A large literature in social neuroscience has associated the medial prefrontal cortex (mPFC) with the processing of self-related information. However, only recently have social neuroscience studies begun to consider the large behavioral literature showing a strong self-positivity bias, and these studies have mostly focused on its correlates during self-related judgments and decision making. We carried out a functional MRI (fMRI) study to ask whether the mPFC would show effects of the self-positivity bias in a paradigm that probed participants’ self-concept without any requirement of explicit self-judgment. We presented social vignettes that were either self-relevant or non-self-relevant with a neutral, positive, or negative outcome described in the second sentence. In previous work using event-related potentials, this paradigm has shown evidence of a self-positivity bias that influences early stages of semantically processing incoming stimuli. In the present fMRI study, we found evidence for this bias within the mPFC: an interaction between self-relevance and valence, with only positive scenarios showing a self vs other effect within the mPFC. We suggest that the mPFC may play a role in maintaining a positively-biased self-concept and discuss the implications of these findings for the social neuroscience of the self and the role of the mPFC.
Presuppositions convey information that comprehenders assume to be true, even when it is tangential to the communicator’s main message. For example, a class of verbs called ‘factives’ (e.g. realize, know) trigger the presupposition that the events or states conveyed by their sentential complements are true. In contrast, non-factive verbs (e.g. think, believe) do not trigger this presupposition. We asked whether, during language comprehension, presuppositions triggered by factive verbs are encoded within the comprehender’s discourse model, with neural consequences if violated by later bottom-up inputs. Using event-related potentials (ERPs), we examined neural activity to words that were either consistent or inconsistent with events/states conveyed by the complements of factive versus non-factive verbs while comprehenders read and actively monitored the coherence of short discourse scenarios. We focused on the modulation of a posteriorly-distributed late positivity or P600. This ERP component is produced when comprehenders constrain their discourse model such that it restricts predictions only to event structures that are compatible with this model, and new input violates these event structure predictions. Between 500-700ms, we observed a larger amplitude late posterior positivity/P600 on words that were inconsistent (versus consistent) with the events/states conveyed by the complements of factive verbs. No such effect was observed following non-factive verbs. These findings suggest that, during active discourse comprehension, the presuppositions triggered by factive verbs are encoded and maintained within the comprehender’s discourse model. Downstream input that is inconsistent with these presuppositions violates event structure predictions and conflicts with this prior model, producing the late posterior positivity/P600.
It has been hypothesized that schizophrenia is characterized by overly broad automatic activity within lexico-semantic networks. We used two complementary neuroimaging techniques, Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI), in combination with a highly automatic indirect semantic priming paradigm, to spatiotemporally localize this abnormality in the brain. Eighteen people with schizophrenia and 20 demographically-matched control participants viewed target words (“bell”) preceded by directly related (“church”), indirectly related (“priest”), or unrelated (“pants”) prime words in MEG and fMRI sessions. To minimize top-down processing, the prime was masked, the target appeared only 140ms after prime onset, and participants simply monitored for words within a particular semantic category that appeared in filler trials. Both techniques revealed a significantly larger automatic indirect priming effect in people with schizophrenia than in control participants. MEG temporally localized this enhanced effect to the N400 time window (300-500ms) — the critical stage of accessing meaning from words. fMRI spatially localized the effect to the left temporal fusiform cortex, which plays a role in mapping of orthographic word-form on to meaning. There was no evidence of an enhanced automatic direct semantic priming effect in the schizophrenia group. These findings provide converging neural evidence for abnormally broad highly automatic lexico-semantic activity in schizophrenia. We argue that, rather than arising from an unconstrained spread of automatic activation across semantic memory, this broader automatic lexico-semantic activity stems from looser connections between the form and meaning of words.
When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) – a direct neural measure of semantic processing. N400 modulation is observed even when the context is a single semantically related “prime” word. This so-called “N400 semantic priming effect” is sensitive to the probability of encountering a related prime-target pair within an experimental block, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using a Bayesian learning model that estimates and updates the probability of encountering a related versus an unrelated prime-target pair on each successive trial. We found that our model’s trial-by-trial estimates of target word probability accounted for significant variance in the amplitude of the N400 evoked by target words. These findings suggest that Bayesian principles contribute to how comprehenders adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing.