Effects of Complex Speech Sound Systems on Language-Dependent Auditory Plasticity
- Institution
- University of Texas at Austin, TX
- Principal investigator
- Fernando Llanos Lucas
- Funding
- $353K
- Duration
- 2025–2028
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Abstract
To understand speech, the brain must quickly sort through a stream of changing sounds and identify the patterns that carry meaning. This ability is shaped by experience, as sounds that are easily recognized by individuals with significant exposure to a language may go unnoticed by individuals without that exposure. Over time, the auditory system adapts by reorganizing how it processes and prioritizes important sound features. This fine-tuning allows the brain to efficiently extract the sound patterns most relevant for communication. Understanding how these neural changes occur is essential for building more accurate models of auditory processing and for developing brain-based tools for clinical diagnostics, neurobiometric identification, and brain-computer interfaces. This project examines how long-term experience with different speech environments shapes both perception and brain activity. Using auditory perception tasks and non-invasive brain recordings, the study compares how speakers of languages with different levels of sound complexity perceive and process key speech features. Artificial intelligence techniques are used to identify reliable neural markers of language-specific and general auditory processing and to model how the auditory system adjusts to familiar and unfamiliar sounds. This work advances our current understanding of the factors that shape auditory processing, has the potential to update current models of auditory neuroplasticity, and supports the development of brain-based technologies focused on auditory function. The project also provides hands-on research experience for both graduate and undergraduate students, helping to train the next generation of scientists. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Fernando Llanos LucasPI
- Daniel Law
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