Distinct Mechanisms of Imagery Differentially Influence Speech Perception.

Journal: eNeuro
Published Date:

Abstract

Neural representation can be induced without external stimulation, such as in mental imagery. Our previous study found that imagined speaking and imagined hearing modulated perceptual neural responses in opposite directions, suggesting motor-to-sensory transformation and memory retrieval as two separate routes that induce auditory representation (Tian and Poeppel, 2013). We hypothesized that the precision of representation induced from different types of speech imagery led to different modulation effects. Specifically, we predicted that the one-to-one mapping between motor and sensory domains established during speech production would evoke a more precise auditory representation in imagined speaking than retrieving the same sounds from memory in imagined hearing. To test this hypothesis, we built the function of representational precision as the modulation of connection strength in a neural network model. The model fitted the magnetoencephalography (MEG) imagery repetition effects, and the best-fitting parameters showed sharper tuning after imagined speaking than imagined hearing, consistent with the representational precision hypothesis. Moreover, this model predicted that different types of speech imagery would affect perception differently. In an imagery-adaptation experiment, the categorization of /ba/-/da/ continuum from male and female human participants showed more positive shifts towards the preceding imagined syllable after imagined speaking than imagined hearing. These consistent simulation and behavioral results support our hypothesis that distinct mechanisms of speech imagery construct auditory representation with varying degrees of precision and differentially influence auditory perception. This study provides a mechanistic connection between neural-level activity and psychophysics that reveals the neural computation of mental imagery.

Authors

  • Ou Ma 马欧
    Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China.
  • Xing Tian 田兴
    Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China xing.tian@nyu.edu.