Looking beneath the surface: the importance of subcortical structures in frontotemporal dementia
Bibliographic record
Abstract
Whilst initial anatomical studies of frontotemporal dementia focussed on cortical involvement, the relevance of subcortical structures to the pathophysiology of frontotemporal dementia has been increasingly recognized over recent years. Key structures affected include the caudate, putamen, nucleus accumbens, and globus pallidus within the basal ganglia, the hippocampus and amygdala within the medial temporal lobe, the basal forebrain, and the diencephalon structures of the thalamus, hypothalamus and habenula. At the most posterior aspect of the brain, focal involvement of brainstem and cerebellum has recently also been shown in certain subtypes of frontotemporal dementia. Many of the neuroimaging studies on subcortical structures in frontotemporal dementia have been performed in clinically defined sporadic cases. However, investigations of genetically- and pathologically-confirmed forms of frontotemporal dementia are increasingly common and provide molecular specificity to the changes observed. Furthermore, detailed analyses of sub-nuclei and subregions within each subcortical structure are being added to the literature, allowing refinement of the patterns of subcortical involvement. This review focuses on the existing literature on structural imaging and neuropathological studies of subcortical anatomy across the spectrum of frontotemporal dementia, along with investigations of brain-behaviour correlates that examine the cognitive sequelae of specific subcortical involvement: it aims to 'look beneath the surface' and summarize the patterns of subcortical involvement have been described in frontotemporal dementia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".