What question did this study set out to answer?

To examine how morphological inflections shape syntactic network topology by comparing word-form and lemma networks derived from connected speech in individuals with probable Alzheimer's disease and healthy controls.

September 18, 2026Seminars in Speech and Language

Word-Form and Lemma Dependency Networks of Connected Speech in Probable Alzheimer's Disease: Morphological Impacts on Syntactic Topological Metrics

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HSHongyan Shi

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Overview

Case-control study reveals altered speech network topology in probable Alzheimer's disease, indicating potential quantitative syntactic biomarkers for cognitive impairment.

Key Points

To examine how morphological inflections shape syntactic network topology by comparing word-form and lemma networks derived from connected speech in individuals with probable Alzheimer's disease and healthy controls.
Gathered spontaneous language samples via the Cookie Theft picture description task from 68 individuals with probable Alzheimer's disease and 68 healthy controls.
Constructed word-form and lemma dependency networks for each participant and calculated topological metrics including node and edge counts, average degree, density, clustering coefficients, and path length.
Both groups exhibited small-world network properties, but only healthy control networks adhered to scale-free rules, whereas patient networks deviated slightly.
Healthy controls demonstrated greater node and edge counts, whereas patient networks showed higher density and clustering coefficients, with significant topological differences displaying modest effect sizes (r = 0.21–0.29).
Intergroup differences in average degree were restricted to lemma networks (higher in controls), while average path length and network diameter were similar across groups.

Cite This Study

Hongyan Shi (2026) studied this question.

synapsesocial.com/papers/6aad0bfcde0393d728b8a868 https://doi.org/10.1055/a-2954-9654

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September 18, 2026Seminars in Speech and Language

Word-Form and Lemma Dependency Networks of Connected Speech in Probable Alzheimer's Disease: Morphological Impacts on Syntactic Topological Metrics

View Full Paper

Ask AI

Bookmark

Authors

HSHongyan Shi

Discussion

Member takes

Overview

Case-control study reveals altered speech network topology in probable Alzheimer's disease, indicating potential quantitative syntactic biomarkers for cognitive impairment.

Key Points

To examine how morphological inflections shape syntactic network topology by comparing word-form and lemma networks derived from connected speech in individuals with probable Alzheimer's disease and healthy controls.
Gathered spontaneous language samples via the Cookie Theft picture description task from 68 individuals with probable Alzheimer's disease and 68 healthy controls.
Constructed word-form and lemma dependency networks for each participant and calculated topological metrics including node and edge counts, average degree, density, clustering coefficients, and path length.
Both groups exhibited small-world network properties, but only healthy control networks adhered to scale-free rules, whereas patient networks deviated slightly.
Healthy controls demonstrated greater node and edge counts, whereas patient networks showed higher density and clustering coefficients, with significant topological differences displaying modest effect sizes (r = 0.21–0.29).
Intergroup differences in average degree were restricted to lemma networks (higher in controls), while average path length and network diameter were similar across groups.

Cite This Study

Hongyan Shi (2026) studied this question.

synapsesocial.com/papers/6aad0bfcde0393d728b8a868 https://doi.org/10.1055/a-2954-9654

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