The role of age and executive function in auditory category learning.
Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study was twofold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence and into early adulthood and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. A sample of 60 participants with normal hearing-20 children (age range=7-12years), 21 adolescents (age range=13-19years), and 19 young adults (age range=20-23years)-learned to categorize novel dynamic "ripple" sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied "Gabor" patches in the visual domain. Results reveal that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e., a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning.
Department of Communication Sciences and Disorders, Moody College of Communication, The University of Texas at Austin, Austin, TX 78712, USA.
Rachel
R
Reetzke
Department of Psychology, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA; Institute of Mental Health Research, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA; Institute for Neuroscience, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA; Center for Perceptual Systems, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA.
W Todd
WT
Maddox
Department of Communication Sciences and Disorders, Moody College of Communication, The University of Texas at Austin, Austin, TX 78712, USA; Department of Psychology, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA; Institute of Mental Health Research, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA; Institute for Neuroscience, College of Liberal Arts, The University of Texas at Austin, Austin, TX 78712, USA. Electronic address: bchandra@utexas.edu.
Bharath
B
Chandrasekaran
D000293:Adolescent; D000367:Age Factors; D001288:Attention / Q000502:physiology*; D001307:Auditory Perception / Q000502:physiology*; D002648:Child; D003210:Concept Formation / Q000502:physiology; D056344:Executive Function / Q000502:physiology*; D005246:Feedback; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology; D055815:Young Adult
Category learning; Development; Executive function; Hypothesis-testing; Perceptual processes; Rule-based learning