Varieties of semantic cognition revealed through simultaneous decomposition of intrinsic brain connectivity and behaviour

Shared understanding of narratives is correlated with shared neural responses

Humans have a striking ability to infer meaning from even the sparsest and most abstract forms of narratives. At the same time, flexibility in the form of a narrative is matched by inherent ambiguity in its interpretation. How does the brain represent subtle, idiosyncratic differences in the interpretation of abstract and ambiguous narratives? In this fMRI study, subjects were scanned either watching a novel 7-min animation depicting a complex narrative through the movement of geometric shapes, or listening to a narration of the animation's social story. Using an intersubject representational similarity analysis that compared interpretation similarity and neural similarity across subjects, we found that the more similar two people's interpretations of the abstract shapes animation were, the more similar were their neural responses in regions of the default mode network (DMN) and fronto-parietal network. Moreover, these shared responses were modality invariant: the shapes movie and the verbal interpretation of the movie elicited shared responses in linguistic areas and a subset of the DMN when subjects shared interpretations. Together, these results suggest a network of high-level regions that are not only sensitive to subtle individual differences in narrative interpretation during naturalistic conditions, but also resilient to large differences in the modality of the narrative.

Similarity in functional brain architecture between rest and specific task modes: A model of genetic and environmental contributions to episodic memory

The ability to keep a mental record of specific past events, dubbed episodic memory (EM), is key to lifespan adaptation. Nonetheless, the neural mechanisms underlying its typical inter-individual variability remain poorly understood. To address this issue, we tested whether individual differences in EM could be predicted from levels of functional brain re-organization between rest and task modes relevant to the transformation of perceptual information into mental representations (relational processing, meaning extraction, online maintenance versus updating of bound perceptual features). To probe the trait specificity of our model, we included three additional core mental functions, processing speed, abstract reasoning, and cognitive control. Finally, we investigated the extent to which our proposed model reflected genetic versus environmental contributions to EM variability. Hypotheses were tested by applying graph theoretical analysis and structural equation modeling to resting state and task fMRI data from two samples of participants in the Human Connectome Project (Sample 1: N = 338 unrelated individuals; Sample 2: N = 268 monozygotic vs. dizygotic twins [134 same-sex pairs]). Levels of functional brain reorganization between rest and the scrutinized task modes, particularly relational processing and online maintenance of bound perceptual features, contributed substantially to variations in both EM and abstract reasoning (but not in cognitive control or processing speed) among the younger adults in our sample, implying a substantial neurofunctional overlap, at least during this life stage. Similarity in functional organization between rest and each of the scrutinized task modes drew on distinguishable neural resources and showed differential susceptibility to genetic versus environmental influences. Our results suggest that variability on complex traits, such as EM, is supported by neural mechanisms comprising multiple components, each reflecting a distinct pattern of genetic versus environmental contributions and whose relative importance may vary across typical versus psychopathological development.

Robust prediction of individual creative ability from brain functional connectivity

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

The default network and the combination of cognitive processes that mediate self-generated thought

Self-generated cognitions, such as recalling personal memories or empathizing with others, are ubiquitous and essential for our lives. Such internal mental processing is ascribed to the Default Mode Network, a large network of the human brain, though the underlying neural and cognitive mechanisms remain poorly understood. Here, we tested the hypothesis that our mental experience is mediated by a combination of activities of multiple cognitive processes. Our study included four functional MRI experiments with the same participants and a wide range of cognitive tasks, as well as an analytical approach that afforded the identification of cognitive processes during self-generated cognition. We showed that several cognitive processes functioned simultaneously during self-generated mental activity. The processes had specific and localized neural representations, suggesting that they support different aspects of internal processing. Overall, we demonstrate that internally directed experience may be achieved by pooling over multiple cognitive processes.