Decreased Audio‐Visual Network Integration Mediates Amyloid‐related Tau Spreading
Bibliographic record
Abstract
Abstract Background Growing evidence indicates that the coexistence of visual and auditory impairments increases the risk of developing Alzheimer's disease (AD). However, the mechanisms through which these sensory deficits influence the progression of AD, particularly their impact on amyloid and tau pathology, remain unclear. We hypothesize that alterations in the audio‐visual dynamic network play a critical role in mediating the spread of amyloid‐related tau pathology during the early stages of AD. Method This study included multimodal imaging data, including functional MRI, [ 18 F]NAV4694 amyloid‐PET, and [ 18 F]NAV4694 tau‐PET, from the TRIAD cohort ( n = 216, Table 1). Participants were classified as amyloid‐beta (Aβ) positive (A+) or negative (A−) based on established global uptake values of [ 18 F]NAV4694 (global standardized uptake value ratio [SUVR] > 1.55). Tau positivity (T+) or negativity (T−) was determined using [ 18 F]MK6240, with a temporal meta‐ROI SUVR threshold > 1.30. Tau staging was based upon Braak stage classification. Brain dynamics in resting‐state fMRI data were analyzed with a multilayer modularity algorithm in MATLAB, focusing on primary sensory and higher‐order networks. Result Module allegiance within the auditory network (AN) and visual networks (VN) was lower in the A+T+ group compared to the A−T− group. Additionally, flexibility within the frontoparietal network (FPN) was increased, while recruitment within the FPN and integration between AN and VN were reduced in the A+T+ group compared to A−T− group (Figure 1). Integration between AN and VN negatively correlated with [ 18 F]MK6240 SUVR in Braak stage 1 through 5 and the temporal meta‐ROI, as well as with neocortical [ 18 F]NAV4694 SUVR. Furthermore, AN‐VN integration mediated the relationship between neocortical [ 18 F]NAV4694 SUVR and [ 18 F]MK6240 SUVR in Braak stage 1 and 2 (Figure 2). Conclusion Our study suggests that audio‐visual network integration during the early stages of tau pathology mediates amyloid‐related tau accumulation. This supports a framework in which decline brain network integration may facilitates the early spread of amyloid‐driven tau pathology across interconnected brain regions.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".