Resting-state functional magnetic resonance imaging (fMRI) has provided converging descriptions of group-level functional brain organization. Recent work has revealed that functional networks identified in individuals contain local features that differ from the group-level description. We define these features as network variants. Building on these studies, we ask whether distributions of network variants reflect stable, trait-like differences in brain organization. Across several datasets of highly-sampled individuals we show that 1) variants are highly stable within individuals, 2) variants are found in characteristic locations and associate with characteristic functional networks across large groups, 3) task-evoked signals in variants demonstrate a link to functional variation, and 4) individuals cluster into subgroups on the basis of variant characteristics that are related to differences in behavior. These results suggest that distributions of network variants may reflect stable, trait-like, functionally relevant individual differences in functional brain organization.

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Recent work has demonstrated that individual-specific variations in functional networks (termed “network variants”) can be identified in individuals using resting state functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time, suggesting that they may be trait-like markers of individual differences in brain organization. However, while networks variants are reliable at rest, is is still untested whether they are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in task and rest states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

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European Americans are self-enhancing, whereas East Asians are sometimes self-critical. However, the mechanisms underlying this cultural difference remain unclear. Here, we addressed this gap by testing 32 Taiwanese and 32 American young adults, who indicated whether their self-esteem would change in various episodes involving success or failure. We monitored their electroencephalogram (EEG) and assessed upperalpha band power in response to the outcome information. An increase in upper-alpha power indicates internally directed attention; therefore, it is an index of self-referential processing when assessed during a judgment about the self. As predicted, Americans judged that their self-esteem (but not another's) would increase more after a success than it would decrease after a failure, thereby showing the previously observed self-enhancing pattern. Taiwanese tended to show the opposite pattern, self-criticism. Notably, Americans, but not Taiwanese, showed an increase in upper-alpha band power in response to the self's successes (vs. failures). This bias in the EEG index of self-referential processing predicted the cultural difference in selfenhancement (vs. criticism). The role of self-referential processing in self-enhancement is discussed.