Age-Related Diversification and Specialization in the Mental Lexicon: Comparing Aggregate and Individual-Level...

Area of Science:

• Cognitive psychology
• Psycholinguistics
• Neuroscience

Background:

• The mental lexicon, representing word knowledge, changes throughout life.
• Previous studies using aggregated data suggest lexical networks become sparser with age (decreased degree and clustering, increased path length).
• It remains unclear if individual lexicons follow the same age-related patterns observed in aggregated data.

Purpose of the Study:

• To investigate age-related changes in the mental lexicon at an individual level.
• To compare individual-level lexical network analysis with traditional aggregate-level approaches.
• To reveal age-specific differences in lexical structure and organization.

Main Methods:

• Developed an individual-level approach to analyze lexical networks within a population-level conglomerate network.
• Compared network properties (degree, clustering coefficient, path length) across different age groups.
• Examined lexical data from three languages: English, Spanish, and Dutch.

Main Results:

• Individual-level analysis revealed that older adults exhibit a higher clustering coefficient in their lexical networks, suggesting more specialized knowledge.
• A reduction in degree alongside increased clustering indicates a shift towards specialized but interconnected knowledge with age.
• Older individuals showed increased distances between associates, indicating a broader range of associations.
• These qualitative patterns were consistent across English, Spanish, and Dutch.

Conclusions:

• Individual-level analysis provides nuanced insights into the aging mental lexicon, complementing aggregate-level findings.
• Lexical networks become more specialized and diverse with age, challenging previous assumptions based solely on aggregated data.
• The study highlights the utility of individual-level network approaches for understanding cognitive changes across the lifespan.