Functional and spatial segregation within the inferior frontal and superior temporal cortices during listening, articulation imagery, and production of vowels

Abstract

Classical models of language localize speech perception in the left superior temporal and production in the inferior frontal cortex. Nonetheless, neuropsychological, structural and functional studies have questioned such subdivision, suggesting an interwoven organization of the speech function within these cortices. We tested whether sub-regions within frontal and temporal speech-related areas retain specific phonological representations during both perception and production. Using functional magnetic resonance imaging and multivoxel pattern analysis, we showed functional and spatial segregation across the left fronto-temporal cortex during listening, imagery and production of vowels. In accordance with classical models of language and evidence from functional studies, the inferior frontal and superior temporal cortices discriminated among perceived and produced vowels respectively, also engaging in the non-classical, alternative function – i.e. perception in the inferior frontal and production in the superior temporal cortex. Crucially, though, contiguous and non-overlapping sub-regions within these hubs performed either the classical or non-classical function, the latter also representing non-linguistic sounds (i.e., pure tones). Extending previous results and in line with integration theories, our findings not only demonstrate that sensitivity to speech listening exists in production-related regions and vice versa, but they also suggest that the nature of such interwoven organisation is built upon low-level perception.

Formant Space Reconstruction From Brain Activity in Frontal and Temporal Regions Coding for Heard Vowels

“…In a previous study, we sought to decode model-free information content from regions involved in vowel listening, imagery and production, and in tone perception (Rampinini et al, 2017). Using four searchlight classifiers of fMRI data, we extracted a set of regions performing above-chance classification of seven vowels or tones in each task.…”

“…Moreover, by dividing the minimum/maximum average F1 range of the vowel set into seven bins, we also selected seven pure tones (450, 840, 1370, 1850, 2150, 2500, 2900 Hz), whose frequencies in Hertz were converted first to the closest Bark scale value, and then back to Hertz: this way, pure tones were made to fall into psychophysical sensitive bands for auditory perception. Then, pure tones were generated in Audacity (©Audacity Team, 2 ; see Rampinini et al, 2017 for further details).…”

“…Functional MRI data were preprocessed using the AFNI software package, by performing temporal alignment of all acquired slices within each volume, head motion correction, spatial smoothing (4 mm FWHM Gaussian filter) and normalization. We then identified stimulus-related BOLD patterns by means of multiple linear regression, including movement parameters and signal trends as regressors of no interest (Rampinini et al, 2017). In FSL (Smith et al, 2004; Jenkinson et al, 2012) T -value maps of BOLD activity related to auditory stimulation (vowels, tones) or task execution (imagery, production) were warped to the Montreal Neurological Institute (MNI) standard space, according to a deformation field provided by the non-linear registration of T1 images of the same standards.…”

“…In our previous study, this dataset was analyzed to uncover brain regions involved in the discrimination of the four sets of stimuli. 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). Moreover, accuracies emerging from the tone perception classifier had been used to measure sensitivity to low-level features of acoustic stimuli within regions identified by the vowel classifiers.…”

“…In a previous study, a searchlight classifier on fMRI data obtained during listening, imagery and production of the seven Italian vowels, revealed that both the temporal and frontal hubs are sensitive to perception and production, each engaging in their classical, as well as non-classical function (Rampinini et al, 2017). Particularly, though, vowel-specific information was decoded in a spatially and functionally segregated fashion: in the inferior frontal cortex, adjoining regions engaged in vowel production, motor imagery and listening along a postero-anterior axis; in the superior temporal cortex, the same pattern was observed when information relative to perception and motor imagery of vowels was mapped by adjoining regions.…”