First- and Second-Order Stimuli Reaction Time Measures Are Highly Sensitive to Mild Traumatic Brain Injuries
Bibliographic record
Abstract
Mild traumatic brain injury (mTBI) has subtle effects on several brain functions that can be difficult to assess and follow up. We investigated the impact of mTBI on the perception of sine-wave gratings defined by first- and second-order characteristics. Fifteen adults diagnosed with mTBI were assessed at 15 days, 3 months, and 12 months postinjury. Fifteen matched controls followed the same testing schedule. Reaction times (RTs) for flicker detection and motion direction discrimination were measured. Stimulus contrast of first- and second-order patterns was equated to control for visibility, and correct-response RT means, standard deviations (SDs), medians, and interquartile ranges (IQRs) were calculated. The level of symptoms was also evaluated to compare it to RT data. In general in mTBI, RTs were longer, and SDs as well as IQRs larger, than those of controls. In addition, mTBI participants' RTs to first-order stimuli were shorter than those to second-order stimuli, and SDs as well as IQRs larger for first- than for second-order stimuli in the motion condition. All these observations were made over the three sessions. The level of symptoms observed in mTBI was higher than that of control participants, and this difference did also persist up to 1 year after the brain injury, despite an improvement. The combination of RT measures with particular stimulus properties is a highly sensitive method for measuring mTBI-induced visuomotor anomalies and provides a fine probe of the underlying mechanisms when the brain is exposed to mild trauma.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".