Abstract

Classical studies have isolated a distributed network of temporal and frontal areas engaged in the neural representation of speech perception and production. With modern literature arguing against unique roles for these cortical regions, different theories have favored either neural code-sharing or cortical space-sharing, thus trying to explain the intertwined spatial and functional organization of motor and acoustic components across the fronto-temporal cortical network. In this context, the focus of attention has recently shifted toward specific model fitting, aimed at motor and/or acoustic space reconstruction in brain activity within the language network. Here, we tested a model based on acoustic properties (formants), and one based on motor properties (articulation parameters), where model-free decoding of evoked fMRI activity during perception, imagery, and production of vowels had been successful. Results revealed that phonological information organizes around formant structure during the perception of vowels; interestingly, such a model was reconstructed in a broad temporal region, outside of the primary auditory cortex, but also in the pars triangularis of the left inferior frontal gyrus. Conversely, articulatory features were not associated with brain activity in these regions. Overall, our results call for a degree of interdependence based on acoustic information, between the frontal and temporal ends of the language network.

Highlights

  • Classical models of language have long proposed a relatively clear subdivision of tasks between the inferior frontal and the superior temporal cortices, ascribing them to production and perception respectively (Damasio and Geschwind, 1984; Gernsbacher and Kaschak, 2003)

  • Using a multivariate decoding approach based on four searchlight classifiers (Kriegeskorte et al, 2006; Rampinini et al, 2017), we identified, within a pre-defined mask of language-sensitive cortex from the Neurosynth database (Yarkoni et al, 2011), a set of regions discriminating among seven classes of stimuli: the seven tones in the tone perception task and the seven vowels in the listening, imagery and production tasks (p < 0.05, corrected for multiple comparisons; see Figure 1)

  • We correlated the formant and articulatory models to brain activity in a region-to-task fashion, i.e., vowel listening activity in vowel listening regions, imagery activity in imagery regions, and production activity in production regions; we correlated the models to brain activity from each task, in regions pertaining to all the other tasks

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Summary

Introduction

Classical models of language have long proposed a relatively clear subdivision of tasks between the inferior frontal and the superior temporal cortices, ascribing them to production and perception respectively (Damasio and Geschwind, 1984; Gernsbacher and Kaschak, 2003). Classical theories propose that, on one hand, perception of speech is organized around the primary auditory cortex in Heschl’s gyrus, borrowing a large patch of superior and middle temporal regions (Price, 2012); on the other hand, production would be coordinated by an area of the inferior frontal cortex, ranging from the ventral bank of the precentral gyrus toward the Formant Reconstruction in Brain Activity pars opercularis and the pars triangularis of the inferior frontal gyrus, the inferior frontal sulcus, and, more medially, the insular cortex (Penfield and Roberts, 1959) This subdivision, coming historically from neuropsychological evidence of speech disturbances (Poeppel and Hickok, 2004), makes sense when considering that the two hubs are organized around an auditory and a motor pivot (Heschl’s gyrus and the face-mouth area in the ventral precentral gyrus), the issue of their exact involvement already surfaced at the dawn of modern neuroscience (Cole and Cole, 1971; Boller, 1978). Cytoarchitecture, connectivity and receptor mapping results do suggest a fine-grained parcellation of frontal and temporal cortical regions responsible for speech (Catani and Jones, 2005; Anwander et al, 2006; Fullerton and Pandya, 2007; Hagmann et al, 2008; Amunts et al, 2010; Amunts and Zilles, 2012)

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