Work

Aging modulates large-scale neural network interactions during speech comprehension

Year: 2025

Type: article

Abstract: Speech comprehension in noisy environments constitutes a critical challenge in everyday life and affects people of all ages. This challenging listening situation can be alleviated using semantic context to predict upcoming words (i.e., predictability gain)-a process associated with the domain-specific semantic network. When no such context can be used, speech comprehension in challenging listening conditions relies on cognitive control functions, underpinned by domain-general networks. Most previous studies focused on regional activity of pre-selected cortical regions or networks in healthy young listeners. Thus, it remains unclear how domain-specific and domain-general networks interact during speech comprehension in noise and how this may change across the lifespan. Here, we used correlational psychophysiological interaction (cPPI) to investigate functional network interactions during sentence comprehension under noisy conditions with varying predictability in healthy young and older listeners. Relative to young listeners, older adults showed increased task-related activity in several domain-general networks but reduced between-network connectivity. Across groups, higher predictability was associated with increased positive coupling between semantic and attention networks and increased negative coupling between semantic and control networks. These results highlight the complex interplay between the semantic network and several domain-general networks underlying the predictability gain. The observed differences in connectivity profiles with age inform the current debate on whether age-related changes in neural activity and functional connectivity reflect compensation or dedifferentiation.

Source: Neurobiology of Aging

DOI: 10.1016/j.neurobiolaging.2025.02.005

Authors: Anna Uta Rysop, Kathleen Anne Williams, Lea-Maria Schmitt, Marcus Meinzer, Jonas Obleser, Gesa Hartwigsen