Articulation as a Predictor of Cognitive Decline
Bibliographic record
Abstract
Background: Speech production is facilitated by motor neural networks that are proximal to neural substrates of general cognitive functions in the frontal lobe. However, the precise relationship between these brain networks supporting articulatory control and more general cognitive functioning has not been determined. A relation may be expected due to the anatomical proximity of specific networks, or due to more global aspects of brain health in individuals, affecting cognitive and motor functions across the board. Lower motor function is expected to affect the stability of speech production, but the extent to which this is also associated with lower cognitive functioning remains unclear. If a strong relation exists, sensitive measures of speech motor control could be used for early detection or prediction of cognitive decline in healthy aging adults. Aims: The aims of this study were to assess to what extent cognitive function is predicted by (1) articulatory stability and (2) fine and gross non-speech motor control. Methods & Procedures: Vowel formant data were collected from a word-reading task in 170 healthy adults ages 20-80. The first three formants were extracted from monosyllabic target word utterances and used to compute each participant’s formant variance. Cognition was measured with the Montreal Cognitive Assessment (MoCA). Non-speech motor control was assessed through peg dexterity (fine control), grip strength (fine and gross), and 4-meter walking stability (gross control). A stepwise linear regression model was used to determine relations between cognitive and motor assessment scores and vowel production variance, accounting for effects of age, sex, race, socio-economic status, and education. Outcomes & Results: The final regression model was statistically significant, F(6, 163) = 18.23, p< .001, with an R2 of 0.4016, indicating that approximately 40.16% of the variance in the MoCA total score can be explained by the model. Lower cognitive ability was significantly predicted by variance in the second formant (ß = -0.28, t(163) = -2.42, p = .016), suggesting that articulatory instability is linked to cognitive function. Additionally, a non-significant trend was observed for peg dexterity (ß = 0.11, t(163) = 1.80, p = .073), indicating that individuals with lower fine motor control may also show lower cognitive scores. Gross motor abilities, however, showed no associations with cognition. Conclusions: These findings provide evidence of a relation between cognitive function and speech production, particularly in relation to articulatory precision. The observed weaker link between fine motor dexterity and cognition suggests a more general relation between cognition and fine motor control. The strong association between vowel variability and cognitive performance suggests that sensitive and fine-grained speech-based measures, such as vowel formant dispersion, may be useful for the early detection of subtle cognitive decline in healthy adults.
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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 | 0.000 |
| 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) | 0.000 | 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".