Fig 1.
(a) Participants (n = 30) answered to 7 given questions (60 s each; condition #1) as well as listened to audio recordings of their own voice from previous sessions (condition #2) while MEG data was recorded. Amplitude envelope was extracted from the continuous speech signal (see Methods). (b) Artefacts were removed from the recorded MEG data [42]. Individual MRIs were used to estimate source models per participant that were interpolated to a template volumetric grid. Cortical areas were divided into 230 anatomical parcels according to the parcellation from the Human Connectome Project [45]. (c) For each parcel, estimated source time series were extracted and the first 3 SVD components were subjected to multitaper spectral analysis. We then estimated MI between the speech envelope and complex-valued spectral estimates of all 3 time series (I). Next, using a blockwise approach, we considered the first 3 SVD components of each parcel as a block and estimated the connectivity between the LSTG and other parcels using a multivariate nonparametric Granger causality approach (mCG; II) [49]. Finally, we assessed whether there is a relationship between the directed connectivities and the speech-brain couplings using correlation analysis (III). LSTG, left superior temporal gyrus; MEG, magnetoencephalography; MI, mutual information; SVD, singular value decomposition.
Fig 2.
Speech-brain coupling during speaking.
Cortical map represents groups statistics of multivariate MI between speech envelope and brain activity in each parcel compared to 95th percentile of surrogate data. Colour code represents the sum of all significant T-values across delay and frequency (FDR-corrected across delays (−1 to 1 s), frequencies (1 to 10 Hz), and parcels). The data underlying this figure can be found in https://osf.io/9fq47/. MI, mutual information.
Fig 3.
Speech-brain coupling in different brain areas and frequency bins during speaking.
(a) The relative change between summed significant t-values for positive and negative delays. Purple colours indicate areas with higher t-values at negative compared to positive lags, whereas green colours indicate stronger effects for positive lags. (b) The spectrum of the averaged significant t-values across positive (green) and negative (purple) delays, for each frequency bin and for L4 and LSTG parcels representing motor and temporal areas, respectively. Error bars represent standard error mean. The data underlying this figure can be found in https://osf.io/9fq47/. LSTG, left superior temporal gyrus.
Fig 4.
Speech-brain coupling for different delays during speaking.
The cortical map represents delays between speech envelope and brain activity where the coupling between both is maximal. Purple colours indicate negative delays (brain activity preceding speech) and green colours indicate positive delays (brain activity following speech). The data underlying this figure can be found in https://osf.io/9fq47/.
Fig 5.
Comparing speech-brain coupling between speaking and listening conditions.
(a) The correlation of lagged MI between speaking and listening for each parcel at delta (2 Hz) and theta (6 Hz). The colorbar illustrates the mean of Fisher Z-transformed correlation across participants. (b) The average of Fisher Z-transformed correlation of lagged MI across all parcels and delays at frequencies from 1 to 10 Hz. The data underlying this figure can be found in https://osf.io/9fq47/. MI, mutual information.
Fig 6.
Statistical comparison of speech-brain coupling in speaking versus listening.
(a) Statistical contrast of positive effect (speaking > listening). (b) Statistical contrast of negative effect (speaking < listening). (c) Frequency-delay profile of statistical contrast averaged over all significant t-values. (d) Spatial distribution of t-values at 5 Hz and 0 ms. Note that only the sum of significant t-values was plotted on inflated brain surfaces in a and b (p < 0.05). The data underlying this figure can be found in https://osf.io/9fq47/.
Fig 7.
(a) Significant connectivity between STG and other cortical parcels during speech production in theta and high gamma frequency bands. A cluster-based permutation test was used to detect significant connectivity patterns. Colour codes t-values. Purple colour represents the flow of information from STG to other cortical parcels and the green colour represents the opposite direction. (b) Significant connectivity patterns between STG and other cortical parcels during speech perception in theta and high gamma frequency bands. Analysis and colour coding corresponds to panel a. (c) Comparison of connectivity patterns between speaking and listening conditions in theta band. A cluster-based permutation test was used to detect significant connectivity differences from all the cortical parcels to STG between speaking and listening conditions. Colour codes t-values. (d) Individual spectrally resolved DAI between left motor cortex and LSTG as well as LP and LSTG. Note that only significant values were plotted on inflated brain surfaces (p < 0.05). The data underlying this figure can be found in https://osf.io/9fq47/. DAI, directed asymmetry index; LP, left parietal; LSTG, left superior temporal gyrus; STG, superior temporal gyrus.
Fig 8.
Low-frequency vs. high-frequency connectivity between all parcels and LSTG.
DAI values in the frequency range 0–30 Hz were compared to DAI values in the frequency range 60–90 Hz in speaking (a) and listening (b) conditions. Colour codes t-values. Purple colour represents stronger connectivity in high frequencies and green colour represents stronger connectivity in low frequencies. Note that only significant values were plotted on inflated brain surfaces (p < 0.05). The data underlying this figure can be found in https://osf.io/9fq47/. DAI, directed asymmetry index; LSTG, left superior temporal gyrus.
Fig 9.
Correlation analysis between top-down GC and MI.
(a) Speech-STG coupling in theta range (positively lagged: 130 ms) is negatively correlated with the top-down beta connectivity from bilateral motor areas and left frontal areas in speaking condition. This effect is largely absent in listening condition (b) as well as speaking condition with 0 ms lag (c). (d) Correlation analysis was conducted between top-down beta connectivity and speech-STG coupling in each frequency bin in theta range. The top-down beta connectivity from bilateral motor areas is negatively correlated with speech-STG coupling in lower theta band (4–6 Hz: first and second rows). However, this correlation was observed between top-down beta connectivity from left frontal area and speech-STG coupling in high theta band (6–8 Hz: third and fourth rows). (e) Top-down low beta (12–20 Hz) connectivity originating from bilateral motor areas are negatively correlated with low theta speech-STG coupling. However, top-down high beta (20–30 Hz) connectivity originating from the left frontal area is negatively correlated with speech-STG coupling in the high theta band. The data underlying this figure can be found in https://osf.io/9fq47/. MI, mutual information; STG, superior temporal gyrus.