Trajectory of olfactory cortex degeneration from normal cognition to Alzheimer's disease: Insights from multimodal neuroimaging
Bibliographic record
Abstract
The olfactory cortex is among the earliest brain regions affected by Alzheimer's disease (AD), with olfactory deficits frequently preceding cognitive decline. This study aimed to characterize the functional and structural degeneration trajectory of the olfactory cortex from normal cognition (NC) to mild cognitive impairment (MCI) and eventually to AD using multimodal neuroimaging techniques. A total of 105 participants (28 with NC, 35 with MCI, and 42 with AD) were subjected to olfactory [University of Pennsylvania Smell Identification Test (UPSIT)] and cognitive [e.g., Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA)] assessments. This was followed by olfactory task–based functional magnetic resonance imaging (fMRI; olfactory activation), resting-state fMRI [amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo)], and structural MRI [gray matter volume (GMV) and white matter volume (WMV)] in 12 olfactory-related regions of interest. Group comparisons using one-way analysis of variance/Kruskal–Wallis and multivariate logistic regression analyses were performed to identify stage-specific imaging biomarkers and evaluate diagnostic performance. From the NC to MCI and then to AD groups, a consistent pattern of declining olfactory activation values, GMV, and WMV, coupled with increased ALFF and ReHo in olfactory subregions, was observed. Moreover, corresponding decreases in olfactory and cognitive scores were noted. Our multivariate logistic regression models yielded the following classification performance: NC versus MCI [right primary olfactory cortex (POC) olfactory activation, right insula olfactory activation, left POC GMV, left insula ReHo, right amygdala ALFF, and MMSE scores] achieved 90.5 % accuracy; MCI versus AD (left hippocampal GMV, left insula ReHo, and MMSE scores) reached 94.8 % accuracy; and NC versus AD (left hippocampal GMV and UPSIT scores) achieved 92.9 % accuracy. Our findings delineate a spatiotemporal progression of olfactory cortex degeneration, with early POC alterations in MCI evolving into widespread atrophy and functional dysregulation in AD. Multimodal MRI metrics and logistic modeling yield highly accurate stage classification, underscoring their potential as sensitive biomarkers for early AD detection and monitoring. • Integration of olfactory task–based functional magnetic resonance imaging (fMRI), resting-state fMRI, and structural MRI systematically traces the trajectory of olfactory cortex degeneration from normal cognition to mild cognitive impairment and eventually to Alzheimer's disease (AD). • Multivariate logistic regression models combining clinical and imaging metrics yielded exceptional diagnostic accuracy (90.5 %–94.8 %), demonstrating the clinical potential of olfactory-based biomarkers. • Early degeneration in the primary olfactory cortex offers measurable changes, supporting its role as a sensitive imaging biomarker for the early detection of AD.
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 | 0.000 |
| 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) | 0.000 | 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".