Altered metabolic connectivity within the limbic cortico-striato-thalamo-cortical circuit in presymptomatic and symptomatic behavioral variant frontotemporal dementia
Bibliographic record
Abstract
Abstract Background Behavioral variant frontotemporal dementia (bvFTD) is predominantly considered a dysfunction in cortico-cortical transmission, with limited direct investigation of cortical-subcortical transmission. Thus, we aimed to characterize the metabolic connectivity between areas of the limbic cortico-striato-thalamic-cortical (CSTC) circuit in presymptomatic and symptomatic bvFTD patients. Methods Thirty-three bvFTD patients and 33 unrelated healthy controls were recruited for this study. Additionally, six asymptomatic carriers of the MAPT P301L mutation were compared with 12 non-carriers who were all from the same family of bvFTD. Each participant underwent neuropsychological assessment, genetic testing, and a hybrid PET/MRI scan. Seed-based metabolic connectivity based on [ 18 F]-fluorodeoxyglucose PET between the main components within the limbic CSTC circuit was explored according to the Oxford-GSK-Imanova Striatal Connectivity Atlas. Results BvFTD patients exhibited reduced metabolic connectivity between the relays in the limbic CSTC circuit, which included the frontal region (ventromedial prefrontal cortex, orbitofrontal cortex, rectus gyrus, and anterior cingulate cortex), the limbic striatum, and thalamus compared to controls. In the bvFTD patients, the involvement of the limbic CSTC circuit was associated with the severity of behavior disruption, as measured by the frontal behavior inventory, the disinhibition subscale, and the apathy subscale. Notably, asymptomatic MAPT carriers had weakened frontostriatal connectivity but enhanced striatothalamus and thalamofrontal connectivity within the limbic CSTC circuit compared with noncarriers. Conclusion These findings suggested that aberrant metabolic connectivity within the limbic CSTC circuit is present in symptomatic and even asymptomatic stages of bvFTD. Thus, metabolic connectivity patterns could be used as a potential biomarker to detect the presymptomatic stage and track disease progression.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".