Neural Basis of Long-term Musical Memory in Cognitively Impaired Older Persons
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine whether exposure to long-known music would evoke more extensive activation of brain regions minimally affected by Alzheimer disease (AD) pathology and outside traditional memory networks using a functional magnetic resonance imaging paradigm involving listening to long-known and recently-learned music in older adults with cognitive impairment to provide insight into mechanisms of long-term musical memory preservation in cognitively impaired older persons. METHODS: Seventeen subjects with a diagnosis of mild AD or mild cognitive impairment were recruited for this study. Subjects were scanned using functional magnetic resonance imaging while they performed a music listening task, which included short clips of personally selected music from the patient's past and newly-composed music heard for the first time 60 minutes before scanning. From this task, we obtained group-level maps comparing brain areas associated with long-known and recently-heard music in all subjects. RESULTS: Exposure to long-known music preferentially activated brain regions including the medial prefrontal cortex, precuneus, anterior insula, basal ganglia, hippocampus, amygdala, and cerebellum relative to recently-heard music. These areas are involved in autobiographical memory and associated emotional responses. In addition, they are minimally affected by early stage AD pathology, thus providing a neural basis for long-known musical memory survival. CONCLUSIONS: Long-known music activates a bilateral network of prefrontal, emotional, motor, auditory, and subcortical regions (cerebellum, putamen, limbic structures). This extensive activation, relative to recently-heard music, may offer structural and functional clues as to why long-term musical memory appears to be relatively preserved among cognitively impaired older persons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".