When attention matters: Domain-specific disruption of explicit but not implicit memory in statistical learning

Area of Science:

• Cognitive Psychology
• Neuroscience
• Linguistics

Background:

• Statistical learning (SL) is crucial for language acquisition.
• The influence of attention on SL, particularly domain-specific vs. domain-general resources, remains unclear.

Purpose of the Study:

• To investigate whether top-down attention affects statistical learning.
• To determine if attention's influence on SL depends on domain-specific or domain-general resources.

Main Methods:

• Participants listened to statistical structures (syllables forming words) under attentional manipulations.
• Attentional conditions included competing visuospatial (domain-general) and linguistic (domain-specific) tasks.
• Statistical learning was assessed via explicit familiarity ratings and implicit reaction-time tasks.

Main Results:

• Explicit statistical learning was impaired only when domain-specific (linguistic) attention was divided.
• Implicit statistical learning remained robust across all attentional conditions, including divided attention.
• Performance on both explicit and implicit measures stayed above chance even with concurrent linguistic tasks.

Conclusions:

• Explicit memory for statistical regularities is sensitive to domain-specific attentional load.
• Implicit statistical learning is resilient to attentional limitations, whether domain-specific or general.
• Language learners can acquire statistical properties of language even while multitasking.