P1‐413: REPEATED EXPOSURE TO FAMILIAR MUSIC ALTERS FUNCTIONAL CONNECTIVITY IN ALZHEIMER'S DISEASE
Bibliographic record
Abstract
Music-based interventions have demonstrated to improve behaviour and cognition for Alzheimer's disease (AD) persons. AD is characterised by disruption of resting-state networks, particularly decreased functional connectivity within the Default Mode Network (DMN). Neuroimaging studies in healthy controls suggest music exposure elicits functional connectivity changes in areas involved in cognition, including the DMN. Our study is the first to use neuroimaging to determine whether daily exposure to long-known music can alter functional brain connectivity (FC) and improve cognitive outcomes in persons with Mild Cognitive Impairment (MCI) and early AD. We recruited 11 persons with MCI or early AD (Table 1). Prior to participation, participants were asked about their music listening habits and music known to them for minimum 20 years. Participants completed a three-week at-home MI where they listened to a playlist of long-known music created for them for 1h/day on an MP3 player. Compliance was tracked with a daily log completed by the participant and validated by a spouse or caregiver. Participants visited St Michael's Hospital once before MI initiation and at MI completion. Each session included cognitive testing (Montreal Cognitive Assessment (MoCA)) and resting-state fMRI. Compared to pre-MI scans, analysis found whole-brain significant differences in FC post-MI (Figure 1). Repeated exposure to music showed a trend toward decreased FC outside the DMN. Increased FC was found within the DMN, including between the medial prefrontal cortex and inferior parietal lobule. Additionally, increases in FC were found in areas involved in emotion processing such as within the orbitofrontal cortex and between the amygdala and cerebellum. Although non-significant, cognitive scores increased post-MI (Table 2). Axial (a) and sagittal (b) brain maps showing significant changes in functional connectivity pre- and post-MI (Bonferroni correction = 0.01). Our study is first to provide empirical evidence that a structured listening regiment to long-known music accessing long-term musical memory systems can change brain FC in persons developing AD. Specifically, long-known music can increase FC in the DMN, a network found to have decreased FC in AD and is implicated in cognitive functioning, as well as emotion processing areas. These results give preliminary insight into the plasticity mechanisms by which music may modulate emotional and executive networks to improve cognition and behaviour in AD.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".