Association between beta amyloid plaque deposition and neuronal activity measured by Resting‐state fMRI in Alzheimer’s Disease and mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Despite the important role of amyloid‐beta protein (Aβ) in the initiation and progression of Alzheimer’s Disease (AD), the precise mechanism by which Aβ disrupts neuronal activity (NA) and structure during disease development, and whether this protein is an appropriate therapeutic target is still controversial. Recently, we introduced several novel NA metrics (Kazemeifar, PLoS One 2017; Haddad, ISMRM 2019) based on specific spatiotemporal features of the resting‐state fMRI (rs‐fMRI) signal. These NA metrics are significantly lower in AD and mild cognitive impairment (MCI) compared to normal elderly controls. Here, we examine whether there is an association between resting‐state fMRI NA levels and Aβ deposition in grey matter (GM) measured by PET in AD and MCI. Method [18F]florbetapir Aβ PET images and rs‐fMRI data (TR = 3s, 197 volumes) in 9 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, 3 early MCI (EMCI), 3 MCI, and 3 AD, aged 77 ± 7 years, 3 females) were included. The rs‐fMRI data was pre‐processed and decomposed into independent components (ICs) using IC analysis. The ICs associated with neuronal activity were identified using a support vector machine classifier (Demertzi, Cortex 2014). NA was quantified in each voxel using the magnitude of the neuronal ICs in the rs‐fMRI signal. This magnitude was calculated based on similarity (cross‐covariance) between each neuronal IC and rs‐fMRI signal (Haddad, ISMRM 2019). In each subject, the pre‐processed PET images (Jagust, Alzheimers. Dement. 2015) were registered to the T1‐weighted image to which the NA maps were already registered. GM voxelwise correlation was then conducted between the NA and [18F]florbetapir uptake maps in each subject. Result The NA and [18F]florbetapir uptake maps in one EMCI subject (Figure 1) and related scatter plot (Figure 2) show the correlation between NA and [18F]florbetapir uptake in GM. In all subjects studied, NA and [18F]florbetapir uptake were significantly negatively correlated (r = ‐0.25 ± 0.14) (Table 1). Conclusion The negative correlation between NA and [18F]florbetapir uptake in this preliminary study indicates that Aβ deposition contributes to decreased neuronal activity in AD and MCI measured by rs‐fMRI. Future studies should determine the susceptibility of various brain regions to Aβ accumulation.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".