The BDNF Val66Met polymorphism is associated with improved performance on a visual-auditory working memory task in varsity athletes
Bibliographic record
Abstract
Cognitive functions are often impacted by concussions and neurocognitive tests are used to assess the recovery process. However, these tests lack sensitivity in tracking the recovery process, which may depend on genetic polymorphisms. Brain derived neurotrophic factor (BDNF) is an important nerve growth factor linked with development and neural plasticity. The Val66Met (rs6265) polymorphism has been associated with reduced activity-dependent BDNF secretion, indicating reduced plasticity and greater stability of cortical networks. While most studies found that Met carriers have poorer scores on memory tests, not all studies are in agreement. The purpose of our study was to examine the consequences of Val/Met genotype on the performance of a cognitively demanding dual task, which involved visual spatial working memory (Corsi block test) and an auditory tone discrimination task. Participants were varsity athletes (n=33). All athletes were cleared to play at the time of testing; however, 19 players had a history of at least one concussion. BDNF genotyping was performed using saliva samples, which showed that 18% of athletes were Met allele carriers. The main outcome for the cognitive task was dual task cost (i.e., the percent reduction in performance on the auditory task while concurrently performing the visual task). Since subjects were asked to focus on the Corsi block test, performance on this task was similar during single and dual conditions. Regression analysis revealed that BDNF genotype accounted for 13% of variance in the auditory cost, while the presence of a concussion explained 11% of variance. Met carriers were significantly more accurate in the auditory task in the dual condition in comparison to the Val/Val athletes. These results are in agreement with a recent study which showed that subjects with the Met allele had significantly better performance on a visuomotor adaptation task.1 1Barton et al (2014). J Vis, 14(9): 4; doi:10.1167/14.9.4 Meeting abstract presented at VSS 2015
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".