The neural basis of video gaming
Bibliographic record
Abstract
Video game playing is a frequent recreational activity. Previous studies have reported an involvement of dopamine-related ventral striatum. However, structural brain correlates of video game playing have not been investigated. On magnetic resonance imaging scans of 154 14-year-olds, we computed voxel-based morphometry to explore differences between frequent and infrequent video game players. Moreover, we assessed the Monetary Incentive Delay (MID) task during functional magnetic resonance imaging and the Cambridge Gambling Task (CGT). We found higher left striatal grey matter volume when comparing frequent against infrequent video game players that was negatively correlated with deliberation time in CGT. Within the same region, we found an activity difference in MID task: frequent compared with infrequent video game players showed enhanced activity during feedback of loss compared with no loss. This activity was likewise negatively correlated with deliberation time. The association of video game playing with higher left ventral striatum volume could reflect altered reward processing and represent adaptive neural plasticity.
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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 | 0.001 |
| 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) | 0.001 | 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".