Connectivity‐Metabolism Interplay in the Salience Network: Insights into Network‐Specific Dysfunctions in Frontotemporal Dementia
Bibliographic record
Abstract
BACKGROUND: F-Fluorodeoxyglucose positron emission tomography (FDG-PET) offers a unique opportunity to study the relationship between FC and energy demands. Alzheimer's is associated with significant dissociation between regional metabolism and neural activity, particularly within functionally active network hubs (Marchitelli et al. 2018); however, other neurodegenerative disorders remain unexplored. Frontotemporal dementia (FTD) is a rare form of dementia marked by functional breakdown of the salience network (SN), which regulates appropriate responses to stimuli. Like Alzheimer's, we hypothesized that FTD would be characterized by functional/metabolic dissociation; however, network-level breakdown would be most evident in the SN given its role in the disease process. METHOD: FDG-PET and rsfMRI were simultaneously collected on a Siemens Biograph mMR scanner from 18 controls and 20 behavioral-variant FTD (bvFTD) patients. FDG maps were converted into standardized uptake value ratio (SUVr). Local FC was quantified as Regional Homogeneity (ReHo), an fMRI metric reflecting regional synchronization of neural activity. Voxel-wise Spearman correlations were used to assess the relationship between ReHo and FDG-SUVr. Furthermore, inter-regional FC was measured with seed-based FC analysis. Group comparisons were made using 2-sample t-tests (p <0.05) while correcting for multiple comparisons. RESULT: Reduced correlations between FDG and ReHo were found within the hubs of the SN in bvFTD, particularly bilateral anterior insula (AI) (Table). Analysis of inter-regional FC revealed diminished communication between the AI and other SN hubs (Table). CONCLUSION: The disconnection between local FC and metabolism in the anterior insula (AI), coupled with disrupted intra-network communication within the SN, supports the hypothesis of insula being a primary target in FTD (Seeley, 2010). These findings indicate a critical role of FC/metabolism coupling in maintaining network integrity and suggests that its disruption may lead to progressive breakdown of the SN, contributing to the functional deficits characteristic of the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".