Studies of abnormal theory of mind (ToM) performance in adult patients with traumatic brain injury (TBI) have reported inconsistent results. Therefore, we conducted a meta-analysis to characterize ToM performance in adult patients with TBI. Random-effects models were employed to estimate the overall effect size and the differential effect sizes across different ToM aspects. Based on a sample of 28 studies (1031 patients and 865 healthy controls), the meta-analytic findings revealed that ToM was significantly impaired in adult patients with TBI compared to healthy controls (g = -1.13). Besides, patients with TBI showed significant impairments in individual ToM tasks, as well as for different stimulus modes and contents involved in these ToM tasks. A meta-regression indicated a positive association between ToM performance and Glasgow Coma Scale score. The results of the current meta-analysis suggest that the performance in ToM tasks may be a good predictor of functional outcomes in adults with TBI, which is important for the identification of targets for cognitive interventions and the development of useful training intervention programs.

Theory of mind in adults with traumatic brain injury: A meta-analysis.

Going beyond the literal meaning of language is key to communicative success. However, the mechanisms that support non-literal inferences remain debated. Using a novel meta-analytic approach, we evaluate the contribution of linguistic, social-cognitive, and executive mechanisms to non-literal interpretation. We identified 74 fMRI experiments (n = 1,430 participants) from 2001 to 2021 that contrasted non-literal language comprehension with a literal control condition, spanning ten phenomena (e.g., metaphor, irony, indirect speech). Applying the activation likelihood estimation approach to the 825 activation peaks yielded six left-lateralized clusters. We then evaluated the locations of both the individual-study peaks and the clusters against probabilistic functional atlases (cf. anatomical locations, as is typically done) for three candidate brain networks-the language-selective network (Fedorenko, Behr, & Kanwisher, 2011), which supports language processing, the Theory of Mind (ToM) network (Saxe & Kanwisher, 2003), which supports social inferences, and the domain-general Multiple-Demand (MD) network (Duncan, 2010), which supports executive control. These atlases were created by overlaying individual activation maps of participants who performed robust and extensively validated 'localizer' tasks that selectively target each network in question (n = 806 for language; n = 198 for ToM; n = 691 for MD). We found that both the individual-study peaks and the ALE clusters fell primarily within the language network and the ToM network. These results suggest that non-literal processing is supported by both i) mechanisms that process literal linguistic meaning, and ii) mechanisms that support general social inference. They thus undermine a strong divide between literal and non-literal aspects of language and challenge the claim that non-literal processing requires additional executive resources.

Papers