title: Influence of the interstimulus interval on temporal processing and learning: testing the state-dependent network model.
abstract: The ability to determine the interval and duration of sensory events is fundamental to most forms of sensory processing, including speech and music perception. Recent experimental data support the notion that different mechanisms underlie temporal processing in the subsecond and suprasecond range. Here, we examine the predictions of one class of subsecond timing models: state-dependent networks. We establish that the interval between the comparison and the test interval, interstimulus interval (ISI), in a two-interval forced-choice discrimination task, alters the accuracy of interval discrimination but not the point of subjective equality-i.e. while timing was impaired, subjective time contraction or expansion was not observed. We also examined whether the deficit in temporal processing produced by short ISIs can be reduced by learning, and determined the generalization patterns. These results show that training subjects on a task using a short or long ISI produces dramatically different generalization patterns, suggesting different forms of perceptual learning are being engaged. Together, our results are consistent with the notion that timing in the range of hundreds of milliseconds is local as opposed to centralized, and that rapid stimulus presentation rates impair temporal discrimination. This interference is, however, decreased if the stimuli are presented to different sensory channels.
authors.affiliation: Brain Research Institute, Department of Neurobiology, University of California-Los Angeles, Los Angeles, CA 90095, USA. dbuono@ucla.edu
authors.forename: Dean V
authors.initials: DV
authors.lastname: Buonomano
authors.forename: Jennifer
authors.initials: J
authors.lastname: Bramen
authors.forename: Mahsa
authors.initials: M
authors.lastname: Khodadadifar
mesh_terms: D000818:Animals; D004192:Discrimination, Psychological / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology*; D008959:Models, Neurological; D016571:Neural Networks, Computer; D013998:Time Perception / Q000502:physiology*