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      When sentences live up to your expectations.

      1 , 2

      NeuroImage

      Elsevier BV

      Predictive coding, Priming, Speech intelligibility, Speech recognition

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          Abstract

          Speech recognition is rapid, automatic and amazingly robust. How the brain is able to decode speech from noisy acoustic inputs is unknown. We show that the brain recognizes speech by integrating bottom-up acoustic signals with top-down predictions. Subjects listened to intelligible normal and unintelligible fine structure speech that lacked the predictability of the temporal envelope and did not enable access to higher linguistic representations. Their top-down predictions were manipulated using priming. Activation for unintelligible fine structure speech was confined to primary auditory cortices, but propagated into posterior middle temporal areas when fine structure speech was made intelligible by top-down predictions. By contrast, normal speech engaged posterior middle temporal areas irrespective of subjects' predictions. Critically, when speech violated subjects' expectations, activation increases in anterior temporal gyri/sulci signalled a prediction error and the need for new semantic integration. In line with predictive coding, our findings compellingly demonstrate that top-down predictions determine whether and how the brain translates bottom-up acoustic inputs into intelligible speech.

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          Author and article information

          Journal
          Neuroimage
          NeuroImage
          Elsevier BV
          1095-9572
          1053-8119
          Jan 01 2016
          : 124
          : Pt A
          Affiliations
          [1 ] Max-Planck-Institute for Biological Cybernetics, 72076 Tuebingen, Germany. Electronic address: johannes.tuennerhoff@tuebingen.mpg.de.
          [2 ] Max-Planck-Institute for Biological Cybernetics, 72076 Tuebingen, Germany; Computational Neuroscience and Cognitive Robotics Centre, Department of Psychology, University of Birmingham, Birmingham B15 2TT, UK.
          Article
          S1053-8119(15)00801-0
          10.1016/j.neuroimage.2015.09.004
          26363344

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