Functionally distinct language and Theory of Mind networks are synchronized at rest and during language comprehension

Abstract

Communication requires the abilities to generate and interpret utterances and to infer the beliefs, desires, and goals of others ("Theory of Mind"; ToM). These two abilities have been shown to dissociate: individuals with aphasia retain the ability to think about others' mental states; and individuals with autism are impaired in social reasoning, but their basic language processing is often intact. In line with this evidence from brain disorders, functional MRI (fMRI) studies have shown that linguistic and ToM abilities recruit distinct sets of brain regions. And yet, language is a social tool that allows us to share thoughts with one another. Thus, the language and ToM brain networks must share information despite being implemented in distinct neural circuits. Here, we investigated potential interactions between these networks during naturalistic cognition using functional correlations in fMRI. The networks were functionally defined in individual participants, in terms of preference for sentences over nonwords for language, and for belief inference over physical-event processing for ToM, with both a verbal and a nonverbal paradigm. Although, across experiments, interregion correlations within each network were higher than between-network correlations, we also observed above-baseline synchronization of blood oxygenation level-dependent signal fluctuations between the two networks during rest and story comprehension. This synchronization was functionally specific: neither network was synchronized with the executive control network (functionally defined in terms of preference for a harder over easier version of an executive task). Thus, coordination between the language and ToM networks appears to be an inherent and specific characteristic of their functional architecture. NEW & NOTEWORTHY Humans differ from nonhuman primates in their abilities to communicate linguistically and to infer others' mental states. Although linguistic and social abilities appear to be interlinked onto- and phylogenetically, they are dissociated in the adult human brain. Yet successful communication requires language and social reasoning to work in concert. Using functional MRI, we show that language regions are synchronized with social regions during rest and language comprehension, pointing to a possible mechanism for internetwork interaction.

Keywords: Theory of Mind; communication; fMRI; functional connectivity; language.

Fig. 1.

Sample trials from the functional localizer paradigms. Language: sentences were contrasted with sequences of pronounceable nonwords. ToM: vignettes about false mental states were contrasted with vignettes about false physical states, each followed by a true/false statement (see Richardson et al. 2018 for screenshots from the nonverbal ToM localizer). MD: harder and easier versions of a spatial working memory task (location memory) were contrasted, each followed by a two-alternative forced choice question and feedback.

Fig. 2.

Masks used to constrain the selection of subject-specific functional regions of interest in the three networks. Language (red): 1) LIFGorb, left inferior frontal gyrus, orbital portion; 2) LIFG; 3) LMFG, left middle frontal gyrus; 4) LAntTemp, left anterior temporal cortex; 5) LPostTemp, left posterior temporal cortex; 6) LAngG, left angular gyrus. ToM (green): 1) TPJ, temporoparietal junction; 2) DMPFC, dorsal medial prefrontal cortex; 3) MMPFC, middle medial prefrontal cortex; 4) VMPFC, ventral medial prefrontal cortex; 5) PC, posterior cingulate cortex and precuneus. MD (blue): 1) IFGop, IFG opercular portion; 2) MFG and 3) MFGorb, middle frontal gyrus and its orbital portion; 4) PrecG, precentral gyrus; 5) Insula; 6) SMA, supplementary motor area; 7) ParInf, inferior parietal cortex; 8) ParSup, superior parietal cortex; 9) ACC, anterior cingulate cortex.

Fig. 3.

Responses of each network’s functional regions of interest (fROIs) to its localizer conditions. Bars correspond to percent signal change, relative to rest, in response to the target and control conditions of each localizer. The responses were estimated with twofold across-runs cross-validation, so that the data used for response estimation were independent from the data used for fROI definition. See glossary.

Fig. 4.

Matrices for functional region of interest (fROI)-to-fROI correlations. The first column corresponds to experiments 1a (resting state), 1b (stories), and 2 [stories; multiple demand (MD) fROIs were not defined in that experiment because the MD localizer was not included]; the second column corresponds to experiments 3a [stories; theory of mind (ToM) fROIs defined by the verbal ToM localizer] and 3b (stories; ToM fROIs defined by the nonverbal ToM localizer). The half-matrix below the diagonal shows all correlations, the half-matrix above the diagonal highlights the significant ones (at P < 0.05, FDR corrected), with the nonsignificant ones colored in black. The order of the fROIs across rows and columns corresponds to the numbers used in Fig. 2; within each network, the regions are sorted by hemisphere (LH, left hemisphere; RH, right hemisphere). Qualitatively, these matrices illustrate our key findings: each of the three networks is internally integrated; the language and ToM network are further synchronized but dissociable. Neither the language nor the ToM network is correlated with the MD network.

Fig. 5.

Average within- and between-network correlations. Column 1 shows results from experiments 1a (resting state), 1b (stories), and 2 (stories). Column 2 shows experiment 3a [stories; theory of mind (ToM) functional regions of interest (fROIs) defined by the verbal ToM localizer], and 3b (stories; ToM fROIs defined by the nonverbal ToM localizer). Error bars are standard errors of the mean by participants. Black dots correspond to the individual participants’ values. Vertical curves are Gaussian fits to empirical null distributions. Significant correlations (Bonferroni-corrected within each experiment; see methods) are marked with asterisks.

Fig. 6.

Average correlations between the temporoparietal junction (rTPJ) theory of mind (ToM) functional region of interest (fROI) (the most mentalizing-selective component of the ToM network; Saxe and Powell 2006) and the rest of the ToM network, the left hemisphere (LH) language network, and the multiple demand (MD) network. The same convention is followed as in Fig. 5.

Fig. 7.

Comparison of between-network correlations for left hemisphere (LH) language regions and the theory of mind (ToM) network (bright yellow) versus right hemisphere (RH) language regions and the ToM network (pale yellow) for experiments 1a (rest), 1b (stories), and 2 (stories). The bright red and green bars show the same data as shown in Fig. 5. The pale red bar shows the average within-network correlation for the RH language functional regions of interest (fROIs). Error bars are standard errors of the mean by participants. Black dots correspond to the individual participants’ values. Vertical curves are Gaussian fits to empirical null distributions. The hypothesis that RH language regions play a special role in pragmatic, ToM-based inference predicts stronger correlations between RH language regions and the ToM network (compared with the LH language regions and the ToM network). This prediction was not supported in any of our experiments.

Fig. 8.

Results of hierarchical clustering for experiment 1a, resting state (left) and experiment 1b, story comprehension (right). Hierarchical clustering creates a binary tree where branch length (horizontal lines) corresponds to the similarity (here, average correlation across participants) between functional regions of interest (fROIs). The color of the dots on the y-axis represents our a priori assignment of fROIs to networks: multiple demand (MD; blue), language (red), and theory of mind (ToM; green). Above each tree diagram, modularity is plotted for all fROI partitions in the tree. Each point in the modularity plot corresponds to a partition: an imaginary vertical line drawn from a location where two fROIs or clusters of fROIs connect to form a higher-level cluster. The dashed lines represent the points of maximum modularity, which correspond to a partition into networks. During resting state, maximum modularity is at a partition into three clusters: MD (blue lines), language (red lines), and ToM (green lines). All fROIs are correctly assigned to clusters, apart from the right IFG language fROI at rest, assigned to the MD network and the bilateral angular gyrus (AngG) language fROIs which were assigned to the ToM network, despite being defined with the language localizer. During story comprehension, maximum modularity is at a two-partite division: an MD cluster (blue) and a language-ToM cluster (yellow). Within the latter, fROIs mostly remain segregated into language and ToM fROIs, except for the left angular gyrus (AngG) language fROI. See glossary.

Fig. 9.

Matrices for functional region of interest (fROI)-to-fROI correlations for the two exploratory conditions: experiment 3c, dialogue and experiment 3d, low-ToM-content text. Same convention is followed as in Fig. 4 as well as the same statistical procedure for determining the significance of correlations. Qualitatively, these matrices illustrate that the resting state and story comprehension results extend to another naturalistic linguistic stimulus rich in mental state attribution (experiment 3c), whereas a naturalistic stimulus low in mental state content does not elicit reliable language-theory of mind (ToM) synchronization (experiment 3d).

Fig. 10.

Average within- and between-network correlations for the two exploratory conditions: experiment 3c, Dialogue and experiment 3d, low-theory of mind (ToM)-content text. The same convention is followed as in Fig. 5.