Functionally distinct language and Theory of Mind networks work together, especially during language comprehension

Abstract

Communication requires the ability to generate and interpret linguistic signals, as well as the ability to infer the beliefs, desires, and goals of others (“Theory of Mind”, ToM). These two abilities have been shown to dissociate: on the one hand, individuals with severe aphasia retain the ability to think about others’ mental states; on the other hand, individuals with autism spectrum disorders are impaired in their social reasoning, but their basic language processing is often intact. In line with this evidence from developmental and acquired disorders, fMRI studies have shown that linguistic and ToM abilities are implemented in distinct sets of brain regions. And yet, language is fundamentally a social tool that allows us to share thoughts with one another. Thus, the language and ToM networks should work closely together in spite of being implemented in distinct neural circuits. Here, we investigated potential interactions between these networks during naturalistic cognition using the functional correlation approach in fMRI. Although inter-region correlations within each network were higher than between-network correlations across experiments, we also observed reliably above-baseline synchronization of BOLD signal fluctuations between the two networks during rest and, to an even greater extent, during story comprehension. This synchronization was functionally specific: neither network synchronized with the executive control network. Thus, coordination between the language and ToM networks appears to be an inherent characteristic of their functional architecture, and is increased during naturalistic language processing.

A robust dissociation among the language, multiple demand, and default mode networks: Evidence from inter-region correlations in effect size

“…If these effect size measures reflect some highly general properties, like the degree of brain vascularization or fluid intelligence levels, then all three networks should co-vary in these measures across individuals. However, if these measures are sensitive tofunctional dissociations among distinct brain networks, we expect the language and MD networks to show little co-variation in these measures across participants, consistent with prior studies (e.g., Fedorenko et al, 2011; Fedorenko et al, 2012; Blank et al, 2014; Blank & Fedorenko, 2017; Paunov et al, in revision). Critically, if effect size measures indeed respect such functional distinctions, then the degree to which the language and DMN regions co-vary across individuals could indicate the extent of functional association between these two networks.…”

“…To do so, we (a) characterized the functional response profiles of each network, and (b) employed a novel analytic approach that tested, across participants, the correlations in response magnitude among the fROIs within each network vs. between networks. Using both analyses, we replicate the dissociation between the language and MD networks (e.g., Fedorenko et al, 2011; Fedorenko et al, 2013; Blank et al, 2014; Paunov et al, in revision), as well as the well-established dissociation between the MD network and the DMN. Critically, we further demonstrate that the language network is also robustly dissociable from the DMN: the former, but not the latter responds strongly during language processing and, whereas regional effect sizes strongly co-vary across individuals within each network, the correlation between the two networks is much weaker.…”

“…Second, language and MD regions show distinct patterns of fluctuations in neural activity during naturalistic cognition. For example, Blank et al (2014; replicated in Paunov et al, in revision) compared fluctuations in the fMRI BOLD signal across language and MD regions either during “rest” or while participants listened to stories. In both conditions, the average pairwise correlations among language regions (see also Hampson et al, 2002; Turken and Dronkers, 2011; Yue et al, 2013) and among MD regions (see also Dosenbach et al, 2007; Seeley et al, 2007; Hampshire et al, 2012) were significantly higher than correlations between pairs of regions straddling the two networks, which were close to zero.…”

The domain-general multiple demand (MD) network does not support core aspects of language comprehension: a large-scale fMRI investigation

“…In all the critical analyses reported here, we treat the MD fROIs as a functionally integrated system given that prior work has established that these regions not only share functional profiles, but also that the MD regions' time-courses are strongly correlated during both rest and task performance (e.g., Blank et al, 2014;Paunov et al, 2019), and the effect sizes in task-based paradigms correlate strongly across participants (Mineroff et al, 2018;Assem et al, 2019). However, we acknowledge the possibility that subdivisions may exist within this network (e.g., Blank et al, 2014;Paunov et al, 2019). And treating this network as an integrated system need not imply that all of its regions are identical in their response patterns and functions.…”

“…Converging evidence from neuroimaging and patient studies suggests that a leftlateralized fronto-temporal brain network is selective for language processing. These regions respond to linguistic input (visual or auditory) across diverse materials and tasks (e.g., Fedorenko et al, 2010Vagharchakian et al, 2012;Scott et al, 2017;Deniz et al, 2019), but not to non-linguistic cognitive tasks, like arithmetic calculations, executive function tasks, music perception, action/gesture observation, and non-verbal social information (e.g., Fedorenko et al, 2011;Monti et al, 2012;Pritchett et al, 2018;Jouravlev et al, 2019;Paunov, 2019;see Fedorenko & Varley, 2016, for a review).…”