Navigational Memory Functional Magnetic Resonance Imaging: A Test for Concussion in Children
Bibliographic record
Abstract
Concussions are high incidence injuries with potentially devastating consequences. Youths are at risk because of a higher threat of repeated injury, and cumulative effects of concussions exist, making accurate diagnosis and follow-up essential. This study examines a navigational memory functional magnetic resonance imaging (fMRI) task to determine whether activation differences exist between children with concussion and uninjured controls. Fifty adolescents were recruited-35 controls and 15 with concussion. All subjects underwent structural and fMRI testing using our navigational memory task, and a battery of neuropsychological testing. The activation patterns of the 15 subjects with concussion were compared with those of 15 age and sex-matched controls. Subtraction and regression analyses were performed using the matched controls along with scatter-plots using means and 95% quantiles of the 35 controls. While no differences were seen with neuropsychological testing or task performance, subjects with concussion had significantly diminished activation in the retrosplenial, thalamic, and parahippocampal areas bilaterally, along with the right dorsolateral prefrontal cortex and left precuneus. Interestingly, they had increased activation in the left hippocampus and right middle temporal gyrus. Regression analysis demonstrated negative correlations between activation and post-concussive symptoms in the left premotor cortex, superior and inferior parietal lobules, and parahippocampal gyrus. Subjects with concussion show both diminished and increased activation in specific cerebral regions, differentiating them from controls. This is one of the first studies to look at such a task using fMRI and its applicability in testing for concussion in children. These findings support navigational memory fMRI as a potential objective test for concussions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".