Concussion Alters the Functional Brain Processes of Visual Attention and Working Memory
Bibliographic record
Abstract
Millions of North Americans sustain a concussion or a mild traumatic brain injury annually, and are at risk of cognitive, emotional, and physical sequelae. Although functional MRI (fMRI) studies have provided an initial framework for examining functional deficits induced by concussion, particularly working memory and attention, the temporal dynamics underlying these deficits are not well understood. We used magnetoencephalography (MEG), a modality with millisecond temporal resolution, in conjunction with a 1-back visual working memory (VWM) paradigm using scenes from everyday life to characterize spatiotemporal functional differences at specific VWM stages, in adults had had or had not had a recent concussion. MEG source-level differences between groups were determined by whole-brain analyses during encoding and recognition phases. Despite comparable behavioral performance, abnormal hypo- and hyperactivation patterns were found in brain areas involving frontoparietal, ventral occipitotemporal, temporal, and subcortical areas in concussed patients. These patterns and their timing varied as a function of VWM stagewise processing, linked to early attentional control, visuoperceptual scene processing, and VWM maintenance and retrieval processes. Parietal hypoactivation, starting at 60 ms during encoding, was correlated with symptom severity, possibly linked to impaired top-down attentional processing. Hyperactivation in the scene-selective occipitotemporal areas, the medial temporal complex, specifically the right hippocampus and orbitofrontal areas during encoding and/or recognition, lead us to posit inefficient but compensatory visuoperceptual, relational, and retrieval processing. Although injuries sustained after the concussion were considered "mild," these data suggest that they can have prolonged effects on early attentional and VWM processes.
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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 | 0.001 |
| 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 | 0.000 | 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".