Journal article
Neural prediction of higher-order auditory sequence statistics
NeuroImage (Orlando, Fla.), Vol.54(3), pp.2267-2277
02/01/2011
DOI: 10.1016/j.neuroimage.2010.10.038
PMID: 20970510
Abstract
During auditory perception, we are required to abstract information from complex temporal sequences such as those in music and speech. Here, we investigated how higher-order statistics modulate the neural responses to sound sequences, hypothesizing that these modulations are associated with higher levels of the peri-Sylvian auditory hierarchy. We devised second-order Markov sequences of pure tones with uniform first-order transition probabilities. Participants learned to discriminate these sequences from random ones. Magnetoencephalography was used to identify evoked fields in which second-order transition probabilities were encoded. We show that improbable tones evoked heightened neural responses after 200 ms post-tone onset during exposure at the learning stage or around 150 ms during the subsequent test stage, originating near the right temporoparietal junction. These signal changes reflected higher-order statistical learning, which can contribute to the perception of natural sounds with hierarchical structures. We propose that our results reflect hierarchical predictive representations, which can contribute to the experiences of speech and music. Published by Elsevier Inc.
Details
- Title: Subtitle
- Neural prediction of higher-order auditory sequence statistics
- Creators
- Nicholas Furl - University College LondonSukhbinder Kumar - Newcastle UniversityKai Alter - Newcastle UniversitySimon Durrant - University of ManchesterJohn Shawe-Taylor - University College LondonTimothy D. Griffiths - University of Newcastle Australia
- Resource Type
- Journal article
- Publication Details
- NeuroImage (Orlando, Fla.), Vol.54(3), pp.2267-2277
- Publisher
- Elsevier
- DOI
- 10.1016/j.neuroimage.2010.10.038
- PMID
- 20970510
- ISSN
- 1053-8119
- eISSN
- 1095-9572
- Number of pages
- 11
- Grant note
- EP/D063612/1 / Engineering and Physical Sciences Research Council; UK Research & Innovation (UKRI); Engineering & Physical Sciences Research Council (EPSRC) EP/D063612/1 / United Kingdom Engineering and Physical Sciences Research Council; UK Research & Innovation (UKRI); Engineering & Physical Sciences Research Council (EPSRC) EP/D063612/1 / EPSRC; UK Research & Innovation (UKRI); Engineering & Physical Sciences Research Council (EPSRC)
- Language
- English
- Date published
- 02/01/2011
- Academic Unit
- Psychological and Brain Sciences; Neurosurgery
- Record Identifier
- 9984303911602771
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