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  A division of labor between power and phase coherence in encoding attention to stimulus streams

Tavano, A., & Poeppel, D. (2019). A division of labor between power and phase coherence in encoding attention to stimulus streams. NeuroImage, 193, 146-156. doi:10.1016/j.neuroimage.2019.03.018.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-3702-D Version Permalink: http://hdl.handle.net/21.11116/0000-0003-3703-C
Genre: Journal Article

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 Creators:
Tavano, Alessandro1, Author              
Poeppel, David1, 2, Author              
Affiliations:
1Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, ou_2421697              
2Department of Psychology, New York University, 6 Washington Pl., 10003, New York City, New York, USA, ou_persistent22              

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Free keywords: Attention Deviancy Oscillation Phase coherence Reaction time
 Abstract: Both time-based (when) and feature-based (what) aspects of attention facilitate behavior, so it is natural to hypothesize additive effects. We tested this conjecture by recording response behavior and electroencephalographic (EEG) data to auditory pitch changes, embedded at different time lags in a continuous sound stream. Participants reacted more rapidly to larger rather than smaller feature change magnitudes (deviancy), as well as to changes appearing after longer rather than shorter waiting times (hazard rate of response times). However, the feature and time dimensions of attention separately contributed to response speed, with no significant interaction. Notably, phase coherence at low frequencies (delta and theta bands, 1–7 Hz) predominantly reflected attention capture by feature changes, while oscillatory power at higher frequency bands, alpha (8–12 Hz) and beta (13–25 Hz) reflected the orienting of attention in time. Power and phase coherence predicted different portions of response speed variance, suggesting a division of labor in encoding sensory attention in complex auditory scenes.

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Language(s): eng - English
 Dates: 2019-02-202018-11-302018-03-082019-03-122019-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2019.03.018
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: San Diego, Calif. : Elsevier
Pages: - Volume / Issue: 193 Sequence Number: - Start / End Page: 146 - 156 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166