Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal–parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity

Status and the brain.

Social hierarchy is a fact of life for many animals. Navigating social hierarchy requires understanding one's own status relative to others and behaving accordingly, while achieving higher status may call upon cunning and strategic thinking. The neural mechanisms mediating social status have become increasingly well understood in invertebrates and model organisms like fish and mice but until recently have remained more opaque in humans and other primates. In a new study in this issue, Noonan and colleagues explore the neural correlates of social rank in macaques. Using both structural and functional brain imaging, they found neural changes associated with individual monkeys' social status, including alterations in the amygdala, hypothalamus, and brainstem--areas previously implicated in dominance-related behavior in other vertebrates. A separate but related network in the temporal and prefrontal cortex appears to mediate more cognitive aspects of strategic social behavior. These findings begin to delineate the neural circuits that enable us to navigate our own social worlds. A major remaining challenge is identifying how these networks contribute functionally to our social lives, which may open new avenues for developing innovative treatments for social disorders

Developmental maturation of the precuneus as a functional core of the default mode network

Efforts to map the functional architecture of the developing human brain have shown that connectivity between and within functional neural networks changes from childhood to adulthood. Although prior work has established that the adult precuneus distinctively modifies its connectivity during task versus rest states (Utevsky, Smith, & Huettel, 2014), it remains unknown how these connectivity patterns emerge over development. Here, we use fMRI data collected at two longitudinal time points from over 250 participants between the ages of 8 and 26 years engaging in two cognitive tasks and a resting-state scan. By applying independent component analysis to both task and rest data, we identified three canonical networks of interest—the rest-based default mode network and the task-based left and right frontoparietal networks (LFPN and RFPN, respectively)—which we explored for developmental changes using dual regression analyses. We found systematic state-dependent functional connectivity in the precuneus, such that engaging in a task (compared with rest) resulted in greater precuneus–LFPN and precuneus–RFPN connectivity, whereas being at rest (compared with task) resulted in greater precuneus–default mode network connectivity. These cross-sectional results replicated across both tasks and at both developmental time points. Finally, we used longitudinal mixed models to show that the degree to which precuneus distinguishes between task and rest states increases with age, due to age-related increasing segregation between precuneus and LFPN at rest. Our results highlight the distinct role of the precuneus in tracking processing state, in a manner that is both present throughout and strengthened across development