Rhythmicity and cross-modal temporal cues facilitate detection

Sanne ten Oever, Charles E. Schroeder, David Poeppel, Nienke van Atteveldt, Elana Zion-Golumbic

Research output: Contribution to journalArticlepeer-review

Abstract

Temporal structure in the environment often has predictive value for anticipating the occurrence of forthcoming events. In this study we investigated the influence of two types of predictive temporal information on the perception of near-threshold auditory stimuli: 1) intrinsic temporal rhythmicity within an auditory stimulus stream and 2) temporally-predictive visual cues. We hypothesized that combining predictive temporal information within- and across-modality should decrease the threshold at which sounds are detected, beyond the advantage provided by each information source alone. Two experiments were conducted in which participants had to detect tones in noise. Tones were presented in either rhythmic or random sequences and were preceded by a temporally predictive visual signal in half of the trials. We show that detection intensities are lower for rhythmic (vs. random) and audiovisual (vs. auditory-only) presentation, independent from response bias, and that this effect is even greater for rhythmic audiovisual presentation. These results suggest that both types of temporal information are used to optimally process sounds that occur at expected points in time (resulting in enhanced detection), and that multiple temporal cues are combined to improve temporal estimates. Our findings underscore the flexibility and proactivity of the perceptual system which uses within- and across-modality temporal cues to anticipate upcoming events and process them optimally.

Original languageEnglish (US)
Pages (from-to)43-50
Number of pages8
JournalNeuropsychologia
Volume63
Issue number1
DOIs
StatePublished - Oct 2014

Keywords

  • Audiovisual integration
  • Detection
  • Rhythmicity
  • Temporal prediction

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Behavioral Neuroscience

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