Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model [Chen, M., & Deem, M. W. 2015. Development of modularity in the neural activity of children's brains. Physical Biology, 12, 016009] suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals' modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole-brain organization from network neuroscience to cognitive processing.

Bilingualism represents an interesting model of possible experience-dependent alterations in brain structure. The current study examines whether interhemispheric adaptations in brain structure are associated with bilingualism. Corpus callosum volume and cortical thickness asymmetry across 13 regions of interest (selected to include critical language and bilingual cognitive control areas) were measured in a sample of Spanish-English bilinguals and age- and gender-matched monolingual individuals (N = 39 per group). Cortical thickness asymmetry of the anterior cingulate region differed across groups, with thicker right than left cortex for bilinguals and the reverse for monolinguals. In addition, two adjacent regions of the corpus callosum (mid-anterior and central) had greater volume in bilinguals. The findings suggest that structural indices of interhemispheric organization in a critical cognitive control region are sensitive to variations in language experience.

Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model (Chen & Deem, 2015) suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals’ modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole brain organization from network neuroscience to cognitive processing.

In cognitive network neuroscience, the connectivity and community structure of the brain network is related to measures of cognitive performance, like attention and memory. Research in this emerging discipline has largely focused on two measures of connectivity—modularity and flexibility—which, for the most part, have been examined in isolation. The current project investigates the relationship between these two measures of connectivity and how they make separable contribution to predicting individual differences in performance on cognitive tasks. Using resting state fMRI data from 52 young adults, we show that flexibility and modularity are highly negatively correlated. We use a Brodmann parcellation of the fMRI data and a sliding window approach for calculation of the flexibility. We also demonstrate that flexibility and modularity make unique contributions to explain task performance, with a clear result showing that modularity, not flexibility, predicts performance for simple tasks and that flexibility plays a greater role in predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.

Bilingual language control may involve cognitive control, including inhibition and switching. These types of control have been previously associated with neural activity in the inferior frontal gyrus (IFG) and the anterior cingulate cortex (ACC). In previous studies, the DRD2 gene, related to dopamine availability in the striatum, has been found to play a role in neural activity during cognitive control tasks, with carriers of the gene’s A1 allele showing different patterns of activity in inferior frontal regions during cognitive control tasks than non-carriers. The current study sought to extend these findings to the domain of bilingual language control. Forty-nine Spanish-English bilinguals participated in this study by providing DNA samples through saliva, completing background questionnaires, and performing a language production task (picture-naming), a non-verbal inhibition task (Simon task), and a non-verbal switching task (shape-color task) in the fMRI scanner. The fMRI data were analyzed to determine whether variation in the genetic background or bilingual language background predicts neural activity in the IFG and ACC during these three tasks. Results indicate that genetic and language background variables predicted neural activity in the IFG during English picture naming. Variation in only the genetic background predicted neural activity in the ACC during the shape-color switching task; variation in only the language background predicted neural activity in the ACC and IFG during the Simon task. These results suggest that variation in the DRD2 gene should not be ignored when drawing conclusions about bilingual verbal and non-verbal cognitive control.