Mapping the dynamic allocation of temporal attention in musical patterns

Many environmental sounds, such as music or speech, are patterned in time. Dynamic attending theory, and supporting empirical evidence, suggests that a stimulus's temporal structure serves to orient attention to specific moments in time. One instantiation of this theory posits that attention sy...

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Bibliographic Details
Main Authors: Fink, L.K (Author), Hurley, B.K (Author), Janata, P. (Author)
Format: Article
Language:English
Published: American Psychological Association Inc. 2018
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Online Access:View Fulltext in Publisher
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Summary:Many environmental sounds, such as music or speech, are patterned in time. Dynamic attending theory, and supporting empirical evidence, suggests that a stimulus's temporal structure serves to orient attention to specific moments in time. One instantiation of this theory posits that attention synchronizes to the temporal structure of a stimulus in an oscillatory fashion, with optimal perception at salient time points or oscillation peaks. We examined whether a model consisting of damped linear oscillators succeeds at predicting temporal attention behavior in rhythmic multi-instrumental music. We conducted 3 experiments in which we mapped listeners' perceptual sensitivity by estimating detection thresholds for intensity deviants embedded at multiple time points within a stimulus pattern. We compared participants' thresholds for detecting intensity changes at various time points with the modeled salience prediction at each of those time points. Across all experiments, results showed that the resonator model predicted listener thresholds, such that listeners were more sensitive to probes at time points corresponding to greater model-predicted salience. This effect held for both intensity increment and decrement probes and for metrically simple and complex stimuli. Moreover, the resonator model explained the data better than did predictions based on canonical metric hierarchy or auditory scene density. Our results offer new insight into the temporal orienting of attention in complex auditory scenes using a parsimonious computational model for predicting attentional dynamics. © 2018 American Psychological Association.
ISBN:00961523 (ISSN)
DOI:10.1037/xhp0000563