Structural brain alterations and predictors of clinical improvement in functional cognitive disorder after concussion
Bibliographic record
Abstract
Functional cognitive disorder (FCD) is an under-studied yet likely prevalent subtype of functional neurological disorder (FND), with neural mechanisms that remain poorly understood. While studies of other FND subtypes have revealed structural and functional brain alterations across several large-scale brain networks, no study to date has investigated neural alterations in FCD. Here, we examined structural grey matter brain differences as measured from magnetic resonance imaging in 37 adults with FCD after concussion compared to 25 post-concussion controls. We compared FreeSurfer-based cortical thickness and subcortical volumes between groups and investigated associations between structural measures and memory symptoms. A subset of participants with FCD (n = 24) participated in a randomized controlled trial of cognitive-behavioral therapy vs. cognitive rehabilitation, and relationships between baseline structural measures and treatment outcomes were evaluated. All primary analyses were adjusted for age, sex, estimated IQ, and loss of consciousness, and corrected for multiple comparisons. No significant between-group differences in cortical thickness or subcortical volume were observed. However, across all participants, greater functional memory symptom severity was associated with larger right amygdala volume, which remained significant adjusting for depression scores, anxiety scores, and psychotropic medication use. Post-hoc analyses identified that this observation was driven by differences in lateral, basal, and paralaminar amygdalar nuclei. Additionally, greater improvement in memory symptoms following treatment was associated with increased pre-treatment cortical thickness in the right inferior frontal gyrus. These findings provide initial insights into the structural neurobiology of FCD and its associations with symptom severity and clinical trajectories.
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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 | 0.000 | 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 | 0.000 | 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".