Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts

<span title="2020-04-10">2020</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="" style="color: black;">NeuroImage</a> </i> &nbsp;
Reading a book, understanding the news reports or any other behaviour involving the processing of meaningful stimuli requires the semantic system to have two main features: being active during an extended period of time and flexibly adapting the internal representation according to the changing environment. Despite being key features of many everyday tasks, formation and updating of the semantic "gestalt" are still poorly understood. In this fMRI study we used naturalistic stimuli and task
more &raquo; ... ulations to identify the neural network that forms and updates conceptual gestalts during time-extended integration of meaningful stimuli. Univariate and multivariate techniques allowed us to draw a distinction between networks that are crucial for the formation of a semantic gestalt (meaning integration) and those that instead are important for linking incoming cues about the current context (e.g., time, space cues) into a schema representation. Specifically, we revealed that time-extended formation of the conceptual gestalt was reflected in the neuro-computations of the anterior temporal lobe accompanied by multi-demand areas and hippocampus, with a key role of brain structures in the right hemisphere. This "semantic gestalt network" was strongly recruited when an update of the current semantic representation was required during narrative processing. A distinct fronto-parietal network, instead, was recruited for context integration, independently from the meaning associations between words (semantic coherence). Finally, in contrast with accounts positing that the default-mode-network (DMN) may have a crucial role in semantic cognition, our findings revealed that DMN activity was sensitive to task difficulty, but not to semantic integration. The implications of these findings for neurocognitive models of semantic cognition and the literature on narrative processing are discussed.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1016/j.neuroimage.2020.116802</a> <a target="_blank" rel="external noopener" href="">pmid:32283276</a> <a target="_blank" rel="external noopener" href="">pmcid:PMC7573538</a> <a target="_blank" rel="external noopener" href="">fatcat:h3j265d22jb47jy2ryyiec6eo4</a> </span>
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