The sensory encoding of the duration, interval, and order of different stimulus features provides vital information to the nervous system. The present study focuses on the influence of practice on auditory temporal–interval discrimination. The goals of the experiment were to determine (1) whether practice improved the ability to discriminate a standard interval of 100 msec bounded by brief 1 kHz tones from longer intervals, and, if so, (2) whether this improvement generalized to different tonal frequencies or temporal intervals. Learning was examined in 14 human subjects using an adaptive, two-alternative, forced-choice procedure. One hour of training per day for 10 d led to marked improvements in the ability to discriminate between the standard and longer intervals. The generalization of learning was evaluated by independently varying the spectral (tonal frequency) and temporal (interval) components of the stimuli in four conditions tested both before and after the training phase. Remarkably, there was complete generalization to the trained interval of 100 msec bounded by tones at the untrained frequency of 4 kHz, but no generalization to the untrained intervals of 50, 200, or 500 msec bounded by tones at the trained frequency of 1 kHz. Thus, these data show that (1) temporal–interval discrimination using a 100-msec standard undergoes perceptual learning, and (2) the neural mechanisms underlying this learning are temporally, but not spectrally, specific. These results are compared with those from previous investigations of learning in visual spatial tasks, and are discussed in relation to biologically plausible models of temporal processing.
Learning and Generalization of Auditory Temporal–Interval Discrimination in Humans
B. Wright,D. Buonomano,H. Mahncke,M. Merzenich
Published 1997 in Journal of Neuroscience
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PUBLICATION RECORD
- Publication year
1997
- Venue
Journal of Neuroscience
- Publication date
1997-05-15
- Fields of study
Mathematics, Medicine, Psychology
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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