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From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination
Rosanna De Meo1, Nathalie M-P Bourquin1, Jean-François Knebel2
1Neuropsychology and Neurorehabilitation Service, Department of Clinical Neurosciences, Vaudois University Hospital Center and University of Lausanne, 1011 Lausanne, Switzerland.
Learning to identify specific birdsongs enhances auditory processing in the brain. Expertise sharpens neural networks involved in sound discrimination, enabling faster recognition of trained species.
Area of Science:
- Neuroscience
- Auditory Perception
- Cognitive Psychology
Background:
- Environmental sound recognition involves hierarchical discrimination from broad to narrow categories.
- Neural mechanisms of fine-grained auditory discrimination and expertise-related plasticity remain largely unknown.
Purpose of the Study:
- To investigate how cortical sound representation is modulated by brief training in recognizing individual birdsongs.
- To examine the neural processes underlying fine-grained discrimination within narrow auditory categories.
Main Methods:
- Participants underwent a 60-minute birdsong recognition training session.
- Auditory evoked potentials (AEPs) were recorded pre- and post-training.
- Performance for trained (T) and control (C) species was compared.
Main Results:
- Significant differences in AEPs between T and C species were observed in specific brain regions (superior temporal gyrus, middle frontal gyrus, middle temporal gyrus, cingulate cortex) post-training.
- Activity was weaker for trained species, suggesting sharpened neural processing.
- Training improved recognition of T species but influenced C species processing at a later stage.
Conclusions:
- Expertise in discriminating trained birdsongs modulates early semantic processing, sharpening a left-lateralized semantic network.
- Auditory semantic access differs based on expertise level, with trained stimuli processed earlier.
- Untrained sound discrimination involves later-stage processing, potentially requiring additional feature analysis.
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