 17.9; PCAv: Easy 34.3±9.1, Moderate 37.5±6.2, Hard 39.2±2.9). Regardless of song performed, individuals who had an increased CV response (increased heart rate +23.4±0.8%) to VR BS increased both MCAv (15.9±1.4%) and PCAv (6±10.4%). The increase in this group appears similar to CBF changes observed during moderate intensity exercise. Future studies exploring the integration of CBF and CV responses to improve brain health with VR are needed. Dr. Kurt Smith is funded through a National Sciences and Engineering Research Council (NSERC) of Canada RGPIN-2020-06269 This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".