Neurophysiological, linguistic, and cognitive predictors of children’s ability to perceive speech in noise

• Main Authors: Elaine C. Thompson, Jennifer Krizman, Travis White-Schwoch, Trent Nicol, Ryne Estabrook, Nina Kraus
• Format: Article
• Language: English
• Published: Elsevier 2019-10-01
• Series: Developmental Cognitive Neuroscience
• Online Access: http://www.sciencedirect.com/science/article/pii/S1878929318301816

Hearing in noisy environments is a complicated task that engages attention, memory, linguistic knowledge, and precise auditory-neurophysiological processing of sound. Accumulating evidence in school-aged children and adults suggests these mechanisms vary with the task’s demands. For instance, co-located speech and noise demands a large cognitive load and recruits working memory, while spatially separating speech and noise diminishes this load and draws on alternative skills. Past research has focused on one or two mechanisms underlying speech-in-noise perception in isolation; few studies have considered multiple factors in tandem, or how they interact during critical developmental years. This project sought to test complementary hypotheses involving neurophysiological, cognitive, and linguistic processes supporting speech-in-noise perception in young children under different masking conditions (co-located, spatially separated). Structural equation modeling was used to identify latent constructs and examine their contributions as predictors. Results reveal cognitive and language skills operate as a single factor supporting speech-in-noise perception under different masking conditions. While neural coding of the F0 supports perception in both co-located and spatially separated conditions, neural timing predicts perception of spatially separated listening exclusively. Together, these results suggest co-located and spatially separated speech-in-noise perception draw on similar cognitive/linguistic skills, but distinct neural factors, in early childhood. Keywords: Auditory development, Speech-in-noise perception, Auditory processing, Electrophysiology, FFR, Cognition, Language, Structural equation modeling