Neural prediction of higher-order auditory sequence statistics

Furl, N. and Kumar, S. and Alter, K. and Durrant, Simon and Shawe-Taylor, J. and Griffiths, T. D. (2011) Neural prediction of higher-order auditory sequence statistics. Neuroimage, 54 (3). pp. 2267-2277. ISSN 1053-8119

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Neural prediction of higher-order auditory sequence statistics
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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 uniformfirstorder
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.

Item Type:Article
Additional Information: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 uniformfirstorder 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.
Keywords:Magnetoencephalography (MEG), Predictive coding, Temporoparietal junction (TPJ), Statistical learning
Subjects:C Biological Sciences > C800 Psychology
C Biological Sciences > C850 Cognitive Psychology
C Biological Sciences > C860 Neuropsychology
Divisions:College of Social Science > School of Psychology
ID Code:4720
Deposited By: Alison Wilson
Deposited On:11 Oct 2011 15:52
Last Modified:13 Mar 2013 09:02

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